Tree Pattern Research Articles

Classification of epileptic EEG signals with the utilization of Bonferroni mean based fuzzy pattern tree

The Electroencephalogram (EEG) is an essential tool used to detect and investigate multiple neurological disorders within the human brain. However, examination and visualization of any such abnormalities in the brain through inspecting these EEG signals is a time-consuming and repetitive task for a neurologist. Hence, there is a need to develop a model that can automatically classify brain disorders based on the EEG signals. In this study, a novel fuzzy classification model is proposed for classifying the EEG signals. First, the discrete wavelet transform (DWT) technique is employed to decompose the signal into time–frequency sub-bands. Then, by utilizing these sub-bands, seven meaningful statistical features are extracted effectively for additional investigation purposes. Then, the retrieved features are provided to the fuzzy pattern tree classifier to obtain meaningful inferences from the data. Here, a distinctive structure of a fuzzy pattern tree is proposed by utilizing the interrelationship handling aggregation operators. More precisely, we utilize the Bonferroni mean (BM) aggregation operator for the enlargement or expansion of the tree while considering the concatenation between the parent and the slave tree. To the best of our knowledge, this is the first work that presents such an interrelationship handling fuzzy logic-based classifier model for EEG signal classification. The proposed algorithm is evaluated using two publicly available datasets, namely the Bonn University (Bonn) epileptic datasets and the Temple University Hospital (TUH) EEG subcorpus of abnormal (TUAB) and epilepsy (TUEP) datasets. This study considers different frames of the binary problem (i.e., healthy vs. seizure detection) and multi-class problem (i.e., healthy vs. seizure free vs. seizure) over the Bonn dataset and achieves more than 99% accuracy over the binary model by testing over all possible combinations of the available experimental dataset and 97.8% accuracy in multi-class model. In the case of TUAB and TUEP categories, the model achieves an accuracy of 88% in predicting normal to abnormal activities and 86% in detecting epilepsy and non-epilepsy within the signals. The outcomes derived from the proposed model outperform some existing studies available in the literature for EEG signal classification. Also, the model is efficient as it considers the uncertainty and association among the features while framing the classifier model.

Modelling how negative plant–soil feedbacks across life stages affect the spatial patterning of trees

In this work, we theoretically explore how litter decomposition processes and soil-borne pathogens contribute to negative plant–soil feedbacks, in particular in transient and stable spatial organisation of tropical forest trees and seedlings known as Janzen-Connell distributions. By considering soil-borne pathogens and autotoxicity both separately and in combination in a phenomenological model, we can study how both factors may affect transient dynamics and emerging Janzen–Connell distributions. We also identify parameter regimes associated with different long-term behaviours. Moreover, we compare how the strength of negative plant–soil feedbacks was mediated by tree germination and growth strategies, using a combination of analytical approaches and numerical simulations. Our interdisciplinary investigation, motivated by an ecological question, allows us to construct important links between local feedbacks, spatial self-organisation, and community assembly. Our model analyses contribute to understanding the drivers of biodiversity in tropical ecosystems, by disentangling the abilities of two potential mechanisms to generate Janzen-Connell distributions. Furthermore, our theoretical results may help guiding future field data analyses by identifying spatial signatures in adult tree and seedling distribution data that may reflect the presence of particular plant–soil feedback mechanisms.

The relationship between forest structure and naturalness in the Finnish national forest inventory

Abstract There is considerable interest in identifying and locating natural forests as accurately as possible, because they are deemed essential in preventing biodiversity loss. In the boreal region, natural forests contain a substantial amount of dead wood and exhibit considerable variation in tree age, size, and species composition. However, it is difficult to define natural forests in a quantitative manner. This is an issue, for example, in the Finnish national forest inventory. If naturalness could be related to the metrics derived from tree measurements, it would be easier to locate natural forests based on the inventory data. In this study, we investigated the value of metrics computed from tree locations and tree sizes for the characterization of a key aspect of naturalness, namely, structural naturalness as defined in the Finnish national forest inventory. We used L-moments, Gini coefficient, Lorenz asymmetry, and interquartile range to quantify the variations in tree size at the plot level. We summarized the spatial pattern of trees with a spatial aggregation index. We compared the structural metrics, species proportions, and stand age using the classes of structural naturalness described in the Finnish national forest inventory, which have been determined in the field without strict numerical rules. These categories are ‘natural’, ‘near-natural’, and ‘non-natural’. We found that the forests evaluated as structurally natural had larger variations in tree size and species composition and showed a more clustered spatial pattern of trees on average, although the variation in the structural metrics was considerable in all three classes. In addition, we used the structural metrics to predict naturalness by employing a random forest algorithm. Based on the structural metrics, it was possible to obtain high precision in the classification only if we simultaneously accepted low recall, and vice versa; the link between the inspected metrics and naturalness evaluated in the field was weak. The stand age separated the three classes more clearly and it also improved the classification.

