Total Tree Height Research Articles

Using Drones for Dendrometric Estimations in Forests: A Bibliometric Analysis

Traditional field inventories have been the standard method for collecting detailed forest attribute data. However, these methods are often time-consuming, labor-intensive, and costly, especially for large areas. In contrast, remote sensing technologies, such as unmanned aerial vehicles (UAVs), have become viable alternatives for collecting forest structure data, providing high-resolution images, precision, and the ability to use various sensors. To explore this trend, a bibliometric review was conducted using the Scopus database to examine the evolution of scientific publications and assess the current state of research on using UAVs to estimate dendrometric variables in forest ecosystems. A total of 454 studies were identified, with 199 meeting the established inclusion criteria for further analysis. The findings indicated that China and the United States are the leading contributors to this research domain, with a notable increase in journal publications over the past five years. The predominant focus has been on planted forests, particularly utilizing RGB sensors attached to UAVs for variable estimation. The primary variables assessed using UAV technology include total tree height, DBH, above-ground biomass, and canopy area. Consequently, this review has highlighted the most influential studies in the field, establishing a foundation for future research directions.

CTRing: An R package to extract wood density profiles from computed tomography images of discs and logs

Accurately determining the position of pith and accessing tree-ring density profiles, including intra-ring variations, is important for both the forest industry and dendroclimatology. Although several available methods exist for acquiring this information, such as X-ray computed tomography (CT), micro-CT, and X-ray films, the availability of open-source programs for extracting data remains limited. The CTRing package in the R environment integrates a series of functions to detect precisely the pith and tree-ring boundaries and generate tree-ring density profiles using CT images of tree cross sections. Before processing, grey values are transformed into density using a calibration function. Pith position is then detected by combining an adapted Hough Transform method and a one-dimensional edge detector. Tree-ring profiles along the pith-to-bark path of interest are inspected visually, and tree-ring boundaries can be easily added or removed manually via a graphical user interface. After correcting for tree-ring boundaries, the inflection points of a 3rd-degree polynomial obtained from density profiles are used to delimit the earlywood–latewood transition. We tested this package using 60 CT-scanned images of white spruce (Picea glauca (Moench) Voss) discs collected at various tree heights (0%, 25%, 50% and 75% of the total tree height as well as at 1.3m). The pith detection function had an average mean error of 0.72mm with 95% of the automatically detected pith locations that differed by less than 2mm from their manually located positions. Error decreased toward the apex of the tree. The functions of the CTRing package are flexible and can be easily implemented or adapted. The package could also be used with simple images of discs to obtain ring-width time series; however, this use must be evaluated further. Future work with this package involves assessing the use of low-quality images and ring-porous species.

Carbon Sequestration and Storage of Urban Trees in a Polluted Semiarid City

Cities play a critical role in anthropogenic CO2 emissions, which exacerbate climate change and impact urban populations. Urban green infrastructure, such as urban trees, provides essential ecosystem services, including reducing atmospheric CO2 levels. However, there is a significant knowledge gap regarding the impact of urban trees on climate change in semiarid, polluted cities like Tehran, the capital and largest metropolis of the Middle East. This study assesses the carbon sequestration and storage potential of Tehran’s urban infrastructure using the i-Tree Eco model. A randomized cluster sampling method was employed, collecting data on species composition, diameter at breast height (DBH), and total tree height. The results indicate that Tehran’s urban trees sequester approximately 60,102 tons of carbon per year, equivalent to 220,393 tons of CO2. The net carbon storage in urban trees is about 254,579 tons, equivalent to 933,455 tons of CO2. Parks and urban green spaces demonstrate the highest rate of carbon sequestration per hectare, followed by urban services land use. Prioritizing the planting of species with high sequestration rates like Cupressus arizonica (Arizona cypress) and Cupressus sempervirens L. var. horizontalis (Mediterranean cypress) could enhance carbon sequestration efforts in Tehran. These data provide valuable insights into the carbon sequestration potential and environmental impact of different land use types, and may aid in the development of effective environmental policies and land management strategies in semiarid urban areas and other cities in similar settings.

