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This study investigated the effects of site quality and stand density on the growth and timber grade structure of Chinese fir plantations in the Rongjiang Basin of Guangxi, China. Chinese fir plantations with different site conditions were selected. A tending experiment was performed on these plantations;growth and timber grade structure data were acquired and analyzed. Improvement in site quality significantly enhanced stand height, diameter at breast height, stand volume, medium-diameter timber yield, and timber dimensions. The tree height and medium-diameter timber yield increased as the site index increased. The higher the site index, the earlier the formation and the higher the yield of large-diameter timber. At this age stage (13 years), the trees in the stand were mainly distributed in three diameter classes of 14, 16 cm, and 18 cm. A decrease in stand density resulted in significant reduction in both the proportion of trees ≤14 cm in diameter and the output rate of small-diameter timber and significant increase in the proportion of trees ≥20 cm in diameter and the output rate of medium-diameter timber. Stand volume decreased with decreasing stand density, but the output of timber dimensions showed an increasing trend. [ABSTRACT FROM AUTHOR]

Assessing the quality of forest sites is crucial for evaluating the potential productivity of forests and formulating effective management strategies. Therefore, it is essential to understand how environmental variables affect the site quality. This study focuses on quantifying the effects of 44 different environmental variables including climate, topography, and soil properties on the site index of Larix kaempferi plantations in three different climate regions in China, utilizing the random forest algorithm. L. kaempferi site index was determined fromstemanalysis data by felling dominant trees from51 even-aged stands. The results indicated that the proposed random forest model explained ~59.47% of site index variations. Among many environmental variables, available phosphorus, pH, degree-days above 5°C (DD5), and spring mean maximum temperature (Tmax_MAM) had significant effects on the site index (P < 0.05), and the importance of soil chemical properties generally exhibits relatively larger effects on the site index than climate variables and topography variables. The partial dependence analysis revealed that the L. kaempferi plantations had maximum values at ~30 mg/kg of available phosphorus in the first soil layers, 30 mg/kg of available phosphorus in the second soil layers, 20 mg/kg of available phosphorus in the third soil layers, the DD5 between 2,600and 3,000°C, and Tmax_MAM ~15°C. Our findings attempt to provide a better understanding of the site-growth relationship. [ABSTRACT FROM AUTHOR]

In this work, we present a study about the application of bi-temporal, large interval aerial laser scans for constructing of tree growth models and estimating site index quality based on the measured increments from the laser scans. We compared two LiDAR scans with 14 years of difference in the national park area, where most areas are unmanaged. We derived the increment curve based on the Chapman-Richard growth formula. We used site index estimates from forest management plans from the national scale as the ground truth (both absolute and relative). We constructed three predictive models for site index estimates from bi-temporal scans, in modalities with and without stand age. Including the stand age improved all models, but even without the age, the models performed relatively well for differentiation between better and worse sites. At this moment, it is not directly possible to estimate age from remotely sensed data, but consistent monitoring, with laser scanning or photogrammetry, undoubtedly detects the harvest or dieback, so in the future, age can be considered as a variable easily estimated from remotely sensed data and so remote sensed material are viable source for understanding of forest growth and production. [ABSTRACT FROM AUTHOR]

Local terrain or microsite conditions influence the development of trees, particularly at early ages. These conditions might be described by edaphic or topographic variables. We mapped soil and topographic variables from four even-aged and even-spaced cork oak plantations located in two climatically distinct Portuguese regions. The major goal of this research was to understand the relation between soil and topographic fine-scale conditions and tree growth expressed by diameter without cork annual growth (idu). The methodology consisted in (1) analysing the spatial variability and autocorrelation of idu; (2) modelling idu with ordinary least squares (OLS) regressions; (3) comparing with spatial modelling of idu, incorporating spatial autocorrelation. The driest stands A and B, exhibited weaker spatial autocorrelation, distributed in smaller clusters (R2 < 0.03, OLS models), while stands C (R2 = 0.18, OLS models) and D (R2 = 0.11, OLS models) showed higher predictive capacity. Spatial models increased R2 scores, keeping most variables from OLS models and accounting for spatial autocorrelation. A + B + C + D OLS model obtained an R2 = 0.34 and respective spatial model R2 = 0.58. Apparent electrical conductivity at 0.5 (ECa0.5) and 1 m of soil depth, slope, elevation and topography position index were included as predictors (OLS), but only ECa0.5, slope and elevation were selected in the spatial model. Models were fitted using average to high productivity stands and should be used cautiously outside this range. Local terrain conditions determine the growth of young cork oak trees. Mapping soil and topographic variables before establishing new plantations may identify limiting microsite conditions where using cork oak species is not suitable due to low growth rates expectations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The stand basal area, closely related to age, site quality, and stand density, is an important factor for predicting forest growth and yield. The accurate estimation of site quality is especially a key component in the stand basal area model. We utilized sample plots with Picea asperata Mast. as the dominant species in the multi-period National Forest Inventory (NFI) dataset to establish a site index (SI) model including climate effects through the difference form of theoretical growth equations and mixed-effects models. We combined the SI calculated from the SI model, stand age, and stand density index to construct a basal area growth model for Picea asperata Mast. stands. The results show that the Korf model is the best SI base model for Picea asperata Mast. The mean temperatures in summer and winter precipitation were used as the fixed parameters to construct a nonlinear model. Ultimately, elevation, origin, and region, as random effects, were incorporated into the mixed-effects model. The coefficients (R2) of determination of the base model, the nonlinear model including climate, and the nonlinear mixed-effects model are 0.869, 0.899, and 0.921, with root-mean-square errors (RMSEs) of 1.320, 1.315, and 1.301, respectively. Among the basal area models, the Richards model has higher precision. And the basal area model including an SI incorporating climatic factors had a higher determination coefficient (R2) of 0.918 than that of the model including an SI without considering climatic effects. The mixed-effects model incorporating climatic and topographic factors shows a better fitting performance of SI, resulting in a higher precision of the basal area model. This indicates that in the development of forest growth models, both biophysical and climatic factors should be comprehensively considered. [ABSTRACT FROM AUTHOR]

Optimizing forest plantation management has become imperative due to increasing forest product demand, higher fertilization and management costs, declining land availability, increased competition for land use, and the growing demands for carbon sequestration. Precision forestry refers to the ability to use data acquired with technology to support the forest management decision-making process. LiDAR can be used to assess forest metrics such as tree height, topographical position, soil surface attributes, and their combined effects on individual tree growth. LiDAR opens the door to precision silviculture applied at the tree level and can inform precise treatments such as fertilization, thinning, and herbicide application for individual trees. This study uses ALS LiDAR and other ancillary data to assess the effect of scale (i.e., stand, soil type, and microtopography) on dominant height and site index measures within loblolly pine plantations across the southeastern United States. This study shows differences in dominant height and site index across soil types, with even greater differences observed when the interactions of microtopography were considered. These results highlight how precision forestry may provide a unique opportunity for assessing soil and microtopographic information to optimize resource allocation and forest management at an individual tree scale in a scarce higher-priced fertilizer scenario. [ABSTRACT FROM AUTHOR]