Pengembangan Parsing PCPATR Sebagai Preservasi Bahasa dan Sastra Banjar

Banjar Mantra is part of the Banjar language and literature in the form of words recited orally by certain people. Mantras are considered to have magical powers for supernatural powers and curses. This study aims to develop a sentence parsing device as a Language and Literature Preservation of Banjar using a sentence parsing application (parse PC-PATR). Parse PC-PATR is a sentence parsing application that will produce a pattern tree to represent the syntactic structure of sentences based on the Banjar language grammars. The problem in this research is that the mantra corpus uses the old genre of Banjarese language and literature. Words in the old genre are currently not widely used in communication by the Banjar people. On the other hand, the absorption of Arabic also presents its own problems. Finally, it is difficult to find the availability of experts who still preserve the Banjar mantra. This research used the ADDIE method with 20 Banjar mantras as test sentences and involved 3 committees of linguists as examiners. The research results showed that the naturalness of the test sentences was as low as 6%. The average parsing tree suitability percentage is 98%. This shows that the sentence parser is acceptable even though the naturalness of the test sentences is only 18% on average.

Gallionellaceae pangenomic analysis reveals insight into phylogeny, metabolic flexibility, and iron oxidation mechanisms.

Neutrophilic iron-oxidizing bacteria (FeOB) produce copious iron (oxyhydr)oxides that can profoundly influence biogeochemical cycles, notably the fate of carbon and many metals. To fully understand environmental microbial iron oxidation, we need a thorough accounting of iron oxidation mechanisms. In this study, we show the Gallionellaceae FeOB genomes encode both characterized iron oxidases as well as uncharacterized multiheme cytochromes (MHCs). MHCs are predicted to transfer electrons from extracellular substrates and likely confer metabolic capabilities that help Gallionellaceae occupy a range of different iron- and mineral-rich niches. Gallionellaceae appear to specialize in iron oxidation, so it would be advantageous for them to have multiple mechanisms to oxidize various forms of iron, given the many iron minerals on Earth, as well as the physiological and kinetic challenges faced by FeOB. The multiple iron/mineral oxidation mechanisms may help drive the widespread ecological success of Gallionellaceae.

Mapping of Rubber Forest Growth Models Based on Point Cloud Data

The point cloud-based 3D model of forest helps to understand the growth and distribution pattern of trees, to improve the fine management of forestry resources. This paper describes the process of constructing a fine rubber forest growth model map based on 3D point clouds. Firstly, a multi-scale feature extraction module within the point cloud column is used to enhance the PointPillars learning capability. The Swin Transformer module is employed in the backbone to enrich the contextual semantics and acquire global features with the self-attention mechanism. All of the rubber trees are accurately identified and segmented to facilitate single-trunk localisation and feature extraction. Then, the structural parameters of the trunks calculated by RANSAC and IRTLS cylindrical fitting methods are compared separately. A growth model map of rubber trees is constructed. The experimental results show that the precision and recall of the target detection reach 0.9613 and 0.8754, respectively, better than the original network. The constructed rubber forest information map contains detailed and accurate trunk locations and key structural parameters, which are useful to optimise forestry resource management and guide the enhancement of mechanisation of rubber tapping.

