Stakeholders and involved parties are crucial in a proper management of forest areas, more so in nature park areas. Urban nature areas and more remote peri-urban areas have objectively the most complex management issues due to the potentially high density of visitors and a diverse range of stakeholders. Such areas can also be valuable nature conservation and biodiversity hotspots, further making stakeholder interactions more complex. In this research, we conduct stakeholder identification for two case study areas – an urban forest nature park and a peri-urban forest nature park, with the aim of developing detailed lists of involved parties, including both public and private entities. We identified three main blocks of stakeholders (regulatory, usage, management), and detailed each group and sub-group for the case study areas. Our main results and conclusions include the identification of minor differences particularly explained by geographical and socio-economic contexts for each of the areas, with the regulatory stakeholder group overlapping the most between the two areas. The potential use of such analysis can improve or develop cooperation between previously unobserved stakeholders, and in research contexts, allow for a greater input from various parties that could have been missed in a more detailed analysis of a research area.

This paper provides an overview of recent progress reached in semi-transparent photovoltaic systems (STPV), which are being assessed as a potential solution to enhance the productivity of plant grown in greenhouses. Utilizing this kind of renewable energy resources, relating with plant growing is attractive solution to increase sustainability for citizens. The aim of this study is to find out recent advances for application of various semi-transparent photovoltaic systems which can be integrated in greenhouses. Solar PVs are among dependable, mature and cost-effective renewable energy systems and solutions, which are promising for building integrated photovoltaics (BIPV) application. The main emerging photovoltaic candidates for BIPV are amorphous silicon, kesterite, chalcopyrite, CdTe, dye-sensitized, organic and perovskite based systems. A monographic study approach has been utilized in this investigation, in ordain to compile and analyse the photovoltaic systems for BIPV mainly investigating and comparing two main parameters: average visible transmittance (AVT) and power conversion efficiency (PCE). The rapid development of new materials and structures for the manufacture of semi-transparent solar panels allows a balance to be struck between AVT, PCE and a comparison of the reviewed materials indicates that organic and perovskite are the most promising for semi-transparent solar panel production and application in greenhouse constructions, based on their PCE and AVT results.

Urban trees, integral to urban environments, demonstrate intricate responses to atmospheric pollutants like particulate matter (PM), tropospheric ozone (O₃), and carbon dioxide (CO₂). Notably, O₃ induces oxidative stress in leaf tissues, while PM, consisting of fine airborne particles, interacts with urban trees through foliar deposition. This interaction is particularly interesting as tree canopies are highly effective filters, capturing and accumulating PM on their surfaces. The present study focused on silver birch, small-leaved lime, and Norway maple seedlings responses to elevated O₃ and CO₂). With and without PM. Maple seedlings exhibited the highest stem height increment, followed by lime and birch. Elevated O₃ and CO₂ without PM led to substantial height increments for lime and maple. Elevated O₃ and CO₂ without PM increased the total polyphenols in lime and maple leaves but decreased the content of total flavonoids in birch and lime leaves. Our findings underscore the adaptability of lime and maple seedlings to elevated O₃ and CO₂, positioning them as promising species for urban environments in the face of changing climates. Birch, while exhibiting biochemical changes, demonstrated less pronounced growth responses. This studyʼs insights into the intricate interactions between urban trees and multiple pollutants, particularly the species-specific responses, are of significant value for urban planning and environmental management.

This study investigates the distribution and carbon content of organic soils in Latvia, leveraging machine learning techniques alongside remote sensing and National Forest Inventory (NFI) data to enhance the precision of organic soil mapping. Our approach integrates data from various sources, including airborne laser scanning (ALS) data, digital elevation models (DEM), depth-to-water (DTW) and wet area maps (WAM), and historical organic soil data. By classifying over 24,000 soil probing measurements across Latvia into distinct peat layer thickness categories, we develop a machine learning model that categorizes the thickness of the organic layer with notable accuracy. Our findings indicate that the model, particularly when employing the xgbTREE algorithm and over-sampling method, successfully identifies areas with peat layers thicker than 40 cm, demonstrating a significant improvement over traditional mapping methods. The study reveals an underestimation of organic soil coverage in Latvia by previous estimates, suggesting a broader distribution than recognized, with the model achieving an accuracy of 0.86 and a kappa value of 0.67. This research not only underscores the efficacy of integrating machine learning and remote sensing for soil mapping but also highlights the critical role of accurate data and models in determining organic soil distribution. The insights gained from this study are vital for policy-making and environmental planning, offering a more detailed understanding of Latviaʼs peatland resources and their conservation needs.

This article examines the importance and necessity of high-level mathematical skills in engineering studies. It analyses the specific mathematical skills required for successful engineering education and their role in engineering studies. The results provide insight into how high-level mathematical skills contribute to the development of engineering competencies and enable engineers to solve complex problem scenarios. Key findings reveal that high-level mathematical skills are indispensable in engineering education, providing the tools needed to solve real-world problems and drive innovation in engineering. Mathematics is the language of engineering. It provides the analytical and problem-solving tools necessary for engineers to design, analyse, and optimize systems, ensuring that they meet safety, efficiency, and performance requirements. Engineers use math as a fundamental tool to make informed decisions and drive technological advancements across various engineering disciplines. Without math, engineering would be severely limited in its ability to design safe, efficient, and innovative solutions to the complex problems that engineers encounter in various industries. The questions contained in the article are investigated using survey data of university students. The purpose of this study is to research the relative applicability and level of knowledge of the learning material learned in secondary educational institutions in mathematics, based on the experience of school graduates and engineering students.