This study examines the relationship between Brutian pine productivity and plant species diversity, focusing on its potential as a valuable resource. Data was collected from 101 natural Brutian pine stands in Muğla and Antalya through inventory studies. Age and height values were recorded for three selected Brutian pine trees in each plot, along with plant species diversity using the Braun-Blanquet scale. Site index values were used to assign productivity scores between 1 and 5 for each plot. Diversity values were adjusted to a scale of 1 to 9 according to Westhoff and Maarel (1973) to calculate alpha diversity indices (Shannon and Simpson) using BİÇEB software. Environmental variables such as elevation, slope, radiation index, annual mean temperature, and annual precipitation were also collected for further analysis. The Kolmogorov-Smirnov normality test was first applied to the data matrix. Since it was determined that the normality assumption was not met (p

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The South American Andes are a set of mountains that generate a diversity of climates. Eucalyptus globulus has been planted on many slopes of the northern Peruvian Andes at high altitudes (for example, in Cajamarca, Peru), but its growth and productive viability remain unknown. In the present study, the following objectives were established: i) to develop Site Index curves for stands of Eucalyptus globulus located in the Peruvian Andes above 3,000 meters of altitude, ii) to analyze the relationship between environmental variables and Site Index, and iii) to evaluate the potential effect of cold on the growth of these stands compared to those in other regions. The Site Index (SI) was estimated using three base growth models (Bertalanffy-Richards, Hossfeld and Korf) and two derivation methods (Algebraic Differences - ADA and Generalized Algebraic Differences - GADA). The relationship between environmental factors and SI was determined by Spearman's correlation coefficient. The potential effect of altitude was evaluated by comparing the site quality curves obtained with those of other regions. The dynamic equation, derived from the Bertalanffy-Richards model using GADA, explained much of the variability of the dominant height growth. The SI was well correlated with distance to water bodies and to a lesser degree with solar radiation, effective depth and base saturation. In addition, compared to other regions, slow growth was evident in the initial stage of planting, probably due to the effect of cold acclimatization (derived from the high altitude). [ABSTRACT FROM AUTHOR]

Compatible model systems were developed for estimating fuel load dynamics in Ulex europaeus (gorse) and in Erica australis (Spanish heath) dominated shrub communities at stand level. The models were based on intensive, detailed destructive field sampling and were fitted simultaneously to fulfill the additivity principle. The models enable, for the first time, estimation of the biomass dynamics of the total shrub layer, size fractions and vegetative stage, with reasonably good accuracy. The approach used addresses the high variability in shrub biomass estimates by using a site index (SI) based on biomass levels at a reference age of 10 years. Analysis of the effect of climatic variables on site index confirmed the preference of gorse for mild temperatures and the ability of high heath communities to tolerate a wider range of temperatures. In the gorse communities, SI tended to increase as summer rainfall and the mean temperature of the coldest month increased. However, in the heath communities, no relationships were observed between SI and any of the climatic variables analyzed. The study findings may be useful for assessing and monitoring fuel hazards, updating fuel mapping, planning and implementing fuel reduction treatments and predicting fire behavior, among other important ecological and biomass use-related applications. [ABSTRACT FROM AUTHOR]

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.

The stand basal area, closely related to age, site quality, and stand density, is an important factor for predicting forest growth and yield. The accurate estimation of site quality is especially a key component in the stand basal area model. We utilized sample plots with Picea asperata Mast. as the dominant species in the multi-period National Forest Inventory (NFI) dataset to establish a site index (SI) model including climate effects through the difference form of theoretical growth equations and mixed-effects models. We combined the SI calculated from the SI model, stand age, and stand density index to construct a basal area growth model for Picea asperata Mast. stands. The results show that the Korf model is the best SI base model for Picea asperata Mast. The mean temperatures in summer and winter precipitation were used as the fixed parameters to construct a nonlinear model. Ultimately, elevation, origin, and region, as random effects, were incorporated into the mixed-effects model. The coefficients (R2) of determination of the base model, the nonlinear model including climate, and the nonlinear mixed-effects model are 0.869, 0.899, and 0.921, with root-mean-square errors (RMSEs) of 1.320, 1.315, and 1.301, respectively. Among the basal area models, the Richards model has higher precision. And the basal area model including an SI incorporating climatic factors had a higher determination coefficient (R2) of 0.918 than that of the model including an SI without considering climatic effects. The mixed-effects model incorporating climatic and topographic factors shows a better fitting performance of SI, resulting in a higher precision of the basal area model. This indicates that in the development of forest growth models, both biophysical and climatic factors should be comprehensively considered.

Optimizing forest plantation management has become imperative due to increasing forest product demand, higher fertilization and management costs, declining land availability, increased competition for land use, and the growing demands for carbon sequestration. Precision forestry refers to the ability to use data acquired with technology to support the forest management decision-making process. LiDAR can be used to assess forest metrics such as tree height, topographical position, soil surface attributes, and their combined effects on individual tree growth. LiDAR opens the door to precision silviculture applied at the tree level and can inform precise treatments such as fertilization, thinning, and herbicide application for individual trees. This study uses ALS LiDAR and other ancillary data to assess the effect of scale (i.e., stand, soil type, and microtopography) on dominant height and site index measures within loblolly pine plantations across the southeastern United States. This study shows differences in dominant height and site index across soil types, with even greater differences observed when the interactions of microtopography were considered. These results highlight how precision forestry may provide a unique opportunity for assessing soil and microtopographic information to optimize resource allocation and forest management at an individual tree scale in a scarce higher-priced fertilizer scenario.

The present study aims to identify the relations between the wood production (m3 per year) of the black pine (Pinus nigra Arnold.) and its habitat characteristics in the Eastern Mediterranean Region. A total of 120 samplings with different aspects, site altitudes, and site classes were studied. In each sample area, at least 5 trees were designated, and soil samples were taken by excavating earth pits. Certain characteristics of the soil samples were identified in the laboratory environment. The relations between the dominant height values of the trees in the sample areas and soil, climate, and physiographic factors were analyzed using correlation analysis, multiple regression analysis, and artificial neural network methods. Significant relations between the wood production values of the trees in the sample areas and slope from physiographic habitat characteristics, average annual temperature from climate characteristics, and pH and total carbonate from soil characteristics were found. The wood production of black pine was explained by multiple regression analysis at a level of 22.4% and by artificial neural network method at 72%.

Carbon sequestration has become an important source of supplementary revenue from forest plantations. Although there are many financial comparisons of species based on timber revenue, there have been few regional comparisons that integrate revenue from carbon. Within New Zealand, radiata pine is the most widely planted species, but there has been a recent upsurge in planting rates for coast redwood. Under New Zealand's Emissions Trading Scheme, areas that are newly afforested under clear-fell rotational forestry receive carbon payments up to a set age, intended to represent the long-term average under successive rotations. Using growth models for both species, the objectives of this research were to regionally quantify (i) how the rotation length and the carbon averaging age influenced the profitability of growing redwood and (ii) compare carbon, timber yields, and profitability between radiata pine and redwood. The results showed the legislated carbon averaging age of 22 years for redwood underestimated the actual mid-points of carbon accumulation, which averaged 26, 28, and 31 years across rotation lengths of 40, 45, and 50 years, respectively. The optimal rotation length for redwood varied markedly by region and carbon price but was most often 40 years, increasing to 50 years at higher carbon prices, particularly for southern regions. Under regimes where revenue was only derived from timber, the redwood internal rate of return (IRR) exceeded that of radiata pine for eight of the nine New Zealand regions. When revenue was received from carbon and timber, redwood had a higher IRR than radiata pine up to carbon prices ranging from 29 to 50 NZD/tonne CO2 for the North Island and 23 to 34 NZD/tonne CO2 in all South Island regions apart from Otago. The IRR of radiata pine exceeded that of redwood at carbon prices above these values for the eight regions and at all carbon prices within the cold, dry Otago region. [ABSTRACT FROM AUTHOR]