Stronger latitudinal phylogenetic patterns in woody angiosperm assemblages with higher dispersal abilities in China

AbstractAimThe equator‐to‐poles decline in the number of species, namely the latitudinal diversity gradient (LDG), is the most conspicuous pattern in biology, yet the underlying mechanisms of this pattern remain controversial. Species dispersal could have strong effects on large‐scale species distributions but has rarely been considered in understanding the LDG. Here we sought to examine how dispersal ability may influence the latitudinal phylogenetic patterns of woody angiosperm assemblages.LocationChina.TaxonWoody angiosperms.MethodsBased on a highly supported mega‐phylogeny constructed from plastid genomes, we assessed the patterns of phylogenetic relatedness and dissimilarity of 1184 trees with three different seed dispersal modes (i.e. zoochory, anemochory and autochory) in 12 permanent forest dynamic plots covering tropical, subtropical and temperate zones in China.ResultsWe found that, compared with zoochorous and anemochorous species, the less vagile autochorous trees exhibited a much weaker latitudinal pattern in phylogenetic relatedness and higher phylogenetic dissimilarity among plots. The phylogenetic dissimilarity pattern of autochorous trees was explained more by geographic distance than environmental factors, consistent with a dominant role for dispersal limitation.Main ConclusionsOur study, for the first time, demonstrates that seed dispersal mode strongly influences the latitudinal phylogenetic patterns of woody angiosperm assemblages in China and highlights the importance of interaction between dispersal limitation and environmental filtering in determining the large‐scale distribution of forest biodiversity.

Matrix product operator representations for the local conserved quantities of the Heisenberg chain

We present the explicit expressions for the matrix product operator (MPO) representation for the local conserved quantities of the Heisenberg chain. The bond dimension of the MPO grows linearly with the locality of the charges. The MPO has more simple form than the local charges themselves, and their Catalan tree patterns naturally emerge from the matrix products. The MPO representation of local conserved quantities is generalized to the integrable SU(N) invariant spin chain.

Source‐sink patterns on coffee trees related to annual climate variability: An approach through stable isotopes analysis

AbstractStable isotopic determination constitutes a useful tool to identify the processes that control the dynamics of the carbon and nitrogen flow in plants, unravelling the mechanisms of their differential investment under different environments. This work aimed to evaluate the spatiotemporal variation of source‐sink patterns of coffee trees under field conditions in response to climatic conditions through the assessment of stable isotopes. For this purpose, stems, leaves, and fruit samples from coffee trees were collected following a temporal pattern based on the region's climatic characteristics and the plant's phenology and a spatial pattern considering different parts of the canopy. The carbon and nitrogen percentage content, the C/N ratio, and the carbon and nitrogen isotopic compositions (δ13C and δ15N) were determined for all samples. The basal portion of the orthotropic branch was also considered for the isotopic analysis of the tree's growth rings. The results obtained were correlated with the climatic variables of the region through a Pearson correlation analysis (p < .05). Coffee plants showed traditional δ13C values of C3 plants. Temporal δ13C variation was associated with the different growth rates between phenological stages and the use of substrates produced at different times under different environmental conditions leading to differences in photosynthetic discrimination. Spatial δ13C variation was observed with heterotrophic tissues isotopically heavier than leaves, with a significant decrease trend in δ13C values from the top (upper third) to the bottom (lower third), associated with ecophysiological differences between the canopy, isotopic fractionation processes downstream of photosynthetic carbon discrimination, and the fixation of C from other pools. Temporal δ15N variation was associated with the precipitation rates in the region and the fertilization distribution across the tree, while the spatial variation was with the plant's nitrogen assimilation and translocation patterns. The tree growth rings isotopic analyses showed isotopic differences between growth rings of the same plant addressed by the climatic conditions, with precipitation being the primary climatic determinant influencing the fixation and discrimination against 13C. Our results highlight the importance of using stable isotope analysis as a reference point for coffee ecophysiological studies to characterize how the temporal and spatial patterns of δ13C and δ15N emerge and signal the influence of climate on the source‐sink relationship of coffee trees under field conditions.

