Dominant Tree Research Articles

Assessment of Tree Damage with the Forest Health Monitoring (FHM) Method and the Convolutional Neural Network (CNN) Method

So far, the assessment or measurement of tree damage has only been done using the Forest Health Monitoring (FHM) method. This study aims to determine the types of tree damage using Forest Health Monitoring (FHM) and Convolutional Neural Network (CNN) methods. The research was conducted at the TAHURA WAR Utilization Block and the Computer Science Laboratory at FMIPA Lampung University. Measuring the type of tree damage using the FHM method is carried out on trees that are in the FHM cluster. Identification of tree damage types with the CNN algorithm using the MobileNet architecture. The results showed that there were 13 types of tree damage found, with five types of tree damage that were commonly found (> 60 cases): open wounds (218 cases), cancer (94 cases), Broken / Cracks and stems (87 cases), broken or dead branches (73 cases), and loss of dominant shoots (69 cases). As for the identification results with the CNN method, there were nine out of 13 types of damage that obtained precision, recall, and F1 scores of 100%. Thus, five types of dominant tree damage were found, one of which was open wounds (218 cases), and nine types of tree damage obtained high accuracy values.

Infiltration rate under the most dominant tree stands at the University Green Space: Swietenia macrophylla, Mimusops elengi, and Polyalthia longifolia

Infiltration is crucial for determining how much rainfall enters the soil and how much becomes runoff. The Universitas Sumatera Utara (USU) Campus Medan is one of the green campuses with diverse tree species. The ability of tree stands on the USU Campus Medan to absorb water needs to be studied for flood mitigation. This study aims to analyze the infiltration rate under the most dominant tree stands at the University Green Space: Swietenia macrophylla (mahagony), Mimusops elengi (tanjung), and Polyalthia longifolia (glodokan tiang) using the Horton method. The infiltration measurement uses double ring infiltrometer. The infiltration data will process using Horton Method. The results show that the infiltration rate under mahogany and tanjung stands are included to medium infiltration. While the infiltration rate under glodokan tiang stand is included to fast infiltration. The correlation test on mahogany, tanjung, and glodokan tiang stands indicate a strong correlation between the actual infiltration rate with Horton’s infiltration rate and have a positive trend, so it can be concluded that Horton method can be used to estimate the infiltration rate in each stand.

The effect of forest structural complexity on tick-borne pathogens in questing ticks and small mammals

Forest management is increasingly focused on enhancing structural complexity. An increase in structural complexity is assumed to increase the abundance and diversity of fauna, including vertebrates. This faunal assemblage serves, in turn, as host community for a suite of vectors and their pathogens, so that structural complexity may cascade through a network of interactions in forest ecosystems. Here we use a network of 19 forest plots representing a gradient of structural complexity and dominant tree species (oak, beech, poplar) to test two hypotheses on the effect of structural complexity on the prevalence of tick-borne pathogens. Our first hypothesis is that tick densities will increase with increasing structural complexity, assuming that each life stage has higher chances of finding a suitable host. The second hypothesis is that the pathogen prevalence in ticks and small mammals decreases (cf. dilution hypothesis) or increases (cf. amplification hypothesis) with increasing structural complexity. These expectations are tested through a community-level analysis, looking at twelve pathogens: seven genospecies of Borrelia (B. afzelii, B. bavariensis, B. garinii, B. burgdorferi sensu stricto, B. spielmanii, B. valaisiana and B. miyamotoi), Babesia s.s., Babesia microti, Anaplasma phagocytophilum, Rickettsia helvetica and Spiroplasma ixodetes. We found that more structurally complex forests have a higher density of questing nymphs (in June and July, during the peak of nymph activity). We did not find a clear change in pathogen prevalence with increasing structural complexity in ticks, wood mice and bank vole; the effect was different for the different pathogens and between the different dominant tree species. No clear co-occurrence patterns of pathogens were found. The density of infected nymphs and thus the disease risk is higher in more complex forests. A potential solution is to focus on decreasing the human-tick interactions in forests instead of trying to decrease the number of questing ticks.