This study addresses how site index may affect crown shape by developing a crown shape regression model for the planted L. kaempferi at high altitudes in the subtropical climate of China. A total of 9241 branches from 78 trees, including 39 dominant trees and 39 intermediate trees, were measured in Hubei Province, southern China. The branch characteristics, including branch length, branch angle, and branch chord length of all living branches, were measured by felling trees. The models that showed good performance in crown shape modeling were used and compared in the present study. The goodness of fit statistics and stability of parameter estimation of the modified Kozak equation were better than those of the segmented polynomial equation. A nonlinear mixed-effect crown shape model was developed based on the modified Kozak equation. In addition to the tree level variables of diameter at the breast height (DBH), crown ratio (CR), and tree height-to-DBH ratio, an attempt was made to incorporate the site index into the crown shape model for the planted L. kaempferi. However, the site index was not a significant variable in the crown shape model. The purpose of our study was to lay the foundation for further study of the growth of the trees and the effects of crown morphology on stem growth in the future. [ABSTRACT FROM AUTHOR]

Site quality evaluation is an important foundation for decision-making and planning in forest management and provides scientific decision support and guidance for the sustainable development of forests and commercial plantations. Site index and site form models were constructed and subsequently compared utilizing fir (Cunninghamia lanceolata) plantations in Nanping City, Fujian Province, China. This papers aim was to construct a site quality classification model, conduct further analysis on the effects of different site factors on the quality of the site, and achieve an assessment of site quality for Chinese fir plantations. An algebraic difference approach was used to establish a site index model and a site form model for Chinese fir in Fujian Province. The suitability of the two models was compared using model accuracy analysis and partial correlation, and the optimal model was chosen for classifying the site quality of the stands. On this basis, a site quality classification model was established using the random forest algorithm, and the importance of each site factor was determined through importance ranking in terms of their impact on site quality. Within the study area, the R2 of the site index model results was 0.581, and the R2 values of the five site form models based on different reference breast diameters, ranked from high to low, were 0.894, 0.886, 0.884, 0.880, and 0.865. The bias correlation coefficient between site form and stand volume was 0.71, and the bias correlation coefficient between site index and stand volume was 0.52. The results confirmed that the site form model is better suited for evaluating the site quality of Chinese fir plantations. The random forest-based site form classification model had a high classification accuracy with a generalization accuracy of 0.87. The factors that had the greatest impact on site form were altitude, canopy closure, and slope gradient, whereas landform had the smallest impact on site form. These results can provide a reference for the evaluation of the site quality of plantations and natural forests in southern China to ensure the long-term sustainable use of forest resources. [ABSTRACT FROM AUTHOR]

Site index and stand age are important variables in forestry. Site index describes the growing potential at a given location, expressed as the height that trees can attain at a given age under favorable growing conditions. It is traditionally used to classify forests in terms of future timber yield potential. Stand age is used for the planning of management activities such as thinning and harvest. SI has previously been predicted using remote sensing, but usually relying on either very short time series or repeated ALS acquisitions. In this study, site index and forest stand age were predicted from time series of interferometric TanDEM-X data spanning seven growth seasons in a hemi-boreal forest in Remningstorp, a test site located in southern Sweden. The goal of the study was to see how satellite-based radar time series could be used to estimate site index and stand age. Compared to previous studies, we used a longer time series and applied a penetration depth correction to the phase heights, thereby avoiding the need for calibration using ancillary field or ALS data. The time series consisted of 30 TanDEM-X strip map scenes acquired between 2011 and 2018. Established height development curves were fitted to the time series of TanDEM-X-based top heights. This enabled simultaneous estimation of both age and site index on 91 field plots with a 10 m radius. The RMSE of predicted SI and age were 6.9 m and 38 years for untreated plots when both SI and age were predicted. When predicting SI and the age was known, the RMSE of the predicted SI was 4.0 m. No significant prediction bias was observed for untreated plots, while underestimation of SI and overestimation of age increased with the intensity of treatment. [ABSTRACT FROM AUTHOR]

Compatible model systems were developed for estimating fuel load dynamics in Ulex europaeus (gorse) and in Erica australis (Spanish heath) dominated shrub communities at stand level. The models were based on intensive, detailed destructive field sampling and were fitted simultaneously to fulfill the additivity principle. The models enable, for the first time, estimation of the biomass dynamics of the total shrub layer, size fractions and vegetative stage, with reasonably good accuracy. The approach used addresses the high variability in shrub biomass estimates by using a site index (SI) based on biomass levels at a reference age of 10 years. Analysis of the effect of climatic variables on site index confirmed the preference of gorse for mild temperatures and the ability of high heath communities to tolerate a wider range of temperatures. In the gorse communities, SI tended to increase as summer rainfall and the mean temperature of the coldest month increased. However, in the heath communities, no relationships were observed between SI and any of the climatic variables analyzed. The study findings may be useful for assessing and monitoring fuel hazards, updating fuel mapping, planning and implementing fuel reduction treatments and predicting fire behavior, among other important ecological and biomass use-related applications.

The accurate regional characterisation of the quantity and value of carbon for key plantation species is important for both forest owners and governments. New Zealand is committed to reaching carbon net zero by 2050 and forests are currently dominated by the fast growing species radiata pine (Pinus radiata) which comprises 90% of all plantations. However, coast redwood (Sequoia sempervirens) is a promising alternative species, that is particularly suited to permanent carbon regimes, as the species is capable of rapid growth over hundreds of years. Recent increases in the carbon price have stimulated afforestation rates within New Zealand and permanent forests now comprise almost one-quarter of new plantings. Using growth models to predict carbon over a 100 year period, the objective of this study was to regionally compare carbon yields and net present value (NPV) for radiata pine and redwood carbon regimes.Model predictions show that by age 100 years, total carbon for redwood exceeded that of radiata pine within eight of the nine regions within New Zealand. Gains were greatest in the North Island, where redwood carbon exceeded that of radiata pine by on average 74%, with differences reaching up to 85% (5,203 vs. 2,808 tonnes CO2/ha at age 100 years). Under a flat baseline real carbon price of $80/tonne CO2, the NPV for redwood was very similar to that of radiata pine within four of the five North Island regions. This similarity between species was maintained across the examined carbon price range which included 26 real carbon values ranging from $35 to $160/tonne CO2. However, NPV for radiata pine exceeded that of redwood within all South Island regions as growth rates for radiata pine were greater over the first 50 years and these earlier returns have higher weighting in discounted cashflow analysis. There was marked divergence in NPV between species across all four South Island regions with increasing carbon price. The establishment of a large permanent redwood resource over the next few decades in the North Island could greatly assist New Zealand to meet its carbon obligations over both the medium to long term.