Quantifying river water contributions to the transpiration of riparian trees along a losing river: lessons from stable isotopes and an iteration method

Abstract. River water plays a critical role in riparian plant water use and riparian ecosystem restoration along losing rivers (i.e., river water recharging underlying groundwater). How to quantify the contributions of river water to the transpiration of riparian plants under different groundwater levels and the related responses of plant water use efficiency is a great challenge. In this study, observations of stable isotopes of water (δ2H and δ18O), 222Rn, and leaf δ13C were conducted for the deep-rooted riparian weeping willow (Salix babylonica L.) in 2019 (dry year) and 2021 (wet year) along the Chaobai River in Beijing, China. We proposed an iteration method in combination with the MixSIAR model to quantify the river water contribution to the transpiration of riparian S. babylonica and its correlations with the water table depth and leaf δ13C. Our results demonstrated that riparian S. babylonica took up deep water (in the 80–170 cm soil layer and groundwater) by 56.5 % ± 10.8 %. River water recharging riparian deep water was an indirect water source and contributed 20.3 % of water to the transpiration of riparian trees near the losing river. Significantly increasing river water uptake (by 7.0 %) and decreasing leaf δ13C (by −2.0 ‰) of riparian trees were observed as the water table depth changed from 2.7 m in the dry year of 2019 to 1.7 m in the wet year of 2021 (p<0.05). The higher water availability probably promoted stomatal opening and thus increased transpiration water loss, leading to the decreasing leaf δ13C in the wet year compared to the dry year. The river water contribution to the transpiration of riparian S. babylonica was found to be negatively linearly correlated with the water table depth and leaf δ13C (p<0.01). The rising groundwater level may increase the water extraction from the groundwater and/or river and produce a consumptive river-water-use pattern of riparian trees, which can have an adverse impact on the conservation of both river flow and riparian vegetation. This study provides new insights into understanding the mechanisms of the water cycle in a groundwater–soil–plant–atmosphere continuum and managing water resources and riparian afforestation along losing rivers.

TACTICAL ANALYSIS OF INDONESIAN NATIONAL FOOTBALL TEAM USING FP-TREE ALGORITHM

Football is the most popular sport in the world, including Indonesia. The current coach of the Indonesian national team is Shin Tae-yong (STY), a former South Korean soccer player. In this study, the researcher intends to study and obtain an overview of the game patterns, tactics and game strategies carried out by STY for the Indonesian national team. The goal to be achieved is gained of tactics and strategies for local coaches in the future. Frequent Pattern Tree (FP-Tree) algorithm was used for this research. Method to analyze match videos and record them in the form of statistical data in a set of data modelling (rows/records) for a particular match session, was used. Then normalize the data, by forming a series of pattern numbers as a representation of the direction of attack in certain situation. As conclusion, the national team's playing pattern, including team formation, how to defend, how to attack. Thus, it makes it easier for coaches to determine the right strategy to beat opponents, when dealing in official matches.

Species Composition and Diversity of Plants along Human-Induced Disturbances in Tropical Moist Sal Forests of Eastern Ghats, India

Plant biodiversity data are prerequisites for the sustainable management of a forest. We used quantitative ecological tools to determine the species composition, diversity (richness and evenness), population structure, distribution patterns, and regeneration status of trees in a Tropical Moist Sal Forest of Eastern Ghats, India. For this purpose, a field inventory was conducted during 2020–2022 in sixteen 1.0 ha forest stands along a human-induced disturbance gradient. A total of 161 species (61 trees, 40 shrubs, 60 herbs) belonging to 77 families and 143 genera were recorded in the 16.0 ha of forest area. The results revealed a significant (p < 0.01) decrease in the tree and shrub species density, basal area, species richness, and diversity along the gradient of disturbance. However, in the case of herbs, the Shannon–Weiner diversity index increased significantly (p < 0.01) with increasing disturbance levels. Irrespective of forest types and disturbance levels, the tree diameter class (10–30 cm) accounted for the highest stem density in the forest. A mixed trend was found in the case of the basal area; the >41 cm diameter class constituted the highest basal area in the Pure Sal Forest while the 10–30 cm class was in the Moist Deciduous Forest without Sal. Tree species richness was found higher in lower diameter classes. Disturbances impacted the distribution pattern of trees; in the Pure Sal Forest, the contagious distribution of trees were 61.54%, 40%, and 12.5% in undisturbed, low-disturbed, and moderately disturbed sites, respectively. The percent of trees showing random and regular distribution increased with the increased level of disturbance in all forest types. The number of tree species having good regeneration decreased with the increased disturbance intensity in all forest types. Frequent grazing, repeated forest fires, and poor soil seed banks at the Moderately Disturbed site were the main reasons for the poor/no regeneration of Pterocarpus marsupium, Adina cordifolia, Terminalia bellerica, and some other economical species. Significant changes in structural attributes of the tree community revealed the impact of human-induced disturbances in the Moist Sal Forests of Eastern Ghats. The disturbance mosaics promoted the growth of many invasive weed species and lianas, depleting the number of valuable species in the forest. This study suggests the adaption of sustainable biodiversity conservation approaches through the active participation of the tribal so that the remnants the Moist Sal Forests of Eastern Ghats can be controlled to prevent further degradation.