Evaluating the impact of historical climate and early human groups in the Araucaria Forest of eastern South America

It has been hypothesized that the Araucaria Forest in southern Brazil underwent expansions in the past, driven either by human groups or by climate fluctuations of the Holocene and Pleistocene. Fossil pollen records of the Paraná pine Araucaria angustifolia, a dominant tree in that forest, provide some insights into when those may have occurred. Still, the timing of those expansions has never been estimated. To infer past range shifts and shed light on their main drivers, we employed next‐generation DNA sequencing (ddRADseq), machine learning, and a comprehensive database of fossil pollen records into a study of historical demographic inference and paleo‐distribution modeling of the Paraná pine. We found that A. angustifolia comprises two populations expanding at different times: one in the Mantiqueira mountain chain, the other in the southern Brazilian plateau. The southern population began to expand during the Last Glacial Period ~ 70 kya, long before human arrival in South America. Still, genetic analyses support that humans later impacted this population, resulting in lower genetic diversity, higher inbreeding, and high levels of gene flow over large distances with a weak pattern of isolation‐by‐distance. It is possible this resulted from human influence on seed dispersal and germination on the southern Brazilian plateau. The Mantiqueira population, in contrast, expanded only recently (~ 3 kya). This timing coincides with Holocene climatic changes and human settlements established further south, although, to date, there is little archeological evidence of human impact in the Mantiqueira. In addition, multitemporal species distribution models built from a combination of present‐day and pollen records infer a range expansion of the Araucaria Forest during glacial times until the cold humid HS1 event (~ 16 kya), when the forest was most widespread, with no evidence of glacial refugia. The combination of genomic and spatial analyses suggests that both human and climatic controls played a role in the dynamics of the Araucaria Forest.

Inverse Domination in X-Trees and Sibling Trees

A set $D$ of vertices in a graph $G$ is a dominating set if every vertex not in $D$ is adjacent to at least one vertex in $D$. The minimum cardinality of a dominating set in $G$ is called the domination number and is denoted by $\gamma(G)$. Let $D$ be a minimum dominating set of $G$. If $V-D$ contains a dominating set say $D^{'}$ of $G$, then $D^{'}$ is called an inverse dominating set with respect to $D$. The inverse domination number $\gamma^{'}(G)$ is the cardinality of a minimum inverse dominating set of $G$. A dominating set $D$ is called a connected dominating set or an independent dominating set of $G$ according as the induced subgraph $\langle D \rangle$ is connected or independent in $G$. The minimum of the cardinalities of the connected dominating sets of $G$ or the independent dominating sets of $G$ is called the connected domination number $\gamma_{c} (G)$ or the independent domination number $\gamma_{i} (G)$ respectively. In this paper, we determine the inverse domination numbers in X-Trees and Sibling Trees. We have also determined the independent domination numbers of both the trees and the connected domination number of Sibling Trees. A result on inverse domination number of some classes of Hypertrees is also included.

Simultaneous Models for the Estimation of Main Forest Parameters Based on Airborne LiDAR Data

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

Transcriptome profiles reveal response mechanisms and key role of PsNAC1 in Pinus sylvestris var. mongolica to drought stress

BackgroundDrought stress severely impedes plant growth, and only a limited number of species exhibit long-term resistance to such conditions. Pinus sylvestris var. mongolica, a dominant tree species in arid and semi-arid regions of China, exhibits strong drought resistance and plays a crucial role in the local ecosystem. However, the molecular mechanisms underlying this resistance remain poorly understood.ResultsHere, we conducted transcriptome sequence and physiological indicators analysis of needle samples during drought treatment and rehydration stages. De-novo assembly yielded approximately 114,152 unigenes with an N50 length of 1,363 bp. We identified 6,506 differentially expressed genes (DEGs), with the majority being concentrated in the heavy drought stage (4,529 DEGs). Functional annotation revealed enrichment of drought-related GO terms such as response to water (GO:0009415: enriched 108 genes) and response to water deprivation (GO:0009414: enriched 106 genes), as well as KEGG categories including MAPK signaling pathway (K04733: enriched 35 genes) and monoterpenoid biosynthesis (K21374: enriched 27 genes). Multiple transcription factor families and functional protein families were differentially expressed during drought treatment. Co-expression network analysis identified a potential drought regulatory network between cytochrome P450 genes (Unigene4122_c1_g1) and a core regulatory transcription factor Unigene9098_c3_g1 (PsNAC1) with highly significant expression differences. We validated PsNAC1 overexpression in Arabidopsis and demonstrated enhanced drought resistance.ConclusionsThese findings provide insight into the molecular basis of drought resistance in P. sylvestris var. mongolica and lay the foundation for further exploration of its regulatory network.

