Database Of Trees Research Articles

A living inventory of planted trees in South Africa derived from iNaturalist

Trees have a multifaceted influence on ecosystems globally. Treescapes have been manipulated by humans over millennia for ecological, economic, and cultural reasons that have changed over time and continue to change. In South Africa tree planting over three centuries has radically affected the composition of treescapes, contributing important ecosystem services, but also disservices. Rapid global change calls for diverse interventions to create more resilient ecosystems. Many nature-based solutions involve manipulating tree cover in rural and urban landscapes. There is a need for a spatially-explicit database of planted trees in South Africa to serve as the foundation for policy and management decisions.We used the community science platform iNaturalist to create a comprehensive database of planted trees in South Africa. Records were carefully checked to verify the accuracy of taxon identifications, locality data, and categorization as planted rather than wild-growing trees.The cleaned database contained 35,303 records of 805 planted tree taxa; over 90 % of records were identified to species level. Almost a third of taxa (32.2 %) belong to three families: Fabaceae (97 taxa), Myrtaceae (80 taxa) and Arecaceae (78 taxa). Rarefaction and extrapolation curves suggest fairly comprehensive sampling, but several regions are under-sampled. Non-native taxa dominate, with Melaleuca viminalis having the most records. The Western Cape has the highest number of records and taxa, particularly in urban areas. Both native and non-native trees provide key ecosystem services, but non-natives dominate.The database provides the first spatially-explicit open-access resource for guiding decisions on tree planting and the management of planted trees in South Africa. It offers a snapshot of tree planting trends, predominantly from recent years, leading to some underrepresentation of historically planted species. The database has numerous potential uses, including guiding management of trees pests and diseases, urban greening initiatives, monitoring for new invasions, and planning nature-based solutions.

Significant impact of urban tree biogenic emissions on air quality estimated by a bottom-up inventory and chemistry transport modeling

Abstract. Biogenic volatile organic compounds (BVOCs) are emitted by vegetation and react with other compounds to form ozone and secondary organic matter (OM). In regional air quality models, biogenic emissions are often calculated using a plant functional type approach, which depends on the land use category. However, over cities, the land use is urban, so trees and their emissions are not represented. Here, we develop a bottom-up inventory of urban tree biogenic emissions in which the location of trees and their characteristics are derived from the tree database of the Paris city combined with allometric equations. Biogenic emissions are then computed for each tree based on their leaf dry biomass, tree-species-dependent emission factors, and activity factors representing the effects of light and temperature. Emissions are integrated in WRF-CHIMERE air quality simulations performed over June–July 2022. Over Paris city, the urban tree emissions have a significant impact on OM, inducing an average increase in the OM of about 5 %, reaching 14 % locally during the heatwaves. Ozone concentrations increase by 1.0 % on average and by 2.4 % during heatwaves, with a local increase of up to 6 %. The concentration increase remains spatially localized over Paris, extending to the Paris suburbs in the case of ozone during heatwaves. The inclusion of urban tree emissions improves the estimation of OM concentrations compared to in situ measurements, but they are still underestimated as trees are still missing from the inventory. OM concentrations are sensitive to terpene emissions, highlighting the importance of favoring urban tree species with low-terpene emissions.

Tree parameter extraction method based on new remote sensing technology and terrestrial laser scanning technology

Ground LiDAR is a terrestrial LiDAR system that is often used for terrain and geomorphic mapping. Ground-based LiDAR can be used to collect more local and short-range data, making it ideal for mapping smaller areas with high precision. In order to solve the rapid extraction of tree parameters in the national public welfare forest survey, the ground-based LIDAR was used to obtain the point cloud of trees, and the point cloud data was registered, denoised, normalized, sliced, parameter extracted, etc., and the parameters of individual trees in the forest were obtained. The Bland-Altman consistency test is used to test whether the method of extracting tree parameters from point clouds is consistent with the traditional measurement method. The experimental results show that the point cloud data obtained by the ground-based LIDAR can quickly, conveniently and accurately extract the tree parameters, which is consistent with the traditional tree parameter extraction method, and has the advantages than the traditional tree parameter measurement, such as point cloud, image and traceability. It has a unique advantage in establishing a tree database. It is suggested that LIDAR should be used for forest survey in the future.