Aging Is Associated With Organ-Specific Alterations in the Level and Expression Pattern of von Willebrand Factor.

VWF (von Willebrand factor) is an endothelial-specific procoagulant protein with a major role in thrombosis. Aging is associated with increased circulating levels of VWF, which presents a risk factor for thrombus formation. Circulating plasma, cellular protein, and mRNA levels of VWF were determined and compared in young and aged mice. Major organs were subjected to immunofluorescence analyses to determine the vascular pattern of VWF expression and the presence of platelet aggregates. An in vitro model of aging, using extended culture time of endothelial cells, was used to explore the mechanism of age-associated increased VWF levels. Increased circulating plasma levels of VWF with elevated levels of larger multimers, indicative of VWF functional activity, were observed in aged mice. VWF mRNA and cellular protein levels were significantly increased in the brains, lungs, and livers but not in the kidneys and hearts of aged mice. Higher proportion of small vessels in brains, lungs, and livers of aged mice exhibited VWF expression compared with young, and this was concomitant with increased platelet aggregate formation. Prolonged culture of endothelial cells resulted in increased cell senescence that correlated with increased VWF expression; VWF expression was specifically detected in senescent cultured endothelial cells and abolished in response to p53 knockdown. A significantly higher proportion of VWF expressing endothelial cells in vivo exhibited senescence markers SA-β-Gal (senescence-associated β-galactosidase) and p53 in aged mouse brains compared with that of the young. Aging elicits a heterogenic response in endothelial cells with regard to VWF expression, leading to organ-specific increase in VWF levels and alterations in vascular tree pattern of expression. This is concomitant with increased platelet aggregate formation. The age-associated increase in VWF expression may be modulated through the process of cell senescence, and p53 transcription factor contributes to its regulation.

Exploring the Centennial-Scale Climate History of Southern Brazil with Ocotea porosa (Nees & Mart.) Barroso Tree-Rings

This article explores the dendrochronological potential of Ocotea porosa (Nees & Mart) Barroso (Imbuia) for reconstructing past climate conditions in the General Carneiro region, Southern Brazil, utilizing well-established dendroclimatic techniques. A total of 41 samples of Imbuia were subjected to dendroclimatic analysis to reconstruct precipitation and temperature patterns over the period from 1446 to 2011. Notably, we achieved the longest reconstructions of spring precipitation and temperature for the Brazilian southern region, spanning an impressive 566-year timeframe, by employing a mean chronology approach. To achieve our objectives, we conducted a Pearson’s correlation analysis between the mean chronology and the climatic time series, with a monthly temporal resolution employed for model calibration. Impressively, our findings reveal significant correlations with coefficients as high as |rx,P| = 0.32 for precipitation and |rx,T| = 0.45 for temperature during the spring season. Importantly, our climate reconstructions may elucidate a direct influence of the El Niño—South Oscillation phenomenon on precipitation and temperature patterns, which, in turn, are intricately linked to the natural growth patterns of the Imbuia trees. These results shed valuable light on the historical climate variability in the Southern Brazil region and provide insights into the climatic drivers affecting the growth dynamics of Ocotea porosa (Nees & Mart) Barroso.