Impact of greening trends on biogenic volatile organic compound emissions in China from 1985 to 2022: Contributions of afforestation projects

The rapid expansion of green areas in China has enhanced carbon sinks, but it also presents challenges regarding increased biogenic volatile organic compound (BVOC) emissions. This study examines the impact of greening trends on BVOC emissions in China from 1985 to 2001 and from 2001 to 2022, focusing on evaluating long-term trends in BVOC emissions within eight afforestation project areas during these two periods. Emission factors for 62 dominant tree species and provincial Plant Functional Types were updated. The BVOC emission inventories were developed for China at a spatial resolution of 27 km × 27 km using the Model of Emissions of Gases and Aerosols from Nature. The national BVOC emissions in 2018 were estimated at 54.24 Tg, with isoprene, monoterpenes, sesquiterpenes, and other BVOC contributing 26.94 Tg, 2.29 Tg, 0.44 Tg, and 24.57 Tg, respectively. Over the past 37 years, BVOC emissions experienced a slow growth rate of 1.7 % (0.79 Tg) during 1985–2001, followed by a significant increase of 12 % (6 Tg) from 2001 to 2022. BVOC emissions in the eight afforestation project areas increased by 2 % and 20 % during the two periods. From 2001 to 2022, at the regional scale, the Shelterbelt program for the middle reaches of the Yellow River area exhibited the largest rate of increase (43 %) in BVOC emissions. The Shelterbelt program for the upper and middle reaches of the Yangtze River made the most largest contribution (45 %) to the national increase in BVOC emissions. Afforestation projects have shifted towards planting more broadleaf trees than needleleaf trees from 2001 to 2022, and there also showed a change from herbaceous plants to broadleaf trees. These trends have led to higher average emission factors for vegetation, resulting in increased BVOC emissions. It underscores the importance of considering BVOC emissions when evaluating afforestation initiatives, emphasizing the need to balancing ecological benefits with potential atmospheric consequences.

Carbon budget at the individual-tree scale: dominant Eucalyptus trees partition less carbon belowground.

Large trees in plantations generally produce more wood per unit of resource use than small trees. Two processes may account for this pattern: greater photosynthetic resource use efficiency or greater partitioning of carbon to wood production. We estimated gross primary production (GPP) at the individual scale by combining transpiration with photosynthetic water-use efficiency of Eucalyptus trees. Aboveground production fluxes were estimated using allometric equations and modeled respiration; total belowground carbon fluxes (TBCF) were estimated by subtracting aboveground fluxes from GPP. Partitioning was estimated by dividing component fluxes by GPP. Dominant trees produced almost three times as much wood as suppressed trees. They used 25 ± 10% (mean ± SD) of their photosynthates for wood production, whereas suppressed trees only used 12 ± 2%. By contrast, dominant trees used 27 ± 19% of their photosynthate belowground, whereas suppressed trees used 58 ± 5%. Intermediate trees lay between these extremes. Photosynthetic water-use efficiency of dominant trees was c. 13% greater than the efficiency of suppressed trees. Suppressed trees used more than twice as much of their photosynthate belowground and less than half as much aboveground compared with dominant trees. Differences in carbon partitioning were much greater than differences in GPP or photosynthetic water-use efficiency.