Development of Local Volume Table for Pinus caribbaea var. hondurensis (Senecl) in Area J4, Omo Forest Reserve, Nigeria

Volume estimation is a crucial part of every forest or plantation because it provides the quantity of timber or wood available at a given period and predicts future or expected growth of the forest. Unfortunately, local volume table are not readily available for some–economically important tree species in Nigeria. Hence, it is of paramount importance that local volume tables for economic tree species such as Pinus caribbaea in Area J4, Omo Forest reserve, Ogun state, Nigeria. Aim: The aim of this study is to develop a local volume table for Pinus caribbaea in Area J4, Omo Forest Reserve, Ogun State, Nigeria. Study Design: Simple random sampling was used for this study. Ten Temporary Sample Plots (TSP) of equal size 25m x 25m were randomly located in the selected plantation (P. caribbaea: established in 1997). All the trees with diameter at breast height (dbh) ≥ 10cm in each TSP were enumerated. Place and Duration of Study: The study was carried out in the Pinus caribbaea plantation in Area J4, Omo forest reserve, Ogun State from November 9th to 20th, 2023. Methodology: The total tree height, merchantable height, diameters at the top, middle, base, and dbh were measured and used to estimate stand volume. A volume table was developed using five selected models, and the best model was selected using least Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Root Mean Square Error (RMSE). Data were analyzed using descriptive statistics and regression at α0.05 with R statistical software. Results: The results obtained in P. caribbaea plantation revealed that the dbh and height were 27.93±6.95 cm and 28.72±3.47 m, respectively, while individual tree volume was 0.83±0.57m3. The combined variable model ( was selected as the best model to develop local volume table for P. caribbaea (AIC = -54.73, BIC = -45.49 and RMSE = 0.20). The statistical metrics implied a suitable selected model which can be use for future predictions with minimal error. Conclusion: The developed volume table for estimating the quantity of wood or timber available in the Pinus caribaea plantation at a given time. The volume model and local volume table developed are to be applied only to the Pinus caribaea plantation in the study area for continuous estimation and valuation of the species.

Yield and economic feasibility of Eucalyptus dunnii stands under different management regimes

The aim of this study was to analyze volume yield, number of logs per assortment and economic feasibility of Eucalyptus dunnii stands under different management regimes. The stands are located in Fernandes Pinheiro, Paraná State, Brazil and cover a total area of 2.26 hectares, fragmented into three strata (treatments): A (8 years after coppicing regime), B (9-year old stand after two thinnings), and C (7-year old stand after one thinning). Diameters at breast height (d) of all trees and heights of 110 trees were obtained. The total height of the other trees was estimated by a hypsometric relationship. Tree volume was obtained through a taper function. For the economic analysis comparing the three strata, the periodic equivalent value (PEV) and the internal return rate (IRR) were evaluated considering an interest rate of 8%. The commercial volumetric estimates ranged from 156.61 to 375.53 m³ ha⁻¹. The stratum A yielded more logs, mostly for energy; stratum B yielded larger logs, and stratum C yielded similar number and volume of logs from all assortment classes. For economic analysis, PEV ranged from R$ 196.16 to R$ 1,255.79 ha year⁻¹, and IRR ranged from 12.73% per year (stratum A) to 21.35% per year (stratum C), based on a interest rate of 8%. It was concluded that the management condition of stratum C resulted in higher economic returns, with its product primarily destined for Sawmill 1.