The present study aims to identify the relations between the wood production (m3 per year) of the black pine (Pinus nigra Arnold.) and its habitat characteristics in the Eastern Mediterranean Region. A total of 120 samplings with different aspects, site altitudes, and site classes were studied. In each sample area, at least 5 trees were designated, and soil samples were taken by excavating earth pits. Certain characteristics of the soil samples were identified in the laboratory environment. The relations between the dominant height values of the trees in the sample areas and soil, climate, and physiographic factors were analyzed using correlation analysis, multiple regression analysis, and artificial neural network methods. Significant relations between the wood production values of the trees in the sample areas and slope from physiographic habitat characteristics, average annual temperature from climate characteristics, and pH and total carbonate from soil characteristics were found. The wood production of black pine was explained by multiple regression analysis at a level of 22.4% and by artificial neural network method at 72%. [ABSTRACT FROM AUTHOR]

The development of regulatory and reference support for the inventory assessment of the state of modal stands is an urgent issue, since it allows obtaining reliable and up-to-date information on the current state of existing forests. The purpose of the study was a statistical substantiation of the division of pine stands into groups by region of growth and stand composition, and their detailed inventory characteristics with an analysis of the distribution in the Forest-Steppe and their productivity. To conduct the study, a stand-wise database of the Production Association “Ukrderzhlisproekt” for Forest-Steppe zone of Ukraine was used. Using a number of non-parametric criteria for evaluating samples (Kruskal-Wallis one-way analysis of variance, the median criterion, Jonckheere-Terpstra test), the study established a difference in the stands parameters of the samples under study and divided the stands of the Forest-Steppe zone into four groups. The main task was to describe the current state of modal pine stands of the Forest-Steppe zone of Ukraine for selected groups, with a detailed distribution of areas and stocks according to the main stand parameters According to the results of the database analysis, it was found that about 92% of the total area of pine stands of the Forest-Steppe zone are artificial forests. Depending on the region of growth, the stands were divided into the left- and right-bank parts of the Forest-Steppe, in composition – into pure and mixed stands. Within the groups under study, the distribution of areas and stocks of pine stands was analysed according to site index classes, types of forest-growing conditions, forest types, relative stand density, and age groups. Site index classes in all groups are dominated by high site index stands of I and Ia site index classes. The proportion of high-grade mixed stands is greater compared to pure stands. In terms of the forest-growing conditions, stands in condition B2 dominate in all groups under study. From the left bank to the right bank, there is an increase in soil fertility from condition B to condition C, and this dependence is also observed from pure to mixed stands. Productivity in terms of the average growing stock of mixed stands of the rightbank and left-bank parts of the Forest-Steppe is very close and considerably less than the stocks of pure stands. The presented research results can be used by scientists as a description of the modal inventory characteristics of the Forest-Steppe region and for the grouping of experimental data when compiling forestry and forest inventory standards

This work aimed to assess if nonlinear models accurately predict the wood productive capacity of B. excelsa plantations in Amazonia and identify topoedaphic characteristics more linked to growth variations in these plantations. Nonlinear models were tested to classify the productive capacity of B. excelsa stands of different ages (14 to 21 years), by algebraic difference method. We used a database of 75 temporary plots and complete stem analyses of 30 trees. Soil sampling was performed at depths of 0–20 cm and 20–40 cm, for chemical analyses ( pH H 2 O , pHKCl, C, P, K+, Ca2+, Mg2+, Al3+, Fe2+, Mn2+, Zn2+ and Na+) and physical (soil density, penetration resistance, granulometry). Topographic information was obtained by GPS and digital elevation image. Site classes were spatialized in the study area by method ordinary point kriging. Relationships between topoedaphic variables and site index were evaluated by correlation matrix to identify major characteristics limiting site productivity, and regression models were generated by stepwise backward method to evaluate whether topoedaphic characteristics explain growth variation in B. excelsa stands. The Chapman-Richards model presented good statistical performance, good distribution of residues, and resulted in consistent polymorphic curves. Polymorphism evaluation indicated differentiated growth patterns of specie among sites. Soil texture (sand content) and topography (elevation) were the main drivers of site productivity, followed by some soil chemical variables (K+, Mn2+ and pHKCl). These results can support planning of activities related to installation and management of B. excelsa stands in the Amazon, besides identifying potential areas of expansion of plantations of this species. [ABSTRACT FROM AUTHOR]

Intensive silviculture demands new inventory tools for better forest management and planning. Airborne laser scanning (ALS) was shown to be one of the best alternatives for high-precision inventories applied to productive plantations. The aim of this study was to generate multiple stand-scale maps of the site index (SI) using ALS data in the intensive silviculture of Eucalyptus dunnii Maide plantations in Uruguay. Forty-three plots (314.16 m3) were established in intensive E. dunnii plantations in the departments of Río Negro and Paysandú (Uruguay). ALS data were obtained for an area of 1995 ha. Linear and Random Forest models were fitted to estimate the height and site index, and OrpheoToolBox (OTB) software was used for stand segmentation. Linear models for dominant height (DH) estimation had a better fit (R2 = 0.84, RMSE = 0.94 m, MAPE = 0.04, Bias = 0.002) than the Random Forest (R2 = 0.85, RMSE = 1.27 m, MAPE = 7.20, Bias=−0.173) model when including only the 99th percentile metric. The coefficient between RMSE values of the cross-validation and RMSE of the model had a higher value for the linear model (0.93) than the Random Forest (0.75). The SI was estimated by applying the RF model, which included the ALS metrics corresponding to the 99th height percentile and the 80th height bicentile (R2 = 0.65; RMSE = 1.62 m). OTB segmentation made it possible to define a minimum segment size of 2.03 ha (spatial radius = 30, range radius = 1 and minimum region size = 64). This study provides a new tool for better forest management and promotes the need for further progress in the application of ALS data in the intensive silviculture of Eucalyptus spp. plantations in Uruguay. [ABSTRACT FROM AUTHOR]

Due to considerable deforestation in North Korea, there is a need to plan forest restoration programs based on scientific forest management. In this study, a methodology was developed for estimating the site index values of six major tree species and the forest productivity potential. The site index values of these tree species were derived in South Korea using the Chapman-Richards equation. These values were used with data from the 6th National Forest Inventory, which included 20 types of edaphic, topographic, and climatic factors, and random forest analysis—a widely used machine learning technique for spatial prediction—to develop a new model for estimating the site index values of these species across South Korea. The prediction accuracy of this model was evaluated using the root mean square error. The results show that the prediction accuracy was high, with a root mean square error of ~ 1 m. Moreover, the importance of the variables related to climate and geography was generally high. The proposed site index estimation model for six tree species was applied across North Korea, and its effectiveness tested by comparing the estimated values with those reported in literature from North Korea. The differences between the model outputs and recorded data in the northern alpine regions were presumably due to the lack of data for high-altitude regions in South Korea. This model is based on the determination of the suitability of tree species in restoration efforts. Therefore, it can contribute to the evaluation of forest productivity in North Korea and may help plan efficient forest restoration programs. [ABSTRACT FROM AUTHOR]