DETERMINING THE SPECIES COMPOSITION OF FOREST VEGETATION IN THE KOSTANAY REGION USING REMOTE SENSING DATA

During the scientific investigation, woody species of forest vegetation were identified and a map of forest vegetation in the Kostanay region was produced using various data sources: field materials, Earth remote sensing data, and ArcGIS10.9 software. An algorithm was developed to detect tree species based on Landsat 9 satellite imagery, characterized by high spatial resolution. Recognition of dominant tree species was performed using various combinations of spectral bands from Landsat 9 imagery, analysis of vegetation indices (NDVI, EVI) across different seasons, and supervised local adaptive classification. The obtained data were validated against field research materials (August-September 2023) and forest management records. The chosen algorithm implements contemporary approaches to acquiring and processing necessary data from satellite remote sensing imagery. Further differentiation and creation of the forest vegetation map of the Kostanay region were based on the established map of tree species, digital elevation model, geological-geomorphological features, field research, thematic maps, and physical geography of the region. As a result of the conducted research, six classes of forest stands were delineated in the Kostanay region, including light-coniferous and deciduous tree species such as pine, birch, aspen, larch, shrubbery, and meadow vegetation. These research findings and the algorithm developed can be applied to other study areas and hold practical significance.

Modified Zagreb index and total domination in trees

Let [Formula: see text] be a simple connected graph. The modified first Zagreb index is denoted by [Formula: see text] is defined as [Formula: see text]. We present a lower bound for [Formula: see text] in terms of order and total domination number for trees and characterize the extremal trees attaining the bound.

Estimating the optimal vegetation coverage for the dominant tree and shrub species over China’s northwest drylands

Estimating the optimal vegetation coverage for the dominant tree and shrub species over China’s northwest drylands

INDIGENOUS FODDER TREE SPECIES COMPOSITION, BIOMASS YIELD AND SOCIOECONOMIC CONTRIBUTION IN SIDAMA RIGIONAL STATE, ETHIOPIA

<p><strong>Background</strong>. Fodder trees are integral components of agroforestry system in the tropics. Indigenous fodder trees (IFT) are grown in Sidama, Ethiopia, for different purposes. However, their composition, biomass yield and socioeconomic importance are inadequately studied. <strong>Objective</strong>. To assess species composition, biomass yield and socioeconomic contribution of IFT. <strong>Methodology</strong>. Three districts and 9 kebeles were purposively selected, from which 273 households were randomly selected for household survey. Sixty households were randomly selected for inventory within nested quadrats of 20 x 20 m. Semi-structured questionnaires and 36 key informants were used to collect primary data. <strong>Results</strong>. Twenty-eight IFT species belonging to 26 genera and 24 families were identified in three agroecologies. Species richness in lowland (11.08) was higher than in highland (9.6) and midland (7.7) (p < 0.001). Similarly, lowland (1.5) was more diverse than midland (1.2) and highland (0.8) (p < 0.001). <em>Arundinaria alpine, Hygenia abyssinica </em>and<em> Erythrina brucei </em>were dominant IFT, altogether accounted for 72.35% of the total basal area. In midland, <em>Cordia africana</em>, <em>Ficus sur, Dracaena steudneri</em> and <em>Melleitia ferruginea</em> were dominant species, and <em>Acacia albida, A. tortolis,</em> <em>Balanites aegyptiaca</em> and <em>C. africana</em> were dominant in lowland, altogether accounting for 56.1 and 76.72% of the total basal area, respectively. <em>E. brucei</em>, <em>Dracaena steudneri</em> and <em>C. africana </em>had the highest biomass yield in highland, midland and lowland, respectively (p < 0.05). Farmers with large land sizes, small family sizes, practicing agroforestry, and having awareness and interest in fodder trees had significantly affected the decision to have IFT. In addition to fodder supply, IFT contributes to soil fertility improvement, income sources, and timber production. <strong>Implication</strong>. The current findings indicated that the dominant fodder tree species with the highest biomass yield can be an alternative source of fodder and used for enhancing the livelihood of farmers in the study area. <strong>Conclusion</strong>. The most abundant and highly dominant species in the three agroecologies contributed to higher biomass yield and can be a potential feed source. </p>

Geospatial Inventory of the Galakand Forestry Area Utilizing GIS Database and Remote Sensing Techniques