Funciones alométricas de altura total para pinos tropicales en Puebla, México

Tropical pines are important because of the amount of wood they produce in short periods. However, it requires allometric functions to predict the total tree height, since it is one of the critical variables to estimate both, it is the total and commercial volume. Accordingly, we aimed to develop a local and a generalized allometric function for model the total height-diameter (h-d) relationship of Pinus caribaea var. hondurensis and hybrid Pinus caribaea var. hondurensis × Pinus tecunumanii in the Sierra Norte of Puebla, México. In order to analyze the relationships, 1 232 h-d pairs were used. The allometric models were fitted with three parameters totaling 80% of the data and validated with 20%. The best model had the lowest average bias, root mean square error, and Akaike’s Information Criterion, as well as of the highest adjusted coefficient of determination. The models explained over 58.55% of the variability in observed total tree height. Nonetheless, the Gompertz and Weibull models obtained the best performances in fit and validation, and estimated h of tropical pines with less uncertainty. In consequence, the fitted allometric functions are reliable for predicting tree h; therefore, it can contribute to the sustainable management of commercial tropical pine plantations in the study region.

Integration of field measurements with unmanned aerial vehicle to predict forest inventory metrics at tree and stand scales in natural pure Crimean pine forests

ABSTRACT Inventorying forest ecosystems is an essential part of forest management planning. However, it is quite costly and time-consuming, particularly for larger areas. Recently, significant developments have been made in unmanned aerial vehicle (UAV) technology to improve the cost and time efficiency in forest inventory. Therefore, UAV images have become one of the inventory tools that produces data with high spatial resolution in determining forest resources. This study aims to investigate the contribution of UAV data to forest inventory in a case study area with a total of 30 sample plots located in pure and natural Crimean pine (Pinus nigra J.F. Arnold ssp. pallasiana (Lamb.) Holmboe) stands in the Black Sea backward region of Türkiye. Total tree height (h) and stem volume (v) were recorded at individual tree level (n = 367), and the number of trees (N), mean height (hmean), top height (htop), stand basal area (BA) and stand volume (V) were calculated at sample plot level (n = 30) from both the field and UAV-based data. Pearson’s correlation coefficients (r) for h and v were 0.96 and 0.72, respectively, the highest correlation at the sample plot level was observed for the hmean - htop (r = 0.96), while the lowest correlation was found for BA (r = 0.54). The suitability of the observation and prediction values was assessed using a t-test at both individual tree and sample plot levels. According to the t-test results, the observation and prediction values for h, v, hmean, htop, BA and V metrics were found to be compatible (p > 0.05), but not for N (p < 0.05). Overall results indicated that UAV technology has a potential to be used in forest inventory and can contribute to the determination of individual tree and stand metrics. Thereby, it saves cost and time in forest inventory studies and helps monitoring the dynamic structure of the forest ecosystem with an effective approach in forest inventory.

3DFin: a software for automated 3D forest inventories from terrestrial point clouds

Abstract Accurate and efficient forest inventories are essential for effective forest management and conservation. The advent of ground-based remote sensing has revolutionized the data acquisition process, enabling detailed and precise 3D measurements of forested areas. Several algorithms and methods have been developed in the last years to automatically derive tree metrics from such terrestrial/ground-based point clouds. However, few attempts have been made to make these automatic tree metrics algorithms accessible to wider audiences by producing software solutions that implement these methods. To fill this major gap, we have developed 3DFin, a novel free software program designed for user-friendly, automatic forest inventories using ground-based point clouds. 3DFin empowers users to automatically compute key forest inventory parameters, including tree Total Height, Diameter at Breast Height (DBH), and tree location. To enhance its user-friendliness, the program is open-access, cross-platform, and available as a plugin in CloudCompare and QGIS as well as a standalone in Windows. 3DFin capabilities have been tested with Terrestrial Laser Scanning, Mobile Laser Scanning, and terrestrial photogrammetric point clouds from public repositories across different forest conditions, achieving nearly full completeness and correctness in tree mapping and highly accurate DBH estimations (root mean squared error &amp;lt;2 cm, bias &amp;lt;1 cm) in most scenarios. In these tests, 3DFin demonstrated remarkable efficiency, with processing times ranging from 2 to 7 min per plot. The software is freely available at: https://github.com/3DFin/3DFin.