Effects of rock lithology and soil nutrients on nitrogen and phosphorus mobility in trees in non-karst and karst forests of southwest China

The primary productivity of terrestrial plants is widely limited by nitrogen (N) and phosphorus (P), and the mobility of N and P in plants is the key to predicting plant growth and development. Non-karst and karst forests soil have different nutrient supply capacities due to the difference in soil parent material, but the effect mechanism of the two soil nutrient conditions on the N and P mobility process of trees remains unclear. In this study, forests dominated by three typical tree species, Eucalyptus maideni, Pinus yunnanensis, and Quercus franchetii were selected as the research objects in non-karst and karst areas of southwest China to investigate the effects of soil nutrient conditions on plants’ N and P foraging, transportation and resorption. The results showed that the rock lithology had significant effects on the soil nutrients, plants’ N and P foraging, transportation, and resorption. The soil total N and P concentrations, soil organic carbon concentration, and pH were higher in karst forests than those in the non-karst forests, but the green leaves N and P concentrations exhibited opposite characteristics. The root foraging potential for N and P in non-karst forests was significantly higher than that in karst forests. The N resorption efficiency of trees in karst forests was higher than that in non-karst forests, but the P resorption efficiency was lower than that in non-karst forests. The trade-offs of foraging, transportation and resorption of trees were adjusted according to changes in nutrient conditions, but the trade-offs of the three processes were not continuous in non-karst and karst forests. Compared with non-karst forests, the decreased degree of root nutrient foraging potential in karst forests was greater than the transportation factor and resorption efficiency. The slow-growing Quercus franchetii among the three typical forests showed better adaptability to foraging, transportation, and resorption of N and P in karst areas. The results revealed the response of different forests’ N and P mobility patterns of trees to different nutrient conditions in non-karst and karst areas, which was helpful to improve the prediction and mechanistic understanding of nutrient cycling in local forest ecosystems.

PENERAPAN ALGORITMA C.45 DALAM MENGANALISA KEPUASAN PELANGGAN PADA PENJUALAN FASHION TRIFT

Fashion thrift sales have become one of the fastest growing industries, especially in this digital era. This research was conducted at one of the thrift businesses in the city of Batam, while the problem with this thrift fashion shop is the lack of stock of goods that attracts customers, because the store buys sack items, likewise this store does not serve purchase orders because items in sacks are available in various types. This study aims to analyze customer satisfaction in data mining techniques to generate new knowledge using the C4.5 classification algorithm, this algorithm uses a data mining method that carries out the process of extracting information about previous decisions. This information is used as information to form a decision tree pattern. Based on all the results of the research stages that have been carried out on the Application of the Decision Tree Classification with the C4.5 Algorithm, it can be concluded that the decision tree analysis produced by the calculation of the C4.5 algorithm shows that the variables that have the highest gain or which are the main factors in determining customer satisfaction are discount variables, product quality and price

Evaluating the bias effects of rooting depth and cryogenic vacuum extraction to quantify root water uptake patterns in deep-rooted apple trees

Accurately assessing isotope information on water sources and mixtures is essential for determining root water uptake (RWU) patterns. This study investigates the impact of rooting depth and cryogenic vacuum extraction (CVE) on the isotopic composition of deep soil water and RWU patterns in a 19-year-old apple orchard on China’s Loess Plateau. We used a Bayesian mixing model (MixSIAR) to analyze corrected isotopic data from soil and xylem water samples collected at different depths, ranging from 3 m to 21.6 m. Our findings reveal a progressive decline in the isotopic composition of deep soil water by 0.63‰ m–1, which decreased deep soil water contributions to transpiration by 1–12% at different rooting depths. The xylem and soil water isotopes became more enriched after correction, with xylem water isotopes closer to the soil water isotope line and water isotopes enriched in the shallow soil layer. Consequently, the contributions of shallow soil water to transpiration increased after xylem water isotope correction but decreased after soil water isotope correction. Monthly averages of these ratios decreased by 12.8% or increased by 8.4%, respectively. After correcting for both soil and xylem water isotopes, the average contributions of shallow soil water increased by 7.4% each month, while those of deep soil water were not consistent. Our findings suggest that rooting depth and CVE have a greater impact on seasonal contribution ratios but a comparatively milder influence on seasonal patterns. This delineation is important for accurately quantifying plant water use strategies.

