Indicator Values Research Articles

Investigation of the Dynamic Relationship between Oil Temperature and Bearing Gearbox Condition Indicator Values for the Bell 407 Helicopter Based on Cointegration Analysis

The primary objective of this study is to investigate the dynamic relationship between oil temperature and the Bearing Gearbox Condition Indicator (BGCI) values of the Bell 407 helicopter. To achieve this goal, we employ robust econometric tools, such as unit root tests, cointegration tests, and Autoregressive Distributed Lag (ARDL) models for both, long-run and short-run estimates. Our findings indicate that variable temperature tends to converge to its long-run equilibrium path in response to changes in other variables. The results of the ARDL analysis confirm that spectral kurtosis, inner race, cage, and ball energy significantly contribute to the increase in temperature. Furthermore, we use the impulse response function (IRF) to trace the dynamic response paths of shocks to the system. The identification of a cointegrating relationship between oil temperature and BGCI values suggests a practical and significant connection that can potentially be used to predict hazardous changes in oil temperature using BGCI values, which is an important implication for enhancing the safety and reliability of helicopter operations. This study presents a promising direction for condition monitoring (CM) in rotating aircraft machinery, emphasizing the potential of integrating temperature data to simplify the diagnostic process while still achieving reliable results.

The Potential Role of Phytoplankton Functional Groups Under Anthropogenic Stressed Wetlands: Characterizing The Environmental Sensitivity.

Anthropogenic and climatic changes are continuously altering the freshwater plankton, necessitating an evaluation of the complex structure of plankton communities to understand and mitigate these impacts. In this context, the present study focuses on evaluating the structure of plankton communities, specifically Phytoplankton Functional Groups (FGs) for assessing the environmental sensitivity of wetlands under changing scenario. These FGs are defined by shared adaptive features rather than taxonomic traits. Over the period from 2016 to 2018, two ecologically distinct wetlands were examined, analysing their phytoplankton FGs and their relationship with water quality parameters. Ecohydrological data revealed significant seasonal variations (p ≤ 0.05) in key parameters such as water depth, temperature, pH, electrical conductivity, dissolved oxygen, total alkalinity, total hardness, NO3-N, and PO4-P. Notably, there were no significant differences observed among the sampling stations within each wetland. A total of 125 phytoplankton genera/species were classified into 23 FGs in the open wetland and 22 FGs in the closed wetland. Spatial and seasonal analyses of dominant FGs suggested both wetlands were experiencing pollution pressures. This study highlights the powerful role of phytoplankton functional groups (FGs) as bioindicators of wetland health, uncovering pollution pressures. In open wetlands, 15 phytoplankton FGs with 36 key taxa (Indicator Value ≥ 40%) emerged as critical indicators, while in closed wetlands, only 10 FGs with 17 taxa were identified. To assess eutrophication, the occurrence of these indicator species was evaluated using BVSTEP function analysis. The study recommends pollution reduction in catchment areas and restoration of riverine connectivity to enhance FG diversity. Phytoplankton FG methodologies are deemed effective for assessing the environmental sensitivity of wetlands significantly impacted by human activities. This research offers a scientific foundation for the evaluation and restoration of wetland ecosystems.

Rapid declines in species diversity and occurrence of common plant species are related to nutrient availability and soil moisture in open habitats

AbstractAimsEnvironmental changes in Europe influence plant community composition, but the literature quantifying these changes often shows inconsistent trends, due mostly to heterogeneous survey methods. Here, we investigated temporal changes in plants over 12 years at the species and community level at a regional scale, using a standardized, plot‐based monitoring scheme.LocationData originated from 1,389 permanent plots of a standardized monitoring scheme targeting plant communities. Plots were distributed in the Burgundy region (France), initially grouped into 175 (2 km × 2 km) grid cells containing eight 10‐m2 plots each, that were surveyed in at least 2 years between 2009 and 2020.MethodsWe characterized changes in vascular plants in 10‐m2 plots by examining the temporal changes in the probability of occurrence of common species, changes in species diversity using species richness, Shannon–Wiener and Pielou's indices and changes in abundance‐weighted mean community ecological preferences using Ellenberg indicator values.ResultsAcross 198 common species, probability of occurrence in the region has shown a decline since 2009. This decline is associated with a general decrease by 13% of both species richness and the Shannon index between 2009 and 2020. This trend was stronger in annual crops and grasslands, whereas forest diversity remained relatively constant over time. Pielou's index diminished on average, except in natural forests. Mean community Ellenberg indicator values suggested slight changes in plant community composition, with an increasing preference for nutrient‐poor soils and Atlantic conditions over time.ConclusionsThe observed biodiversity loss in the Burgundy region is consistent with a widespread shift in community composition in response to environmental change. Existing conservation measures do not seem to compensate for the average losses, indicating that these measures are still inadequate to protect plant communities. Our approach also emphasizes the speed at which plant communities are changing and thus the need for better monitoring of the European flora.