Height-diameter models for King Boris fir (Abies borisii regis Mattf.) and Scots pine (Pinus sylvestris L.) in Olympus and Pieria Mountains, Greece

In forest science and practice, the total tree height is one of the basic morphometric attributes at the tree level and it has been closely linked with important stand attributes. In the current research, sixteen nonlinear functions for height prediction were tested in terms of their fitting ability against samples of Abies borisii regis and Pinus sylvestris trees from mountainous forests in central Greece. The fitting procedure was based on generalized nonlinear weighted regression. At the final stage, a five-quantile nonlinear height-diameter model was developed for both species through a quantile regression approach, to estimate the entire conditional distribution of tree height, enabling the evaluation of the diameter impact at various quantiles and providing a comprehensive understanding of the proposed relationship across the distribution. The results clearly showed that employing the diameter as the sole independent variable, the 3-parameter Hossfeld function and the 2-parameter Näslund function managed to explain approximately 84.0% and 81.7% of the total height variance in the case of King Boris fir and Scots pine species, respectively. Furthermore, the models exhibited low levels of error in both cases (2.310m for the fir and 3.004m for the pine), yielding unbiased predictions for both fir (−0.002m) and pine (−0.004m). Notably, all the required assumptions for homogeneity and normality of the associated residuals were achieved through the weighting procedure, while the quantile regression approach provided additional insights into the height-diameter allometry of the specific species. The proposed models can turn into valuable tools for operational forest management planning, particularly for wood production and conservation of mountainous forest ecosystems.

Vertical variation in swelling properties of Norway spruce bark depending on tree age and bark moisture content

AbstractIn forest ecosystems, interception of rainwater on foliar and woody surfaces and the subsequent partitioning into stemflow is largely controlled by physical and hydrological properties of bark. Few forest ecohydrology studies have explored the role of bark properties (e.g., thickness, density) on bark water storage capacity and stemflow production. Even fewer have explored how different phases of water (e.g., liquid, vapor) may affect bark through bark swelling properties across the stem and how the degree of swelling affects tradeoffs between bark water storage and stemflow generation. Thus, the objective of this study was to analyze changes in a bark swelling index (BSI) vertically along stems of Picea abies (Norway spruce) after exposure to both water vapor and liquid water, as a function of tree age and bark moisture content. We found that tree age influenced BSI and bark moisture content, wherein BSI was ∼ 6.5% lower in older trees (70 years) compared to younger trees (35 and 50 years), and average moisture content was 10.4–13.2% lower. BSI increased when bark was exposed to hygroscopic water vapor and reached maximum swelling after 1 day of water saturation. BSI also increased from the base of the tree to 20–30% of total tree height, beyond which BSI remained relatively stable across all age classes. Enhanced understanding of bark swelling mechanisms as a result of stem position, age, and moisture content and exposure provide stronger foundations for understanding canopy hydrologic partitioning and the fate of rainwater moving through forest canopies.

Growth, Yield, and Stem Quality of Tectona grandis Grown with Different Spacings at Longuza Forest Plantation, Tanzania

Spacing is a silvicultural practice that affects the growth of trees in forest plantations. However, the yield depends on growth, which is determined by spacing. In addition, spacing influences the quantity of the final crop available for harvesting, specifically in forest plantations for sawlog production. Spacing is also used as a management practice to control the quality of trees, as dense stands are expected to have trees with good stem quality. However, little has been done to address the effects of spacing on the growth, yield, and stem quality of Tectona grandis until final harvesting age. Teak plantations in Tanzania are grown at a rotation age of 20 years. Thus, this study aimed to assess the effect of spacing on the growth, yield, and stem quality of 24-year-old T. grandis in a Longuza Forest plantation in Muheza, Tanzania. Data were collected from a spacing trial using a randomized complete block design with three treatments: 2 m × 2 m, 3 × 3 m, and 4 m × 4 m, with three replications. The growth and yield parameters assessed were diameter at breast height (dbh) total tree height, and stem quality. Data were analyzed to obtain the basal area, volume, and mean annual increment. Statistical analysis was performed using analysis of variance (ANOVA), and multiple comparisons among treatment means were performed using Tukey's honest significant difference test (p-value = 0.05). The results showed that spacing did not significantly affect growth and yield parameters. The stem quality was significantly different in some treatments. The highest dbh and height growth were observed at 4 m× 4 m spacing. The highest values of basal area, volume, and mean annual increment were observed at a 3 m× 3 m spacing. Stem quality differed significantly between the 2 m× 2 m and 4 m× 4 m spacings. Because teak plantations in Tanzania are aimed at sawlog production, it is recommended to continue practising a spacing of 3 m× 3 m, which will ensure a higher mean annual increment with a higher volume at the stand level. In addition, a spacing of 3 m × 3 m ensured a higher percentage of trees with good stem quality.