The fast and the capacious: memory-efficient multi-GPU accelerated explicit state space exploration with GPUexplore 3.0

The GPU acceleration of explicit state space exploration, for explicit-state model checking, has been the subject of previous research, but to date, the tools have been limited in their applicability and in their practical use. Considering this research, to our knowledge, we are the first to use a novel tree database for GPUs. This novel tree database allows high-performant, memory-efficient storage of states in the form of binary trees. Besides the tree compression this enables, we also propose two new hashing schemes, compact-cuckoo and compact multiple-functions. These schemes enable the use of Cleary compression to compactly store tree roots. Besides an in-depth discussion of the tree database algorithms, the input language and workflow of our tool, called GPUexplore 3.0, are presented. Finally, we explain how the algorithms can be extended to exploit multiple GPUs that reside on the same machine. Experiments show single-GPU processing speeds of up to 144 million states per second compared to 20 million states achieved by 32-core LTSmin. In the multi-GPU setting, workload and storage distributions are optimal, and, frequently, performance is even positively impacted when the number of GPUs is increased. Overall, a logarithmic acceleration up to 1.9× was achieved with four GPUs, compared to what was achieved with one and two GPUs. We believe that a linear speedup can be easily accomplished with faster P2P communications between the GPUs.

Application of GIS technologies for accounting plus trees

Introduction 
 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.
 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.
 Materials and Methods
 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.
 Results 
 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.
 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.
 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.
 Conclusions 
 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.
 8 Figs., 1 Table, 20 Refs.

The street tree distribution across a streetscape reflects the social inequality of Latin American cities

Due to the ecosystem services they provide, street trees are fundamental for the quality of life and well-being of the urban human population. However, street trees are usually not equitably distributed across streetscapes, making some demographic groups most vulnerable to the consequences of a poorly managed street tree community. In this study, we evaluated if the socioeconomic characteristics of a large Latin American metropolis (wealth and density of older adults and children) are related to aspects describing characteristics of the street tree community (number of trees, beta diversity, canopy diameter, and proportion of native trees). Our street trees database is comprised of more than 250,000 trees and 559 species. Through a model selection approach, we observed that all socioeconomic characteristics relate to an aspect of the street tree community. The number of trees increased with wealth, but the highest densities of older adults were observed in regions with fewer trees. Canopy cover, conversely, decreased in wealthier neighborhoods and in regions with a higher density of children, while increasing with the density of older adults. Beta diversity of native trees also decreased with wealth. These results not only highlight the luxury effect across the streetscape but reflect the social inequality of Latin American cities: most people from both demographic groups live in regions with a less exuberant tree cover. Our approach can help identify the strengths and weaknesses regarding the plan and management of this street tree community, assisting in the definition of public policies and guidelines for a more sustainable and equitable urban landscape.

Change in urban forest age structure affects the value of ecosystem services provided

To achieve resilience goals, urban planners and decision-makers need accurate information on the benefits provided by urban trees and on the effects that management may have on them. This study investigates the impacts of management and disturbances on urban forest structure and function in Turku, Finland. Using a comprehensive urban tree database and the i-Tree software suite, we assessed the current structure and estimated the value of ecosystem services provided by Turku's urban forest. Additionally, we simulated changes in the urban forest over a 50-year period, considering different tree planting scenarios and the potential outbreak of the Asian longhorned beetle (ALB). Turku's urban forest comprised 38,438 public trees, dominated by Acer platanoides, Pinus sylvestris, Tilia × europaea, and Betula pendula. The estimated carbon storage was 12,336 t, valued at 1.98 million €, with an annual sequestration rate of 284 t (45,549 €/year). The trees also removed 8.97 t of pollutants annually, with an estimated value of 153,273 €. At the current rate of tree planting, the number of trees would decline over the course of 50 years resulting in a gradual decrease in the provision of ecosystem services. Although doubling the tree planting rate could slowly increase carbon storage and sequestration even under moderate ALB attack, it was insufficient to offset the damage caused by ALB if tree mortality rate reaches 50%. Compared to carbon storage and sequestration, changes in urban forest age structure had a more immediate impact on the removal of air pollution. These findings emphasize the importance of prioritizing investments in urban forests on grounds of their capacity to provide diverse ecosystem services. Incorporating these findings into decision-making processes would promote sustainable and resilient urban environments.