Recreating structurally realistic tree maps with airborne laser scanning and ground measurements

The estimation of forest attributes representing aspects of structural biodiversity from vast areas is difficult not only because of the lack of agreement on what constitutes a structurally diverse forest, but also due to difficulties in the detection of small trees. However, a structurally diverse forest should have large variation in tree size (i.e., height and diameter), as well as some clustering of trees, as regular tree pattern is typical for managed forests. In this work we developed a framework for building structurally representative tree maps using airborne laser scanning data and a limited number of ground measurements using data from two locations in Finland. In the proposed method, an individual tree detection algorithm is optimized so that the number of undetected trees and false detections is minimized. The ground measurements are then used to train models for predicting the number and location of undetected trees and false detections by resampling the attributes of undetected trees in the training data. This model can then be applied to other areas in the proximity of the ground measurements to build tree maps, with the location, height, and diameter for each tree. The methodology was shown to reproduce the number of trees, the height distribution, and the spatial pattern of the trees with sufficient accuracy for practical use in large-scale mapping of forest attributes. For example, the individual tree detection could find at best about 54% of the trees with an additional 7% of false detections, resulting in a bias of approximately −30%, while with the new method the bias was reduced to ±10% of the stem density. Further research is needed on how to account for tree species when building tree maps.

Distribution of giant trees in the urban areas and western suburbs of Tokyo, Japan

ABSTRACT Giant trees reflect site environmental conditions and to elucidate the distribution pattern of the giant trees, we investigated relationships between giant tree locations and landforms. On the basis of elevation, the landforms of Tokyo were divided into four types (lowland, plateau, hill, and mountain), and tree distribution patterns were divided into five groups, including three sub-types, with occurrence patterns of representative species [I: Frequently lowlands, often plateaux and mountain type (Machilus thunbergi); II: Frequently plateaux, often lowland, hill, or mountain type (Quercus acuta, Prunus speciosa, Taxodium distichum, Liriodendron tulipifera, Cedrus deodara, Aphananthe aspera, and Prunus × yedoensis “Somei-yoshino”) with two subtypes, II-1: Typically plateaux (Cinnamomum camphora, Castanopsis sieboldii, and Ginkgo biloba) and II-2: Frequently plateaux and hills (Zelkova serrata); III: Typically plateaux and hill type (Certis sinensis var. japonica, Torreya nucifera, Carpinus tschonoskii, Quercus myrsinifolia, and Quercus serrata) with one subtype, Frequently plateaux (Prunus jamasakura); IV: Mountains often with plateaux or hill type (Acer pictum subsp. mono, Aesculus turbinate, Abies firma, Cryptomeria japonica, and Cercidiphyllum japonicum); and V: Mountain-limited type (Castanea crenata, Pterocarya rhoifolia, and Fraxinus platypoda)]. Some giant trees, including Quercus crispula, Fagus japonica, Fagus crenata, and Tsuga sieboldii, were distributed in mountainous areas but not on plateaux, hills, or in lowlands. Some unique giant trees (Aphananthe aspera, Certis sinensis var. japonica, and Carpinus tschonoskii) are self-seeding in the wild and found in plateau areas but not mountainous or hilly areas. These results suggest that the distribution of giant trees is influenced by site ecological characteristics, tree physiology, and human management and land-use.

KEANEKARAGAMAN JENIS DAN POLA PENYEBARAN POHON DI HUTAN LINDUNG GUNUNG EGON DUSUN BLIDIT KECAMATAN WAIGETE KABUPATEN SIKKA

This study aims to determine the diversity of species and distribution patterns of trees in the protected forest of Mount Egon, Blidit Hamlet, Waigete District, Sikka Regency and is expected to be useful for the development of science and technology, especially in the field of forestry and plantations. This research was carried out for one month from February 13 to 13. March 2023. The research used was scientific research using survey and transect methods with an observation plot size of 10 x 10. The results obtained from the study found twelve tree species, namely, Hibiscus tiliaceus, Schleichera oleosa, Santalum Album, Dimocarpus longan, Ficus carica, terminalia catappa toona sinensis, averrhoa bilimbi, canarium indicum, shorea spp, dendrocalamus asper, ficus benjamina, with a diversity index of 2,340 with criteria 1<H'<3, the diversity of tree species in the protected forest of Mount Egon is classified as moderate and the distribution pattern with IM< 1 then the distribution pattern is uniform.