The broadbean seed beetle (Bruchus rufimanus) is a significant pest of faba bean (Vicia faba) both in Latvia and in many other parts of the world. The objective of this study was to check the susceptibility of the faba bean variety ‘Merkurʼ to the broadbean seed beetle in Latvia, comparing it with other popular varieties: ‘Boxerʼ and ‘Lauraʼ. The trials were conducted in 2021 and 2022 at the Research and Study Farm ‘Peterlaukiʼ in Jelgava County and at a commercial farm in Cēsis County. The larval infestation rate of seeds of different varieties, the survival rate of individuals (larvae, pupae, imagines) in the seeds, as well as the percentage of seeds damaged by the pest in the yield were compared. It was observed that ‘Merkurʼ seeds were significantly less infested than ‘Boxerʼ and ‘Lauraʼ seeds. However, the survival rate of larvae in the seeds of ‘Merkurʼ was similar to that in ‘Lauraʼ seeds and higher than in ‘Boxerʼ seeds. The highest proportion of seeds damaged by the pest was found in the ‘Merkurʼ and ‘Boxerʼ yields, varying between 5–75% between years and trial locations. Therefore, it was concluded that the variety ‘Merkurʼ, evaluated from a practical point of view, does not differ from the other two varieties. Without taking additional plant protection measures, the percentage of seeds damaged by the broadbean seed beetle can significantly exceed the maximum limit (3%) specified in the buyersʼ quality criteria.

The study aims to find out the efficiency of periodic training of the harvester (cut-to-length) operator, using the automatically saved data of the harvesterʼs information system. It has been established that logging service providers and training institutions do not analyse the operatorʼs work before starting the training; therefore, the training is carried out according to certain, standard programs, without going into the previous performance of each trainee operator. The research uses data automatically saved by Ponsse harvesters during the year, obtained from Ponsse Manager. The study found that by using automatically saved data of the harvester information and performing data grouping with subsequent analysis, it is possible to determine the progress in the execution of specific stem processing operations and to identify operations where the instructor should pay increased attention during training. The research analysed the data of 3 operators, obtained while working with Ponsse harvesters in clear-cutting. In the study, it was found that operator A reduced stem processing time by 3%, labour productivity increased by 15%, and fuel consumption per l m⁻³ decreased by 14% over 3 months. Operator B, after training, saw a 20% reduction in stem processing time, a 13% increase in work productivity, and a 5% increase in fuel consumption l m⁻³ over 3 months. Operator C had a 10% increase in stem processing time, a 1% increase in labour productivity, and a 2% increase in fuel consumption l m³ after training.

Only less than one percent of the territory of Latvia is occupied by broadleaved (trees having relatively wide flat leaves) forests. The aim of the research is to assess forest vegetation in the island of Upursala of Cirišs Lake. The data is collected in four forest areas of the island. Totally 12 plots, each with an area of 200 m² (20 x 20 m) have been created. In each plot, the accounting of growing trees and deadwood is carried out. The vegetation is measured in each forest area – the projective vegetation cover and cover of each plant species by tree, shrub, herb and moss layer are determined. The research founds that the average stock of growing trees on the island of Upursala is 565.8 m³ ha⁻¹. The average amount of dead wood is 108 m³ ha⁻¹, it consists mainly of fallen deadwood. Totally 45 species are listed in the vegetation plots, of which seven are determinants of European broadleaved forests. The largest number of determinant species of European broadleaved forests has been observed in stands with mixed forests (aspen – small-leaved lime – pedunculate oak, aspen – Scots pine – pedunculate oak and Scots pine – Silver birch – aspen). It can be argued that these stands will become the European broadleaved forests in the future.

Light is one of the most significant environmental factors affecting the growth of plants, as it is the driving force of photosynthesis. Among others, the red and blue light are the most relevant, as these spectral regions are absorbed by chlorophyll the most. In addition, red and blue light trigger specific photomorphogenic responses that allow plants to capture the available light efficiently. Accordingly, the proportion of red and blue light (R:B ratio) is considered one of the most important characteristics of light for plants, as optimal R:B provides balanced growth and photosynthesis. The aim of this study was to evaluate how the in vitro cultures of hybrid aspen (Populus tremula L. × P. tremuloides Michx.) are affected by different R:B ratios under fixed illumination intensity. We examined the growth characteristics of plantlets under wide spectrum LED luminaires with three different R:B proportions – 1:1, 7:3 and 9:1. While photosynthesis-related variables were significantly affected by light, the effect on morphology was less pronounced. Overall, increased proportions of red light decreased the photosynthetic performance of plantlets without giving significant benefits in the form of longer shoots that could be used to facilitate propagation effectiveness. Nonetheless, the effect of light treatment remains at least partially clones-specific and should be considered in case of further application for propagation purposes.

Canopy litterfall is a vital component of forest ecosystems, facilitating nutrient and organic carbon transfer to the soil. Understanding litterfall dynamics in forests is crucial for assessing carbon fluxes at the national level and refining carbon balance estimations. However, information about aboveground litterfall dynamics in old-growth forests remains scarce. The aim of the study was to characterize the annual litterfall carbon input in coniferous old-growth forests on drained and undrained organic soils. In total, 12 old-growth Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) H. Karst) forests stands with the age range of 146–171 years were selected. Using cone-type litter traps, we obtained data on litterfall volumes over a one-year period. Our findings reveal that old-growth forest annual carbon input from litterfall exceeds estimates of mature forest stands aboveground litterfall. In drained sites, mean annual litter carbon input reached 2.80 ± 0.29 t ha⁻¹ yr⁻¹, while in undrained sites, it amounted to 2.17 ± 0.17 t ha⁻¹ yr. Basal area and deadwood showed a close positive correlation with annual litter carbon input, underscoring the peculiarities of late successional forest stand carbon dynamics. Total stand basal area as easily measurable forest inventory parameter was the best predictor of annual litter C input for practical application.