Biodiversity data synthesis on trees of Indian Himalayan Region: Policy and management implications

The recent adoption of Kunming-Montreal Global Biodiversity Framework requires empirical synthesis of biodiversity data spanning across broad biogeographic scales to inform conservation policy and management. Although the availability and access to biodiversity databases have recently improved, yet majority of these databases lack sufficient geographic coverage, especially from the biodiversity hotspot regions of developing countries, thereby severely limiting their utility and generalizability across the globe. Here, we present a comprehensive tree database (2199 species) of the Indian Himalayan Region (IHR) – home to two global biodiversity hotspots – collated from a quantitative synthesis of 234 studies published over the last one century. Taking leverage of this novel database, we unravel the patterns of diversity, distribution, and drivers of the trees of IHR. We found that the species richness, compositional similarity, distribution patterns, and biome affiliation of the tree diversity vary significantly across the IHR, with nearly half of the tree species affiliated with the wet tropical biome. Of the 10 climatic and environmental drivers used, the annual mean temperature and elevation width in combination best predicted the variation in tree diversity across the IHR. We also document 117 endemic and 88 threatened tree species in the IHR, which merit conservation priority. Our findings have significant utility in formulating management and restoration strategies for biodiversity conservation across the IHR. Overall, our study showcases a model biodiversity database with wide policy implications in the planning and management of tree-focussed environmental programs to restore the degraded forest landscapes and plantation-specific climate change mitigation strategies in the region.

The experience of preserving ancient trees in Vienna, Austria

Ancient trees hold considerable aesthetic and ecological value within urban environments. The examination of ancient trees and their overall health and condition is an integral part of a comprehensive assessment aimed at preserving these trees and conserving the natural environment within urban spaces. The purpose of the study was to examine the experience of preserving valuable trees growing in urban space. General scientific theoretical methods – analysis and synthesis – were used to work with lists of tree inventory. Heritage trees grow in all districts in Vienna. It was established that ancient trees were given the status of natural monuments since 1936, the dynamics of bequests were traced, and the decades of Vienna’s most active nature conservation activities were determined. The most famous heritage trees in the city were described. The species diversity of monumental trees was analysed, and their taxonomic affiliation was summarised. The heritage trees in Vienna are represented by 49 genera, most of which belong to the phylum of Magnoliophyta. The most common species among protected trees are Platanus orientalis L., Pinus nigra J.F. Arnold, Aesculus hippocastanum L., Quercus robur L., Taxus baccata L., Tilia platyphyllos Scop. Most of heritage trees (60%) are solitary trees. It was evaluated that the general sanitary condition of protected trees is excellent; almost all trees have high vitality and play a leading role in shaping urban landscapes. Every heritage tree possesses a commendable and elevated aesthetic rating. Analysis of the existing inventory of ancient trees in Vienna, their sanitary condition and aesthetic condition will contribute to the environmental awareness of communities and the improvement of management measures for such trees. The obtained results can be used to share the experience of researchers from different countries regarding preserving ancient trees and forming European databases of heritage trees

Association between familial aggregation of chronic kidney disease and its incidence and progression