Carbon stock estimation of Sonneratia alba in mangrove restoration area in Pasar Rawa, Langkat North Sumatera

Mangrove forests must be protected because they are an important ecosystem for climate mitigation. Mangrove forests are one of the “blue carbon” ecosystems capable of absorbing significantly more carbon than terrestrial forests. Mangrove restoration is being carried out in various regions as part of an effort to rehabilitate damaged ecosystems, one of which being Pasar Rawa Village in Langkat Regency. Sonneratia alba is a native plant that is employed in restoration activities. The purpose of this study is to investigate carbon stock in the S. alba monoculture restoration area in Pasar Rawa Village, Langkat Regency, North Sumatra Province. Purposive sampling was employed in this study, with plots distributed evenly around the research area. Carbon stock estimation is performed non-destructively by estimating carbon estimates based on diameter at breast height (DBH) and total height of trees. According to the research findings, the total carbon stored in the Sonneratia alba restoration area is quite low, at 60.89 ton.ha−1. S. alba produced 192.13 ton.ha−1 of absorbed carbon with CO2 absorption of 19212.84 g/m2 and so was classified as low.

Species-specific allometric models for reducing uncertainty in estimating above ground biomass at Moist Evergreen Afromontane Forest of Ethiopia

An allometric equation is used to convert easily measured tree variables into biomass. However, limited species-specific biomass equations are available for native tree species grown in various biomes of Ethiopia. The available pantropic generic equation has resulted in biases owing to the uncertainty of the generic model estimation due to the difference in tree nature and response to growth conditions. The objective of the study is, thus, to develop a species-specific allometric equation for reducing uncertainty in biomass estimation at the Moist Evergreen Afromontane Forest in south-central Ethiopia. Five tree species were selected for model development, these selected trees were harvested and weighed in the field. The measured above-ground biomass data related to easily measured tree variables: diameter at stump height, diameter at breast height (dbh), crown diameter, and total tree height. The developed model evaluated and compared with previously published model by using measures of goodness of fit such as coefficient of determination (R2), total relative error, mean prediction error, root mean square error, and Akaike information criteria. The analysis showed that a model with dbh as a single predictor variable was selected as the best model for the estimation of above-ground biomass. It gives the highest R2 for Syzygium guineense (0.992) and the lowest for Bersama abyssinica (0.879). The additions of other tree variables did not improve the model The pantropic model by Brown overestimates the biomass by 9.6–77.8% while both Chave models resulted in an estimation error of 12–50.3%. Our findings indicated that species-specific allometric equations outperformed both site-specific and pantropic models in estimating above-ground biomass by giving 0.1% up to 7.9% estimation error for the respective tree species.