African mahogany plantations are increasing in Brazil, especially those planted with the species Khaya grandifoliola C. DC. Despite the interest in establishing plantations, there is a lack of studies in management practices for the genus. This makes it difficult to improve methodologies that optimise forest inventory activities, which are essential to support forest management decisions. Therefore, this study aimed to evaluate the effect of the number of trees selected to determine the mean dominant height, and to verify its impact on site classification of African mahogany stands. This will then optimise height sampling and ensure correct site index estimation. To determine the dominant height, 11 treatments were tested, with the selection of 1st to 11th thickest trees per plot, representing between 9 and 102 dominant trees per hectare. The effect of the treatments was evaluated using the values of the mean dominant height and metrics regarding site index classification (stability, stratification capacity and relationship with stand growth). Treatments with inclusion of more dominant trees resulted in a more stable site classification at the expense of a lower correlation with stand growth. Treatments using fewer dominant trees resulted in a greater allocation of plots in the upper site classes, showing that the number of trees used to calculate the dominant height influences the distribution of plots in different site classes. We concluded that Treatments 3 (27 trees ha−1) to 6 (55 trees ha−1) had the best performance, guaranteeing adequate site index estimation. The selection of at least 27 and a maximum of 55 dominant trees per hectare is recommended for African mahogany plantations with low planting densities. [ABSTRACT FROM AUTHOR]

Stand density control coupled with site control is a key technique for cultivating large-diameter timber of Chinese fir trees, whose yield can be effectively increased by the optimal density and site management mode employed. This study aimed to evaluate the dynamic changes in timber assortment structure under differing initial planting densities and site quality based on growth data of a 41-year trial of Chinese fir plantations. Our results showed that the total timber yield and both large-diameter timber outturn and the outturn rate all increased with better site quality under the same initial planting density. Further, the outturn peak as well as outturn rate peak for both medium- and small-diameter timber was reached sooner with improved site quality. For the same site class, a lower initial planting density augmented the total timber outturn rate, and also resulted in less time required for the total timber outturn rate to reach a constant or maximum value. Finally, the total timber outturn rate of all density plots tended to be nearly identical. Using a high planting density increased the outturn of small-diameter timber, whose outturn peak was delayed in the denser plots. The bolstering effect of low density upon the growth of large-diameter timber was enhanced by higher site quality, with density-induced differences in large-diameter timber more pronounced; conversely, that promoting effect weakened under poor site quality conditions. The interaction between planting density and site index significantly influenced the growth of any timber assortment of Chinese fir in the early stage following its formation. Notably, the significant effect of site index on large-diameter timber lasted longer than that of other timber assortments. The optimal site conditions for cultivating large-diameter timber trees of Chinese fir consist of a site class ≥ 20 with a planting density limited to no more than 1667 trees/ha, whose stand rotation period must be over 26 years, so as to maximize the output of large-diameter timber yield. Our empirical findings will be helpful for the construction of an optimal cultivation mode for the density, site, and rotation age of large-diameter timber in Chinese fir plantations.

Larix principis-rupprechtii Mayr (larch) is one of the main afforestation and timber production species used in North China. Climate change has led to a change in its suitable distribution and growth. However, the impact of climate change on its growth suitability is not clear. In this study, using forest resource inventory data and spatially continuous environmental factor data (temperature, precipitation, topography, and soil) in Hebei and Shanxi Provinces, China, the random forest model (RF) was used to simulate the larch site index (SI) and growth suitability under three shared socioeconomic pathways (SSPs: SSP1-2.6, SSP2-4.5, and SSP5-8.5) for the current and future (2021-2040, 2041-2060 and 2080-2100). The results revealed that (1) RF had excellent performance in predicting the regional SI (R2 = 0.73, MAE = 0.93 m, RMSE = 1.35 m); (2) the main factors affecting the productivity of larch were the mean temperature of the warmest quarter (BIO10), elevation (ELEV), mean diurnal range (BIO2), and annual precipitation (BIO12); and (3) larch currently had a higher SI in the Bashang areas and in the high-altitude mountains. The areas characterized as unsuitable, poorly suitable, moderately suitable, and highly suitable accounted for 15.45%, 42.12%, 31.94%, and 10.49% of the total area, respectively. (4) Future climate warming had an obvious inhibitory effect on the SI, and the effect strengthened with increasing radiation intensity and year. (5) The moderately suitable and highly suitable areas of larch growth showed a downward trend under future climate scenarios. By the end of this century, the suitable growth areas would decrease by 14.14% under SSP1-2.6, 15.17% under SSP2-4.5, and 19.35% under SSP5-8.5. The results revealed the impact of climate change on larch growth suitability, which can provide a scientific basis for larch forest management. [ABSTRACT FROM AUTHOR]

This study was carried out to identify relationships between site index (dominant height at a reference age) and ecological variables of trembling poplar forests in Türkiye. Samples were collected from 78 plots differing in elevation, aspect, inclination, slope position, and site class. Physiographic factors of the sample plots were recorded, soil samples were collected from different predefined layers from soil pits, and bedrock samples were collected for identification. From three trees at the stand top height, the tree closest to the arithmetic mean height was felled, and its height and age were determined. Physical and chemical characteristics of the soil samples were analysed. Relationships of the soil properties, physiographic factors, and climate with site index were assessed with correlation, stepwise regression, and regression tree methods. Significant relationships were found between site index at 30 years and elevation from the physiographic factors; the maximum temperature and the number of snowy days of the coldest month from the climate characteristics; fine earth, silt, and pH from the percentage values of soil properties at different depths; and fine earth, silt, and clay from the soil characteristics aggregated on pedon level. The height growth of trembling poplar was 11.8% according to stepwise regression analysis and 18% according to the regression tree method. The models obtained in the current study might help evaluate the potential of sites regarding the growth of trembling poplar. [ABSTRACT FROM AUTHOR]

The development of regulatory and reference support for the inventory assessment of the state of modal stands is an urgent issue, since it allows obtaining reliable and up-to-date information on the current state of existing forests. The purpose of the study was a statistical substantiation of the division of pine stands into groups by region of growth and stand composition,and their detailed inventory characteristics with an analysis of the distribution in the Forest-Steppe and their productivity. To conduct the study, a stand-wise database of the Production Association “Ukrderzhlisproekt” for Forest-Steppe zone of Ukraine was used. Using a number of non-parametric criteria for evaluating samples (Kruskal-Wallis one-way analysis of variance, the median criterion, Jonckheere-Terpstra test), the study established a difference in the stands parameters of the samples under study and divided the stands of the Forest-Steppe zone into four groups. The main task was to describe the current state of modal pine stands of the Forest-Steppe zone of Ukraine for selected groups, with a detailed distribution of areas and stocks according to the main stand parameters According to the results of the database analysis, it was found that about 92% of the total area of pine stands of the Forest-Steppe zone are artificial forests. Depending on the region of growth, the stands were divided into the left- and right-bank parts of the Forest-Steppe, in composition – into pure and mixed stands. Within the groups under study, the distribution of areas and stocks of pine stands was analysed according to site index classes, types of forest-growing conditions, forest types, relative stand density, and age groups. Site index classes in all groups are dominated by high site index stands of I and Ia site index classes. The proportion of high-grade mixed stands is greater compared to pure stands. In terms of the forest-growing conditions, stands in condition B2 dominate in all groups under study. From the left bank to the right bank, there is an increase in soil fertility from condition B to condition C, and this dependence is also observed from pure to mixed stands. Productivity in terms of the average growing stock of mixed stands of the rightbank and left-bank parts of the Forest-Steppe is very close and considerably less than the stocks of pure stands. The presented research results can be used by scientists as a description of the modal inventory characteristics of the Forest-Steppe region and for the grouping of experimental data when compiling forestry and forest inventory standards. [ABSTRACT FROM AUTHOR]