This study aimed to examine the association between familial aggregation of chronic kidney disease (CKD) and risk of CKD development and its progression. This nationwide family study comprised 881,453 cases with newly diagnosed CKD between 2004 and 2017 and 881,453 controls without CKD matched by age and sex, using data from the Korean National Health Insurance Service with linkage to the family tree database. The risks of CKD development and disease progression, defined as an incident end-stage renal disease (ESRD), were evaluated. The presence of any affected family member with CKD was associated with a significantly higher risk of CKD with adjusted ORs (95% CI) of 1.42 (1.38–1.45), 1.50 (1.46–1.55), 1.70 (1.64–1.77), and 1.30 (1.27–1.33) for individuals with affected parents, offspring, siblings, and spouses, respectively. In Cox models conducted on patients with predialysis CKD, risk of incident ESRD was significantly higher in those with affected family members with ESRD. The corresponding HRs (95% CI) were 1.10 (1.05–1.15), 1.38 (1.32–1.46), 1.57 (1.49–1.65), and 1.14 (1.08–1.19) for individuals listed above, respectively. Familial aggregation of CKD was strongly associated with a higher risk of CKD development and disease progression to ESRD.

Comprehensive Analysis of BR Receptor Expression under Hormone Treatment in the Rubber Tree (Hevea brasiliensis Muell. Arg.).

Brassinosteroids (BRs) are important for plant growth and development, with BRI1 and BAK1 kinases playing an important role in BR signal transduction. Latex from rubber trees is crucial for industry, medicine and defense use. Therefore, it is beneficial to characterize and analyze HbBRI1 and HbBAK1 genes to improve the quality of the resources obtained from Hevea brasiliensis (rubber tree). Based on bioinformatics predictions and rubber tree database, five HbBRI1s with four HbBAK1s were identified and named HbBRI1~HbBRL3 and HbBAK1a~HbBAK1d, respectively, which were clustered in two groups. HbBRI1 genes, except for HbBRL3, exclusively contain introns, which is convenient for responding to external factors, whereas HbBAK1b/c/d contain 10 introns and 11 exons, and HbBAK1a contains eight introns. Multiple sequence analysis showed that HbBRI1s include typical domains of the BRI1 kinase, indicating that HbBRI1s belong to BRI1. HbBAK1s that possess LRR and STK_BAK1_like domains illustrate that HbBAK1s belong to the BAK1 kinase. BRI1 and BAK1 play an important role in regulating plant hormone signal transduction. Analysis of the cis-element of all HbBRI1 and HbBAK1 genes identified hormone response, light regulation and abiotic stress elements in the promoters of HbBRI1s and HbBAK1s. The results of tissue expression patterns indicate that HbBRL1/2/3/4 and HbBAK1a/b/c are highly expressed in the flower, especially HbBRL2-1. The expression of HbBRL3 is extremely high in the stem, and the expression of HbBAK1d is extremely high in the root. Expression profiles with different hormones show that HbBRI1 and HbBAK1 genes are extremely induced by different hormone stimulates. These results provide theoretical foundations for further research on the functions of BR receptors, especially in response to hormone signals in the rubber tree.

Airborne multispectral imagery and deep learning for biosecurity surveillance of invasive forest pests in urban landscapes

Urban and peri-urban trees in major cities provide a gateway for exotic pests and diseases (hereafter “pests”) to establish and spread into new countries. Consequently, they can be used as sentinels for early detection of exotic pests that could threaten commercial, environmental and amenity forests. Biosecurity surveillance for exotic forest pests relies on monitoring of host trees — or sentinel trees — around high-risk sites, such as airports and seaports. There are few publicly available spatial databases of urban street and park trees, so locating and mapping host trees is conducted via ground surveys. This is time-consuming and resource-intensive, and generally does not provide complete coverage. Advances in remote sensing technologies and machine learning provide an opportunity for semi-automation of tree species mapping to assist in biosecurity surveillance. In this study, we obtained high resolution (≥12 cm), 10-band, multispectral imagery using the ArborCam™ system mounted to a fixed-wing aircraft over Sydney, Australia. We mapped 630 Pinus trees and 439 Platanus trees on-foot, validating their exact location on the airborne imagery using an in-field mapping app. Using a machine learning, convolutional neural network workflow, we were able to classify the two target genera with a high level of accuracy in a complex urban landscape. Overall accuracy was 92.1% for Pinus and 95.2% for Platanus, precision (user’s accuracy) ranged from 61.3% to 77.6%, sensitivity (producer’s accuracy) ranged from 92.7% to 95.2%, and F1-score ranged from 74.6% to 84.4%. Our study validates the potential for using multispectral imagery and machine learning to increase efficiencies in tree biosecurity surveillance. We encourage biosecurity agencies to consider greater use of this technology.