This study investigated the dramatic reduction of forested areas in Azerbaijan, exceeding 50% over the past two centuries, largely due to increased wood production. Focusing on the period between 1880 and 1990, it analyzed the impact of timber harvesting on the composition of dominant tree species, with a special focus on beech trees, in the Galakand forestry area. Utilizing GIS databases and remote sensing techniques, the research assessed the changes in forest cover and species distribution, highlighting the critical transition from lush beech and oak forests to areas dominated by hornbeam, east hornbeam, oak-hornbeam, and juniperus-bush light forests. The study demonstrated the negative consequences of historical overexploitation, advocating for forest farming practices that promote the recovery and preservation of native forest ecosystems. Key findings revealed a marked decline in valuable wood species due to intensive logging activities, particularly between 1880 and 1914, and the detrimental effects of forest renewal cabins established from 1930 to 1970. The outlined measures in the study highlighted that the forest primarily comprises wooded areas (reserves with a completeness of 0.1-0.2, clearings, and clearings), non-forest lands repurposed as pastures and forested pastures with a density ranging from 0.3 to 0.4. Overall, the findings underscore the importance of sustainable forest management practices to reverse the adverse effects of historical overexploitation and preserve the biodiversity of Azerbaijan's ecosystems. The paper emphasized the necessity of sustainable forest management to reverse the damage and protect Azerbaijan's biodiversity to enhance measures for sustainable forestry, along with the critical role of advanced GIS and remote sensing in monitoring and conserving forest resources.

Eco-physiological adaptation strategies of dominant tree species in response to canopy and understory simulated nitrogen deposition in a warm temperate forest

Nitrogen (N) is an indispensable element for plant growth and survival. The increased global N deposition due to human activities has aroused attention to forest ecosystems, but most studies have not considered the process of N interception, assimilation, and leaching in forest canopy. To investigate the responses and adaptive strategies of dominant tree species in a warm temperate forest to atmospheric N deposition, this study implemented five treatments: control treatment, canopy simulated low N deposition, canopy simulated high N deposition, understory simulated low N deposition, and understory simulated high N deposition. The morphological and physiological traits and nutrient uptake strategies of three dominant tree species (Liquidambar formosana, Quercus acutissima, and Quercus variabilis) in warm temperate deciduous broad-leaved forest were studied under different forms and levels of stimulated N deposition. The results showed that the specific leaf area (SLA) of the three dominant tree species decreased under high N application. To optimize resource absorption and improve nutrient transport rates, the specific root length (SRL) and specific root area (SRA) of the three tree species tended to decrease, while the average root diameter (ARD) increased. Under canopy N deposition (CAN), the contents of carbon (C), N, total chlorophyll (Tchl), and total amino acids in Q. variabilis leaves were lower than those under understory N deposition (UAN) treatment. Furthermore, principal component analysis (PCA) revealed the differences between different genera (L. formosana and Q. variabilis, L. formosana and Q. acutissima) under various N treatments, and there was no significant difference between the same genus (Q. variabilis and Q. acutissima). The results indicated that the eco-physiological characteristics of different tree species under N deposition treatment were species-specific, and traditional UAN perhaps exaggerated the effect of atmospheric N deposition on tree growth characteristics. Our study considers the retention and redistribution of forest canopy, which is more in accordance with the natural N deposition, and helps us to understand the eco-physiological responses of dominant tree species in forest ecosystem to atmospheric N deposition.

Význam buku lesního ve střední Evropě v období klimatické změny: přehled současných poznatků

In the period of ongoing global climate change, ecosystems, including Central European forests, face significant challenges such as summer droughts and heat waves, which increase the climate risks also for the European beech (Fagus sylvatica L.), an important and dominant broadleaved tree species in this region. This article provides a comprehensive review of current knowledge on the adaptation strategies of European beech in response to changing climatic conditions, highlighting its ecological demands, development of taxonomy, ecological and economic importance and exploring its resilience, growth characteristics, and challenges such as water regime, pests, diseases, and the impact of climate change. A key finding is that despite the various stressors affecting European beech, adaptive management and the use of mixed forest stands can significantly contribute to its conservation and sustainable use. The importance of integrating the genetic diversity and adaptive capacity of European beech into forestry practices is emphasised. The review of 203 studies highlights the need for further research focused on understanding the interactions between European beech and a changing climate in order to develop more effective strategies for its conservation and sustainable management in the future.