The rapid development of non-parametric machine learning methods, such as random forest (RF), extreme gradient boosting (XGBoost), and the light gradient boosting machine (LightGBM), provide new methods to predict the site index (SI). However, few studies used these methods for SI modeling of Masson pine, and there is a lack of comparison of model performances. The purpose of this study was to compare the performance of different modeling approaches and the variability between models with different variables. We used 84 samples from the Guangxi Tropical Forestry Experimental Centre. Five-fold cross-validation was used and linear regression models were established to assess the relationship between the dominant height of the stand and different types of variables. The optimal model was used to predict the SI. The results show that the LightGBM model had the highest accuracy. The root mean square error (RMSE) was 3.4055 m, the relative RMSE (RMSE%) was 20.95, the mean absolute error (MAE) was 2.4189 m, and the coefficient of determination (R2) was 0.5685. The model with climatic and soil chemical variables had an RMSE of 2.7507 m, an RMSE% of 17.18, an MAE of 2.0630 m, and an R2 of 0.6720. The soil physicochemical properties were the most important factors affecting the SI, whereas the ability of the climatic factors to explain the variability in the SI in a given range was relatively low. The results indicate that the LightGBM is an excellent SI estimation method. It has higher efficiency and prediction accuracy than the other methods, and it considers the key factors determining site productivity. Adding climate and soil chemical variables to the model improves the prediction accuracy of the SI and the ability to evaluate site productivity. The proposed Masson pine SI model explains 67.2% of the SI variability. The model is suitable for the scientific management of unevenly aged Masson pine plantations. [ABSTRACT FROM AUTHOR]

Chinese fir [Cunninghamia lanceolata (Lamb.) Hook.] has a large native distribution range in southern China. Here, we tested differences in productivity of Chinese fir plantations in different climatic regions and screened the main environmental factors affecting site productivity in each region. Relationships of a Chinese fir site index with climatic factors and the soil physiochemical properties of five soil layers were examined in a long-term positioning observation trial comprising a total of 45 permanent plots in Fujian (eastern region in the middle subtropics), Guangxi (south subtropics) and Sichuan (central region in the middle subtropics) in southern China. Linear mixed effects models were developed to predict the site index for Chinese fir, which was found to vary significantly among different climatic regions. Available P, total N, bulk density and total K were dominant predictors of site index in three climatic regions. The regional linear mixed models built using these predictors in the three climatic regions fit well (R2 = 0.86–0.97). For the whole study area, the available P in the 0–20-cm soil layer and total N in the 80–100-cm soil layer were the most indicative soil factors. MAP was the most important climatic variable influencing the site index. The model evaluation results showed that the fitting performance and prediction accuracy of the global site index model using the climatic region as the dummy variable and random parameters and the most important soil factors of the three climatic regions as predictors was higher than that of global site index model using the climatic variable and the most indicative soil variables of the whole study area. Our results will help with further evaluation of site quality of Chinese fir plantations and the selection of its appropriate sites in southern China as the climatic changes. [ABSTRACT FROM AUTHOR]

Forest productivity is one of the most important aspects of forest management, landscape planning, and climate change assessment. However, although there are multiple elements known to affect productivity, most of them rely on the "nature" of the edaphic, climatic, and geographic conditions, and only some specific aspects can be modified through forest management or "nurture". Through evaluation of site resource availability and an understanding of the main drivers of productivity, management can present solutions to overcome site resource limitations to productivity. Therefore, understanding the implications of a specific management regime requires understanding what drives productivity across large spatial extents and among different management regimes. In this study, we used data from over 1 million hectares of industrial forestland, covering over 6000 different soils and several management regimes of Pinus taeda L. plantations, as well as plot-based data from the Forest Inventory and Analysis (FIA) program, facilitating a comparison of planted and natural Pinus taeda stands. Combined with US Geological Survey LiDAR data, we computed site index and generated wall-to-wall productivity maps for planted Pinus taeda stands in the southeastern US, as well as point-based site index estimates for the FIA dataset. We modeled site index using a random forest algorithm considering edaphic, geologic, and physiographic province information based on the Forest Productivity Cooperative "SPOT" system, and also included climate and management history data. Our model predicted site index with an R2 of 0.701 and RMSE of 1.41 m on the industrial data and R2 of 0.417 and RMSE of 1.84 m for the FIA data. We found that year of establishment of the forest, physiographic province, and geology, were the most important drivers of site index. The soil classification modifier indicating root restrictions were the most important soil-specific variable. Additionally, we found an average increase in site index of 3.05 m since the 1950s for all FIA data, and an average increase of 4.73 m for all industrial data since the 1970s. For the latest period analyzed (2000–2012), average site index in planted FIA plots was 1.2 m higher than naturally regenerated FIA plots, and site index in all industrial forestland had a site index almost 3 m greater than planted FIA plots. Overall, we believe this work sets the foundation for better understanding of forest productivity and highlights the importance of intensive silviculture to improve productivity, and as an additional tool to achieve the economic, environmental, and social objectives. • Productivity in intensive/extensive management was compared with LiDAR/NFI data. • Management and environment explained 70 % and 40 % of variance in each data source. • Variable importance and interaction were comparable among data sources. • Management level and age of plantation had a non-negligible effect on site index. • Site index increased 5 m in industrial data and 3 m in NFI data since the 1970s. [ABSTRACT FROM AUTHOR]

This study addresses how site index may affect crown shape by developing a crown shape regression model for the planted L. kaempferi at high altitudes in the subtropical climate of China. A total of 9241 branches from 78 trees, including 39 dominant trees and 39 intermediate trees, were measured in Hubei Province, southern China. The branch characteristics, including branch length, branch angle, and branch chord length of all living branches, were measured by felling trees. The models that showed good performance in crown shape modeling were used and compared in the present study. The goodness of fit statistics and stability of parameter estimation of the modified Kozak equation were better than those of the segmented polynomial equation. A nonlinear mixed-effect crown shape model was developed based on the modified Kozak equation. In addition to the tree level variables of diameter at the breast height (DBH), crown ratio (CR), and tree height-to-DBH ratio, an attempt was made to incorporate the site index into the crown shape model for the planted L. kaempferi. However, the site index was not a significant variable in the crown shape model. The purpose of our study was to lay the foundation for further study of the growth of the trees and the effects of crown morphology on stem growth in the future.