Forest structure and individual tree inventories of northeastern Siberia along climatic gradients

Abstract. We compile a data set of forest surveys from expeditions to the northeast of the Russian Federation, in Krasnoyarsk Krai, the Republic of Sakha (Yakutia), and the Chukotka Autonomous Okrug (59–73∘ N, 97–169∘ E), performed between the years 2011 and 2021. The region is characterized by permafrost soils and forests dominated by larch (Larix gmelinii Rupr. and Larix cajanderi Mayr). Our data set consists of a plot database describing 226 georeferenced vegetation survey plots and a tree database with information about all the trees on these plots. The tree database, consisting of two tables with the same column names, contains information on the height, species, and vitality of 40 289 trees. A subset of the trees was subject to a more detailed inventory, which recorded the stem diameter at base and at breast height, crown diameter, and height of the beginning of the crown. We recorded heights up to 28.5 m (median 2.5 m) and stand densities up to 120 000 trees per hectare (median 1197 ha−1), with both values tending to be higher in the more southerly areas. Observed taxa include Larix Mill., Pinus L., Picea A. Dietr., Abies Mill., Salix L., Betula L., Populus L., Alnus Mill., and Ulmus L. In this study, we present the forest inventory data aggregated per plot. Additionally, we connect the data with different remote sensing data products to find out how accurately forest structure can be predicted from such products. Allometries were calculated to obtain the diameter from height measurements for every species group. For Larix, the most frequent of 10 species groups, allometries depended also on the stand density, as denser stands are characterized by thinner trees, relative to height. The remote sensing products used to compare against the inventory data include climate, forest biomass, canopy height, and forest loss or disturbance. We find that the forest metrics measured in the field can only be reconstructed from the remote sensing data to a limited extent, as they depend on local properties. This illustrates the need for ground inventories like those data we present here. The data can be used for studying the forest structure of northeastern Siberia and for the calibration and validation of remotely sensed data. They are available at https://doi.org/10.1594/PANGAEA.943547 (Miesner et al., 2022).

English Long Sentence Segmentation and Translation Optimization of Professional Literature Based on Hierarchical Network of Concepts

The structure of English long sentences is generally complicated, with complicated logical levels, many parallel elements, many modifiers and conjunctions, and long post attributives. Moreover, pronouns in English long sentences often need to be judged according to the context. Complex English long sentences are very common in English and even run through the whole English article. The analysis results of these complex long sentences will seriously affect the quality and readability of machine translation. In this paper, HNC (hierarchical network of concepts) method is improved to realize the segmentation of long sentences, so as to simplify sentence patterns. According to the characteristics of professional literature, this paper puts forward a translation optimization method of professional literature combining HNC with statistics, which greatly improves the recognition efficiency of unknown words by extracting professional terms. The results show that the word segmentation method based on HNC and statistics proposed in this paper has achieved a good word segmentation effect in the open test environment, with an accuracy rate of 93.38% and a recall rate of 94.51%. The conclusion shows that our method can make full use of the knowledge of the source tree database, thereby improving the accuracy of the syntactic model on the target tree database.

An open-access database of infectious disease transmission trees to explore superspreader epidemiology.