Application of GIS technologies for accounting plus trees

Introduction &#x0D; Nowadays, an important forest genetic resources (FGR) conservation activity is the systematization of information on gene pool conservation units in electronic databases. It should be noted, however, that the existing international databases mainly relate only to units represented by populations (stands), which are visualized as polygons on the map. As the scientists from the Department of New Information Technologies in URIFFM have implemented the website “Geoportal: Forests of Ukraine”, it became technically possible to add information on plus trees to its functionality and combine data on tree locations and their characteristics in a united electronic database.&#x0D; The study aimed to improve the organization of information on plus trees, their accounting, survey, and use as improvement units by applying free software (Python, JavaScript) and the PostgreSQL relational database with the PostGIS module.&#x0D; Materials and Methods&#x0D; In 2021, one of the work stages was to develop software and methodology for forming the Plus Trees database and to provide a user manual. In particular, a data schema was created to store both attribute and geographical information on tree improvement units in Ukraine. In addition, attribute and geographical information of forest inventory are used. The database of plus trees contains basic information from plus tree Passports or selection/inventory data from the reports.&#x0D; Results &#x0D; The proposed database consists of several panels. The first panel contains elements for setting coordinates and entering plus tree numbers. The second panel is intended for selecting a species name of trees. The third panel of the data entry form contains mandatory attributes (total height of a plus tree and its diameter at a height of 1.3 m). The fourth panel contains other tree characteristics.&#x0D; During the testing of the developed database structure and the working out of the instruction, the information on plus trees in seven regions of Ukraine (Kharkiv, Poltava, Sumy, Dnipro, Zaporizhzhia, Luhansk, and Donetsk) was entered, which is about 25% of the country’s plus tree pool. In addition, the design of the web pages was finalized in parallel with the data entry.&#x0D; The developed software can be useful to both scientists and forest managers. Its use will simplify the search for plus trees in forest stands for their inventory, and survey, as well as in cases where it is necessary to collect seeds or cuttings for the seed orchards or progeny tests creation in forest enterprises or at forest seed centers. For scientists, it will provide an opportunity to systematize, analyze, and generalize information, in particular, to improve methodical approaches to the selection of the plus trees.&#x0D; Conclusions &#x0D; A data schema was created to store both attribute and geographic information on forest tree species tree improvement units in Ukraine. The schema considers the complex structure of coordinated units and includes the developed algorithms for data verification which will allow the effective use of the proposed database for the plus tree accounting.&#x0D; 8 Figs., 1 Table, 20 Refs.

Tree allometry and stand structure in dryland forests relics of northern Côte d’Ivoire

The contribution of dryland forests in West Africa to carbon stocks remains poorly documented due to the lack of appropriate allometric models and inventory data. In this study, we gathered such data for dryland forest relics of northern Côte d’Ivoire. Inventory data were used to determine and sample the dominant species, and to characterize the stand structure. Destructive biomass data were used to develop local mixed-species allometric models for estimating tree aboveground biomass (AGB) and test the validity of existing allometric models, and to characterize the stand structure (including carbon stock). A total of 118 tree species belonging to 102 genera and 36 families were inventoried in 41 plots of 25 × 25 m (625 m² each, totalling 2.56 ha) sampled in three sites in the Korhogo department. Among them, seven predominant species, including one exotic, were selected for destructive sampling in one site, the Lataha Forest Research Station. Destructive biomass data for 34 trees belonging to these dominant species and with diameter at breast height between 6 and 41 cm were used to fit allometric equations specific to this forest type and to test the predictions of existing equations earlier developed for the global tropics and for African dry forests. Six equations integrating three predictors, stem diameter (D), total tree height (H) and wood specific gravity (ρ) were developed and the models with the three predictors showed the best performance. Pantropical models significantly over-estimated tree AGB by 20 % while models developed for African dry forests provided reliable estimates, suggesting a specific allometry of trees in dryland forest relics that needs to be further explored.. With our best AGB model, a quantity of 141.26 ± 92.72 tDM.ha−1 was estimated confirming that these dryland forest relics are important carbon stocks for this region where open vegetation dominates. This study constitutes an important contribution for the carbon accounting programs related to the implementation of REDD+ initiatives in Côte d’Ivoire.