Carbon sequestration has become an important source of supplementary revenue from forest plantations. Although there are many financial comparisons of species based on timber revenue, there have been few regional comparisons that integrate revenue from carbon. Within New Zealand, radiata pine is the most widely planted species, but there has been a recent upsurge in planting rates for coast redwood. Under New Zealand’s Emissions Trading Scheme, areas that are newly afforested under clear-fell rotational forestry receive carbon payments up to a set age, intended to represent the long-term average under successive rotations. Using growth models for both species, the objectives of this research were to regionally quantify (i) how the rotation length and the carbon averaging age influenced the profitability of growing redwood and (ii) compare carbon, timber yields, and profitability between radiata pine and redwood. The results showed the legislated carbon averaging age of 22 years for redwood underestimated the actual mid-points of carbon accumulation, which averaged 26, 28, and 31 years across rotation lengths of 40, 45, and 50 years, respectively. The optimal rotation length for redwood varied markedly by region and carbon price but was most often 40 years, increasing to 50 years at higher carbon prices, particularly for southern regions. Under regimes where revenue was only derived from timber, the redwood internal rate of return (IRR) exceeded that of radiata pine for eight of the nine New Zealand regions. When revenue was received from carbon and timber, redwood had a higher IRR than radiata pine up to carbon prices ranging from 29 to 50 NZD/tonne CO2 for the North Island and 23 to 34 NZD/tonne CO2 in all South Island regions apart from Otago. The IRR of radiata pine exceeded that of redwood at carbon prices above these values for the eight regions and at all carbon prices within the cold, dry Otago region.

One of the most important indicators for using wooden materials as a building material is safety stress (SS). Site index is also an essential criterion for construction materials. This research was planned with the aim to reveal the relationship between safety stress and site index classes (I, II, III) of red pine wood, which is an important tree species of Turkey and the Mediterranean basin. Also, the safety coefficient was calculated. The safety stress tests for compression, bending, and tensile, tensile perpendicular to fibers, cleavage, and shearing strengths were calculated as 9.2, 9.7, 8.9, 0.35, 0.10, and 1.4 N/mm2, respectively. The statistical analyses indicated that the site index difference had a significant effect on the safety stress in red pine wood as mentioned above. Again, the safety coefficient was calculated as 5.27 for red pine wood. In addition, it was determined that the safety stress values of red pine wood provided the desired lower limit values according to the standard (TS 647 and EN 1995-1-1), excluding class I. As a result of the regression and correlation analyses, the presence of a moderately increasing linear relationship (R2 values equal to 0.41-0.68) was found between the density and safety stress values for all site indexes.

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Frequent (≤3 y) prescribed burn has been conducted in the Escambia Experimental Forest in southern Alabama, USA, since 2001.The change in the density of new germinants (≤1 y) and older seedlings and saplings (>1 y) of longleaf pine (Pinus palustris Mill.) from stands of varying conditions was quantified using the locally estimated scatterplot smoothing and spatial statistical methods. A relatively longer fire interval or time since last fire (TSLF) > 600 days favored the recruitment of young seedlings. However, a short fire return interval or TSLF≤ 600 days promoted the recruitment of older seedlings and saplings. Large basal area (BA) and site index (SI) tended to diminish natural regeneration, whereas large quadratic mean diameter (QMD) and age were facilitative. The interactive effect of these factors indicated that a ratio of TSLF/BA of 60 to 120 and QMD/SI of 1.8 to 2.2 would maximize the recruitment of young seedlings. The recruitment of older seedlings and saplings increased linearly with QMD/SI but had no relationship with TSLF/BA. Recruitment was largely absent when QMD/SI was <2.0. As a result, we recommend that QMD/SI be no greater than 2.0 and TSLF/BA range from 60 to 120 to regenerate longleaf pine naturally. [ABSTRACT FROM AUTHOR]

Aim of the study: We investigated the most suitable thinning ages and intensities to maximize productivity and minimize the rotation age of Tectona grandis clonal plantations in the Brazilian Eastern Amazon. Area of study: Capitão Poço, State of Pará, Eastern Amazonia, Brazil. Materials and methods: We used diameter, height, and volume data from 72 permanent plots measured on nine occasions. We determined the classification of forest sites using the generalized algebraic difference approach (GADA). Clutter’s segmented model was used to simulate different intensities of basal area reduction, determining the technical ages according to the projected increments. Main results: The polymorphic site curves generated by the GADA method revealed that there were sites with different productive characteristics. The Clutter model produced compatible projections of basal area and volume that followed the behavior of the productivity classes. The final production was maximized when three thinning intensities (basal area reductions) were applied: 1st thinning (50%), between the ages of 3.5 to 4.2 years; 2nd thinning (50%), between the ages of 6.1 to 7.3 years; and 3rd thinning (25%), between the ages of 10.6 to 12.8 years. Projected rotation ages ranged from 13.9 to 16.6 years earlier than seminal plantings. The simulations increased the net volume by 8.3%, on average, compared to no thinning. Research highlights: Simulations with three thinnings maximized production compared to the no thinning scenario. The time interval between thinnings was less than five years. The research results can help forest management decision-making and reveal production increases of T. grandis clonal stands in a shorter time.

We developed a system for modeling the growth and yield of planted teak (Tectona grandis L.f.) for small diameter products under varying management regimes in the tropical Central Highlands of Viet Nam. We compared an independent and simultaneous system of models to predict dominant height (Ho), quadratic mean diameter (Dg), averaged tree height (Hg) with Dg, and mean tree volume (V) versus stand age (A). In addition, the model system performance with and without site index (SI) and stand density (N) as covariates were compared using K-fold cross-validation. The best modeling system was obtained with the simultaneously fit models that included SI and N and were in the form of: Dg=Dm/(1 + a × exp(-b × A)) × exp[e1 × (SI– 15) + e2/1000 × (N – 722)]; Hg=Hm × exp(-a × exp(-b × A)) × exp[e1 × (SI– 15) + e2/1000 × (N – 722)]; and V=π4×104Dg2×Hg×0.45; where Dm, Hm, a, b, e1and e2 were the parameters to be estimated. These models will help predict the growth and yield of teak planted for different planting schemes, includings monoculture, agroforestry, and forest enrichment planting in this region.

Site index and stand age are important variables in forestry. Site index describes the growing potential at a given location, expressed as the height that trees can attain at a given age under favorable growing conditions. It is traditionally used to classify forests in terms of future timber yield potential. Stand age is used for the planning of management activities such as thinning and harvest. SI has previously been predicted using remote sensing, but usually relying on either very short time series or repeated ALS acquisitions. In this study, site index and forest stand age were predicted from time series of interferometric TanDEM-X data spanning seven growth seasons in a hemi-boreal forest in Remningstorp, a test site located in southern Sweden. The goal of the study was to see how satellite-based radar time series could be used to estimate site index and stand age. Compared to previous studies, we used a longer time series and applied a penetration depth correction to the phase heights, thereby avoiding the need for calibration using ancillary field or ALS data. The time series consisted of 30 TanDEM-X strip map scenes acquired between 2011 and 2018. Established height development curves were fitted to the time series of TanDEM-X-based top heights. This enabled simultaneous estimation of both age and site index on 91 field plots with a 10 m radius. The RMSE of predicted SI and age were 6.9 m and 38 years for untreated plots when both SI and age were predicted. When predicting SI and the age was known, the RMSE of the predicted SI was 4.0 m. No significant prediction bias was observed for untreated plots, while underestimation of SI and overestimation of age increased with the intensity of treatment.