Historically, emerging and reemerging infectious diseases have caused large, deadly, and expensive multinational outbreaks. Often outbreak investigations aim to identify who infected whom by reconstructing the outbreak transmission tree, which visualizes transmission between individuals as a network with nodes representing individuals and branches representing transmission from person to person. We compiled a database, called OutbreakTrees, of 382 published, standardized transmission trees consisting of 16 directly transmitted diseases ranging in size from 2 to 286 cases. For each tree and disease, we calculated several key statistics, such as tree size, average number of secondary infections, the dispersion parameter, and the proportion of cases considered superspreaders, and examined how these statistics varied over the course of each outbreak and under different assumptions about the completeness of outbreak investigations. We demonstrated the potential utility of the database through 2 short analyses addressing questions about superspreader epidemiology for a variety of diseases, including Coronavirus Disease 2019 (COVID-19). First, we found that our transmission trees were consistent with theory predicting that intermediate dispersion parameters give rise to the highest proportion of cases causing superspreading events. Additionally, we investigated patterns in how superspreaders are infected. Across trees with more than 1 superspreader, we found preliminary support for the theory that superspreaders generate other superspreaders. In sum, our findings put the role of superspreading in COVID-19 transmission in perspective with that of other diseases and suggest an approach to further research regarding the generation of superspreaders. These data have been made openly available to encourage reuse and further scientific inquiry.

An integrated approach to estimate how much urban afforestation can contribute to move towards carbon neutrality

Urban afforestation is considered a promising nature-climate solution that may contribute to achieve climate neutrality by 2050, since it can increase C-storage and C-sequestration, whilst providing further multiple ecosystem services for citizens. However, the quantification of the CO2 sequestration capacity that may be provided by an urban forest as well as the capacity to impact the city-level C-balance and offset anthropogenic emissions is a complex issue. Methodological approaches, quantity and quality of information contained in urban tree database, and the level of detail of the planned urban forest can strongly influence the estimation of C-sequestration potential offered by urban forests. In this work, an integrated framework based on emission inventory, tree species/morphology and ecosystem modelling has been proposed for the city of Prato, Italy, a representative medium size European city to: i) evaluate the current C-sequestration capacity of urban trees; ii) upscale such capacity with different afforestation scenarios, iii) compare the sink capacity offered by ecosystems with current and projected anthropogenic emissions. Results indicated that the green areas within the Municipality of Prato can sequester 33.1 ktCO2 yr−1 under actual conditions and 51.0 ktCO2 yr−1 under the afforestation scenario which maximize the CO2 sequestration capacity, offsetting the 7.1 % and 11 % of the total emissions (465.8 ktCO2 yr−1), respectively. This study proves that, in the various afforestation scenarios tested, the contribution of urban afforestation to the municipality carbon balance is negligible and that carbon neutrality can only be reached by the substantial decarbonization of emission sectors.

Genome-wide identification and response stress expression analysis of the BES1 family in rubber tree (Hevea brasiliensis Muell. Arg.).

Brassinolide (BR) plays an important role in plant growth, development, and the adaptation adversity process. Moreover, BRI1-EMS-SUPPRESSOR 1 (BES1) genes are crucial transcription factors (TFs) in the BR signaling pathway. To realize the function of HbBES1 family is helpful to improve genetic resources for rubber tree breeding. Based on the rubber tree database, we used bioinformatics to characterize physicochemical properties, gene structure, cis-elements, and expression patterns. These results indicated that there were nine BES1 members in rubber tree, which we named HbBES1-1 to HbBES1-9 and divided into two groups (I and II) based on their genetic relationships. HbBES1 genes in the same group shared similar gene structures and motifs. Cis-acting element analysis showed that the promoter sequences of HbBES1 genes contained many regulator elements that were related to hormone and stress, indicating that HbBES1 genes might be involved in the regulation of hormone and stress signal pathways. Our analysis of tissue specificity revealed that all of the nine HbBES1 members expressed highly in branches. Gene expression profiles under different hormone treatments showed that the HbBES1 gene family was induced to varying degrees under different hormones, HbBES1-3 and HbBES1-9 were extremely induced by ethylene (ETH). These results lay the foundation for further exploration of the molecular mechanism of the BES1 gene family, especially HbBES1-3 and HbBES1-9, regulating plant stress tolerance in rubber tree.