Effect of site, silviculture and tree social status on internal checking variation in plantation-grown Eucalyptus nitens

ABSTRACT Internal checking is a wood-drying defect that affects many tree species, including eucalypts, and can adversely affect the recovery of high-quality timber. We studied the patterns of within- and between-tree variation in wood checking from three Eucalyptus nitens silvicultural trials and determined the predictability of wood checking from wood properties. We hypothesised that changed wind exposure and inter-tree competition due to thinning would increase wood checking. In total, 144 trees from two silvicultural treatments (thinned/unthinned) and three social status classes per site (dominant/subdominant/suppressed) were sampled. Regardless of site, social status and silvicultural treatment, longitudinal and radial variation within trees was the major source of variation in checking. Checking was concentrated longitudinally in bottom logs and radially in the middle of wedges, with a shift in checking towards the cambium in the thinned treatment. On average, dominant trees in the thinned treatment had higher levels of checking than dominant trees in unthinned treatments at all sites, but the opposite trend was found for suppressed trees. Wedge checking was poorly predicted using non-destructive traits assessed on standing trees. Our models accounted for at most 22% of the variation in wedge checking and the best predictors were the destructive measures of wedge collapse. With most checking occurring in lower logs, future studies should concentrate on reducing checking in bottom logs, which are typically pruned for clearwood products.

Hierarchical Integration of UAS and Sentinel-2 Imagery for Spruce Bark Beetle Grey-Attack Detection by Vegetation Index Thresholding Approach

This study aimed to examine the efficiency of the vegetation index (VI) thresholding approach for mapping deadwood caused by spruce bark beetle outbreak. For this, the study used upscaling from individual dead spruce detection by unmanned aerial (UAS) imagery as reference data for continuous spruce deadwood mapping at a stand/landscape level by VI thresholding binary masks calculated from satellite Sentinel-2 imagery. The study found that the Normalized Difference Vegetation Index (NDVI) was most effective for distinguishing dead spruce from healthy trees, with an accuracy of 97% using UAS imagery. The study results showed that the NDVI minimises cloud and dominant tree shadows and illumination differences during UAS imagery acquisition, keeping the NDVI relatively stable over sunny and cloudy weather conditions. Like the UAS case, the NDVI calculated from Sentinel-2 (S2) imagery was the most reliable index for spruce deadwood cover mapping using a binary threshold mask at a landscape scale. Based on accuracy assessment, the summer leaf-on period (June–July) was found to be the most appropriate for spruce deadwood mapping by S2 imagery with an accuracy of 85% and a deadwood detection rate of 83% in dense, close-canopy mixed conifer forests. The study found that the spruce deadwood was successfully classified by S2 imagery when the spatial extent of the isolated dead tree cluster allocated at least 5–7 Sentinel-2 pixels.

The epidemic forest reveals the spatial pattern of the spread of acute respiratory infections in Jakarta, Indonesia

Acute respiratory infection (ARI) is a communicable disease of the respiratory tract that implies impaired breathing. The infection can expand from one to the neighboring areas at a region-scale level through a human mobility network. Specific to this study, we leverage a record of ARI incidences in four periods of outbreaks for 42 regions in Jakarta to study its spatio-temporal spread using the concept of the epidemic forest. This framework generates a forest-like graph representing an explicit spread of disease that takes the onset time, spatio-temporal distance, and case prevalence into account. To support this framework, we use logistic curves to infer the onset time of the outbreak for each region. The result shows that regions with earlier onset dates tend to have a higher burden of cases, leading to the idea that the culprits of the disease spread are those with a high load of cases. To justify this, we generate the epidemic forest for the four periods of ARI outbreaks and identify the implied dominant trees (that with the most children cases). We find that the primary infected city of the dominant tree has a relatively higher burden of cases than other trees. In addition, we can investigate the timely (Rt\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R_t$$\\end{document}) and spatial reproduction number (Rc\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R_c$$\\end{document}) by directly evaluating them from the inferred graphs. We find that Rt\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R_t$$\\end{document} for dominant trees are significantly higher than non-dominant trees across all periods, with regions in western Jakarta tend to have higher values of Rc\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R_c$$\\end{document}. Lastly, we provide simulated-implied graphs by suppressing 50% load of cases of the primary infected city in the dominant tree that results in a reduced Rc\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R_c$$\\end{document}, suggesting a potential target of intervention to depress the overall ARI spread.

The outer-independent edge-vertex domination in trees

The outer-independent edge-vertex domination in trees