Assessment of morphological variability in natural populations of Haldina cordifolia (Haldu)

The surveys were conducted in natural populations of Haldina cordifolia in the forest areas of three states of central India namely Madhya Pradesh, Chhattisgarh and Maharashtra. Based on the growth parameters of the individual tree, a total of thirty trees from nine forest divisions of these three states were selected as candidate plus trees (CPTs). Variation was observed in girth at breast height (GBH), total height, and clear bole height (CBH) of trees surveyed. The maximum GBH was recorded in the CPTs of Balrampur (243.75 cm) while the minimum was recorded in Balaghat (115 cm). The maximum height of CPTs was recorded in Dindori (30.25 m) while the minimum was recorded in Allapalli (19 m). The maximum CBH% of total height was recorded in Bilaspur (44.22) while the minimum was recorded in Katghora (37.31). Higher GBH and height of trees may be resulted due to more age of trees. CPTs of Bilaspur were of middle age and showed the highest CBH% (44.22) and relatively low GBH and height when compared with those of Dindori and Balrampur. With age, the trees of Bilaspur will gain more height and girth which will result in higher yield.

Accuracy of tree height estimation with model extracted from artificial neural network and new linear and nonlinear models

Variable height is commonly used as an input attribute to estimate other variables. Thus, to ensure less susceptibility to errors, it is necessary to obtain the variable height correctly. In addition to DBH, hypsometric relationships are influenced by several factors, such as site, age, genetic variation, and silvicultural practices. The inclusion of these factors in hypsometric models can lead to a gain in the quality of the estimates and in the biological realism. The objective of this study was to propose and evaluate the performance of a model extracted from artificial neural network training and of new models to estimate the total height of eucalyptus trees. The data used in this study originated from temporary forest inventories conducted in eucalyptus stands in Minas Gerais, Brazil. A multilayer perceptron artificial neural network was trained, and a nonlinear equation was extracted from the best-performing network to predict the total heights of trees. New linear and nonlinear hypsometric models were constructed and fit considering variables related to individual trees (DBH) and stands (plot basal area, age and site index). The new hypsometric models proposed in this study showed satisfactory performance and are effective for estimating the total heights of eucalyptus trees, particularly the model extracted from the artificial neural network and the nonlinear model

Assessing the benefits and management of urban forest in supporting low carbon city in Jakarta, Indonesia

Abstract. Aulia R, Kaswanto, Arifin HS, Mosyaftiani A, Syasita N, Wahyu A, Wiyoga H. 2023. Assessing the benefits and management of urban forest in supporting low carbon city in Jakarta, Indonesia. Biodiversitas 24: 6151-6159. Climate change is a phenomenon that has become a global concern including in urban areas. Jakarta is one of the most populated cities in Indonesia, reaching 10.56 million people in 2020 with high emissions levels due to high human activities. Thus, efforts to reduce carbon emissions to mitigate climate change are necessary in Jakarta one of which is through the concept of low carbon city and manifested in the establishment of Green Open Space (GOS), including urban forests. Urban forests aim to sequester and store carbon, and improve the urban microclimate. This research aimed to assess the benefits of urban forests in Jakarta in term of their capacity in carbon sequestration using i-Tree Eco tool, and analyse the management of urban forests related to the applicable regulations. To collect data on trees, this study created 49 plots scattered across Srengseng Urban Forest, Cipayung Urban Forest, Munjul Urban Forest, Rawa Malang Urban Forest, and Pondok Labu Urban Forest. Tree species, Diameter at Breast Height (DBH), total tree height, live tree height, crown base height, crown width, percent crown loss, and crown light exposure were all gathered. Furthermore, in-depth interviews with urban forest managers were performed to gather additional information on present management, including questions derived from Jakarta's green open space legislation to assess management efficacy. The results of the analysis of urban forest quality show that the health status of trees is one of the factors that indicate the quality of urban forests at the five study sites, with more than 50% of the total trees in fair condition (75- 90% health). The gross carbon sequestration of trees in five urban forests Jakarta is about 184.8 metric tons of carbon per year. Additionally, the in-depth interviews also test the mortality of the urban forest, a decent indicator of current management with estimates over the next 10 years, showing a slight increase in carbon sequestration and storage capacity. However, the mortality scenario leads to a trend toward a decrease in leaf area and the number of tree categories, especially in the Srengseng Urban Forest.