SHOOT: phylogenetic gene search and ortholog inference

Determining the evolutionary relationships between genes is fundamental to comparative biological research. Here, we present SHOOT. SHOOT searches a user query sequence against a database of phylogenetic trees and returns a tree with the query sequence correctly placed within it. We show that SHOOT performs this analysis with comparable speed to a BLAST search. We demonstrate that SHOOT phylogenetic placements are as accurate as conventional tree inference, and it can identify orthologs with high accuracy. In summary, SHOOT is a fast and accurate tool for phylogenetic analyses of novel query sequences. It is available online at www.shoot.bio.

Перспективность применения древесно-кустарниковых растений в озеленении города Краснодар

Nowadays, about half of the world’s population lives in cities. Green spaces, as well as the condition of landscaping facilities and the quality of woody and shrubby plants play an important role in creating a comfortable environment and improving the ecological conditions for people living in the city. The research purpose is to assess the current state of landscaping objects, the quality of woody and shrubby plants and the resistance of tree species to anthropogenic loads using Krasnodar as a case study. The following parks and squares became the research objects: Solnechny Ostrov (“Sunny Island”) Park, Park named after Maxim Gorky, Kuban Stadium Park, Chistyakovskaya Grove, Botanical Garden of Professor I.S. Kosenko, Marshal Zhukov’s Park, Druzhba Narodov Square, Mayskiy Square, Square named after L.G. Gatov, Vishnyakovsky Square, Square named after Ivan Kochubey, Festivalny Square, and Novorozhdestvenskiy Square. The research was carried out in 2016–2019. During the research, 27 options of studies were described, 2634 trees and shrubs, their 50 species and forms related to 2 groups, 21 families and 30 genera were studied. The plantations that occupy large areas of the landscaping sites were sampled for study. An assessment of the state of woody species in Krasnodar was carried out. The results are compared with those obtained by other authors. Among the studied species, 16 woody species meet the recommendations of Dyuval’-Stroyev M.R. and 27 do not meet them; no data is available for 7 species. Having analyzed the main characteristics of native and invasive woody and shrubby species used in landscaping of Krasnodar, we come to the conclusion that the main part of introduced species belongs to the strongly weakened category, while the native species are in the weakened category. At present, the conditions for tree growth in Krasnodar have changed: anthropogenic load has increased. In this regard, there is a need for further inventory of tree species and assessment of woody and shrubby plants to create a complete database of trees and shrubs that are most resistant to the current urban conditions. For citation: Primakov N.V. Prospects for Woody and Shrubby Plants in the Landscaping of Krasnodar. Lesnoy Zhurnal [Russian Forestry Journal], 2022, no. 1, pp. 98–109. DOI: 10.37482/0536-1036-2022-1-98-109

Research Trends in Korea of the Inspiratory Muscle Training Applied to Stroke Patients: A Systematic Review

Purpose : This study aimed to analyze the effectiveness of inspiratory muscle training(IMT) studies for stroke patients conducted over the past 10 years(2011–2020) in Korea. Methods : Previous literature was electronically searched using the RISS, KISS, KCI, and NDSL databases. Tree databases were searched for stroke IMT articles. A total of 12 studies were selected according to the PRISMA guidelines, and the Jeong’g qualitative evaluation criteria were used to refer to the checklist presented by the Scottish Intercollegiate Guideline Network. Results : Twelve studies met the criteria. In a qualitative evaluation on the papers, one study scored 8 out of 10, seven scored between 6 and 7, and four scored 5. Intervention sessions were conducted between 20 and 30 min, each at a frequency of three to five sessions per week, for a total of 4–8 weeks. The results indicated that IMT effectively improved respiratory function, physical activity, and respiratory muscle function in stroke patients. Conclusion : IMT was found to have a positive effect on respiratory function, physical activity, and respiratory muscle function in stroke patients.