To achieve the goal of carbon neutrality, overseas plantation projects have been conducted in several countries, including Vietnam. In the present study, stand growth models and a yield table were developed and used to analyze the economic feasibility of Acacia hybrid plantations in southern Vietnam. Diameter at breast height, tree height, and number of trees were determined in the field; basal area, mean height, dominant tree height, stand density, and stand volume were estimated using in situ data. The initial number of trees increased for five years and reached 4947 trees ha−1; tree numbers then decreased to 1987 trees ha−1 until the stands reached ten years of age. The highest current annual increment of stand volume was shown to be 46.23 m3 ha−1 yr−1 when stands were 7 years old. For 7 years of stand age, the net present value was USD 1566/ha, and the internal rate of return was 13%, exceeding the market interest rate (4%). Therefore, an A. hybrid plantation is a reasonable proposition for an overseas plantation project in southern Vietnam and the growth models will be useful for the management of an A. hybrid plantation. [ABSTRACT FROM AUTHOR]

Sustainable forest management requires accurate biometric tools to estimate forest site quality. This is particularly relevant for prescribing adequate silvicultural treatments of forest management planning. The aim of this research was to incorporate topographic and climatic variables into dominant height growth models of patula pine stands to improve the estimation of forest stand productivity. Three generalized algebraic difference approach (GADA) models were fit to a dataset from 66 permanent sampling plots, with six re-measurements and 77 temporary inventory sampling plots established on forest stands of patula pine. The nested iterative approach was used to fit the GADA models, and goodness-of-fit statistics such as the root mean square error, Akaike's Information Criterion, and Bias were used to assess their performance. A Hossfeld IV GADA equation type that includes altitude, slope percentage, mean annual precipitation, and mean annual minimum temperature produced the best fit and estimation. Forest site productivity was negatively affected by altitude, while increasing the mean annual minimum temperature suggested the fastest-growing rates for dominant tree height. [ABSTRACT FROM AUTHOR]

The site index (SI) is the most commonly used and representative measure of the phytocentric approach; it evaluates the site productivity based on the stand height and age. In the case of mixed stands with complex structures, phytocentric methods are very limited, while in non-forest areas, they are not applicable. In situations where the applicability of phytocentric methods is limited, the site productivity is determined by geocentric methods. Geocentric methods allow direct modelling of site productivity, expressed by SI predicted from various environmental variables. The aim of this study was to develop a geocentric model for oak. Site productivity expressed by SI was described by the environmental variables and stand characteristics. To develop the SI model, we used the data from 2490 NFI plots with dominant oak species (Quercus sessilis and Quercus robur). A generalized additive model was used in modelling site productivity. We documented a significant relationship between SI and the environmental variables, age of stands and stand density. Furthermore, the site productivity for oak is shaped by climate factors, soil type, geology, and altitude. The model developed based on the geocentric method, explained 55.1% of the variation of SI. [ABSTRACT FROM AUTHOR]

This study examined the relationships between soil, climatic and physiographic variables and site productivity in Fagus orientalis Lipsky stands in Artvin, Northeastern Turkey. The site productivity described by the site index (SI, top height at stand age of 100 years) was available for three forest locations. SI varied significantly depending on the edaphic, climatic and physiographic variables. A linear regression model was constructed to test the hypothesis that soil, climatic and physiographic variables could be used to predict the SI of the Fagus orientalis forest types in the study region. The most important single variable in the model was precipitation in the driest quarter of the year, which accounted for 55.1% of the variability in SI and was positively correlated. In a multiple regression model, precipitation in the driest quarter, radiation index, slope and physiological soil depth were the most important variables for explaining SI in the study region. 80% of the observed SI variation was explained by these variables. The SI models developed in this study provide a basis for understan-ding the complex relationship between forest productivity and site conditions. The findings of this study will assist resource managers in making cost-effective decisions about the management of Fagus orientalis forests in the northeastern region of Turkey. [ABSTRACT FROM AUTHOR]

Shortleaf pine site index on the Cumberland Plateau is one of the least studied silvics of the species. To obtain site index information, practitioners must use site index curves from outside the region. This research proposes a novel approach to using USDA Forest Service, Forest Inventory and Analysis data to develop a shortleaf pine site index equation specific to the Plateau. Shortleaf pine site trees (n = 410) were grown forward or backward until base age of 50 years, using site specific, mixed-model parameters. Over thirty height models were then fit using traditional methods and the algebraic difference approach (ADA). Fit and cross-validation statistics, along with examinations of model behavior, showed that a derivation of the Lundqvist-Korf model provided the best estimates. The model was rearranged to directly estimate site index, and a traditional site index graph is provided. Site index estimates had average validation results nearly four times better than the currently recommended site index curve developed off the Plateau. Forest practitioners now have access to improved site index estimation for restoring and managing shortleaf pine on the Cumberland Plateau. [ABSTRACT FROM AUTHOR]

Aim of study: Practically and simply assessing biodiversity by using inventory variables in four types of forest plantation stands (mixed and pure) including species such are chestnut, blue gum and maritime pine. Area of study: Northwest Portugal in Vale do Sousa (14,840 ha), which is 97% covered with plantation forests. Material and methods: Simulated data, from 90-year stand-level forest management planning, were considered using three indicators: tree species (number of different species and species origin—native or exotic), mean diameter at breast height (DBH), and shrub biomass. Two shrub regeneration types (fully regenerated by seed and fully regenerated by resprouting), and three site quality conditions were also considered. Main results: Mean biodiversity scores varied between very low (10.13) in pure blue gum stands on lowest-quality sites with shrub regeneration by seed, and low (29.85) in mixed stands with a dominance of pine, on best-quality sites with shrub regeneration by resprouting. Site quality and shrub regeneration type significantly affected all biodiversity scores in mixed stands dominated by pine and pure chestnut stands, while less affected pure blue gum stands and mixed stands were dominated by blue gum. Research highlights: The considered biodiversity indicators cover the major biodiversity aspects and allow biodiversity assessment over time. The findings are relevant for biodiversity conservation and fire protection management.

Introduction : Since the population increases and the industry develops, the demand for fossil fuels continues to increase, creating problems of energy resource depletions and accelerating global warming. Thus, many countries are making active efforts to replace fossil fuels with bioenergy as a renewable energy. In particular, trees managed and produced by forest industry have a high potential as energy sources for biofuel industry, because they have a conceptual characteristic of carbon neutrality. Recently, energy plan and policy are being developed to cultivate trees on fallow lands, environmentally restored sites, and ground-level work places of abandoned mines; however, economic feasibility for such plans and policies cannot be readily evaluated due to insufficient information on the amount of the energy to be produced from tree cultivation. Thus, the objective of this study is to develop a methodology which can be used to estimate the potential energy amount of the bioenergy from tree cultivation based on tree species, cultivation time, and cultivation area conditions. Methodology : The methodology consists of three stages. In the first stage, the total volume of the trees per area is estimated by using the number of trees per unit area and the average stem volume of the tree, which are affected by the site index representing the environmental conditions of cultivation area. In the second stage, the total mass of biomass is calculated by using the density of wood, the biomass expansion factors for the above-ground biomass, and root-shoot ratio. In the last stage, the amount of the energy produced from the tree cultivation is estimated by taking into account the caloric value evaluated based on the carbon, hydrogen, and oxygen compositions of the tree. Case Study : A case study for conifers and broad-leaved trees is performed to demonstrate the methodology. The conifers are Jungbu local pine, Korean white pine, and Japanese larch, and the broad-leaved trees are oak, red oak, and birch. The results of the case study validate the developed methodology and clearly showed the procedure and necessity for the methodology by estimating the bioenergy productions from the trees. Conclusions : The developed methodology can be used to provide practical information needed to determine the economic feasibility of the plan, policy, and project for tree cultivations.