Prediction Models for Ceiba pentandra in the Guinea Savanah Ecological Zone of Ghana

This study investigated the relationships between seven dendrometry variables in Ceiba pentandra. The relationships between stem diameter at breast height, total tree height, crown diameter, crown height, crown ratio, crown projection area and number of branches. Also, the relationship between Crown diameter and total tree height was studied. Regression prediction models were derived using simple linear regression analysis. Pearson correlation between variables was done using the Pearson’s Correlation coefficient. Stem diameter at breast height and crown diameter were used as independent variables as they are readily easy to measure with high accuracy. The study showed that positive correlations exited between stem diameter at breast height and total tree height, crown diameter, crown height, crown projection area, number of branches and crown ratio. Again, a positive correlation exited between the crown diameter and total height (0.39). The value of Pearson correlation coefficient (r) between the stem diameter at breast height, total tree height, crown diameter and crown height was 0.98; that between stem diameter at breast height and crown projection area was 0.95; between stem diameter at breast height, number of branches and crown ratio was 0.96. The correlation coefficient between crown diameter and total height was also 0.98. The coefficient of determination (Ar2) between the stem diameter at breast height, total tree height and crown height was 0.9; between stem diameter at breast height and crown diameter was 0.91; between stem diameter at beast height and crown projection area was 0.84; and 0.88 between stem diameter at breast height, number of branches and crown ratio. The coefficient of determination between crown diameter and total tree height was 0.9. Thus, the stem diameter at breast height accounted for about 90% of the total tree and crown heights. Also stem diameter accounted for 91% of crown diameter, 84% of crown projection area, and 88% of both crown ratio and number of branches. The crown diameter, on the other hand, accounted for 90% of the crown projection area. P-values were significant at 0.05 for all the variables studied (P ≤ 0.05). The models developed will enhance decision making in forest management and save cost and time spent in collecting data on these dendrometry variables studied.

Genomic prediction across generations in a Eucalyptus grandis breeding population

Forest genetic breeding programs are intricate, long-term, and costly processes. To overcome these limitations, genomic selection emerges as an important tool to enable shorter cycles through early selection and to increase breeding value accuracies. Genomic selection is based on a predictive model derived from a training population (TP), integrating genotypic, phenotypic, and pedigree data to predict breeding values on selection candidates (SP) based on genomic information. As breeding generations advance, the relatedness between the TP and SP decreases, with the reduction of the prediction ability. The objective of this study is to optimize the TP for a Eucalyptus grandis breeding population across four consecutive generations (G1, G2, G3, and G4). A population of 66,221 individuals (from four generations) resulting from cross-breeding and open-pollination were measured for diameter at breast height (DBH) and total tree height (HT). Wood quality traits were determined for 16,068 trees and assessed using Near-Infrared Spectroscopy (NIRS). A total of 3,221 individuals from the four generations were genotyped using the EUCHIP60K or the Euc72k Axiom Eucalyptus Genotyping Array. We compared the prediction ability using all the previous generations in the TP as opposed to only including the previous generation. Single-step GBLUP (ssGBLUP) models were evaluated in three phenotypic traits: volume, pulp yield, and wood density. The inclusion of all the previous generations provides a higher predictive ability of 0.40 and 0.54 for volume and pulp yield, respectively, in the target generation G4. When only the previous generation G3 was used as a TP, no significant differences in predictive abilities were observed for volume, and there was a slight decrease in pulp yield. In contrast, for wood density, the predictive ability was highest (0.37) in the G4 when the model was training with only the G3, while including all preceding generations decreased to 0.33. Our results provide insight into the optimization of TP across generations, encouraging the implementation of genomic selection in the Eucalyptus breeding program.