Prioritizing conservation sites for multi-pond systems to maintain protection of water quality in a fragmented agricultural catchment

Precise targeting of conservation practices to the most effective sites in multi-pond systems (MPS) is critical for resource optimization and water quality improvement. Previous studies generally prioritized ponds for conservation practices considering nutrient removal efficiency. However, they have frequently overlooked the role of ponds in sediment interception and the impact of human activities and environmental factors around the pond. Herein, the present study developed and applied a novel framework for pond prioritization by integrating the Pressure-State-Response (PSR) model, graph theory, and K-mean clustering. The framework consists of three components. An indicator system is developed to represent the nutrient removal performance of any MPS, impacts on catchment sediment connectivity, external threats, and human-initiated conservation. A flow path network considering natural and artificial elements was constructed to calculate indicator values. A cluster analysis was conducted on the index values of different ponds, and a hierarchical sorting method were used to prioritize ponds. The framework was applied to the Guilinqiao Catchment, a typical fragmented agricultural catchment in the Yangtze River Basin, China. The study has quantified the Pressure, State, and Response indices of different ponds in this catchment, prioritized the ponds, and drawn recommendations for conserving MPSs based on field surveys and remote sensing data. Ponds with higher Pressure index, higher State index, and lower Response index scores should be targeted as conservation priorities. This framework provides an effective method for ensuring management of MPSs to sustainably maximize water cleanup capacity with limited resources.

The role of pollen and NPP research in palaeoenvironmental reconstruction of the Neolithic archaeological site “Gorjani-Topole” (Slavonia region, eastern Croatia)

The palynological study of eight samples from the Gorjani-Topole archaeological site was conducted with the aim of palaeoenvironmental reconstruction. In total, 44 different palynomorphs were recorded: 12 pollen taxa, 23 fungal spores/remains, four algal cysts, one amoebae and four palynomorphs of unknown origin. Among the non-pollen palynomorphs, Chomotriletes (previously Pseudoschizaea) occurred with the greatest frequency and abundance. The low pollen richness accompanied by the presence of only a few sporopolleninrich pollen types indicates unfavourable preservation conditions in the analysed core samples. The dominance of erosion/desiccation indicators supports the scenario of significant oscillations of the hydrological level in the sediments, with periodic drying of the substrate. Although the interpretation of changes in plant cover, due to the reduced pollen spectrum, is not feasible, it is still possible to indicate paleoecological trends and partially interpret them, considering the indicator value of the few preserved palynomorphs. The findings of cultivated grass pollen (Cerealia) and other anthropogenic indicators including weed pollen (Convolvulus arvensis) are of great importance. Moreover, Riccia moss spores or fungal Epicoccum spores could also indicate the anthropogenic impact on the study area.

The influence of unconventional assembly techniques on the comfort indicators of waterproof materials

The present paper aims to highlight the correlations between the comfort indicators of waterproof cotton-based fabrics, and the specific parameters of unconventional assembly technology. The materials considered include layers of Gore-Tex film, serving as substitutes for waterproof materials, intended to manufacture outerwear products such as protective equipment (jackets and overalls), which are breathable waterproof membranes. The comfort indicator values were obtained through standardised methods, and data processing and representation in two-dimensional (2D) and three-dimensional (3D) systems using correlation/graphing methods were carried out in Excel software, and using Jandel Table Curve 3D v2. Although experimental research can be extended to include specific functions related to durability indicators, this study focused theoretically and experimentally on how the variation in temperature of the low-pressure hot air jet can lead to changes in the vaporization coefficient, air permeability index, and thermal conductivity coefficient. The relationship between the comfort indicator values (thermal conductivity coefficient, air permeability index, and vapour permeability coefficient) of the considered materials and the treatment parameters of the installation (pressure, temperature, velocity) is expressed through statistically adequate mathematical models, highlighted by a correlation coefficient R = 0.983, with significance certified by the Fischer test. The study of comfort indicators was conducted under optimized treatment parameters, ensuring durability and presentation value functions in the treatment zone remain unchanged compared to those of the base materials.

An Evidential Reasoning Method of Comprehensive Evaluation of Water Quality Based on Gaussian Distribution

This study provides an evidential reasoning method for water quality evaluation based on Gaussian distribution to handle the problem of comprehensive water quality evaluation for a region across a period (multiple sections and multiple time points). The method turns the collection of observed water quality indicator values into a probability distribution of water quality grades by using the Gaussian distribution to compute the confidence assessment of water quality grades over one period. It eliminates the subjectivity involved in determining confidence levels and the problem of information loss during data fusion that arises with conventional approaches. The probability distribution of each assessment grade is then determined by repeatedly synthesizing evidence of the same water quality grade using the improved evidential reasoning synthesis rule. To avoid the subjectivity included in experience-based weight settings, principal component analysis (PCA) is utilized to calculate the weights of water quality indicators based on contribution rates and load coefficients. In the end, utility theory is presented to modify the discrete probability distribution of precise numerical expressions, offering thorough results for the evaluation of water quality and facilitating the comparison of various water quality grades. Using the Xiangjiang River Basin as a case study, the proposed evaluation method is contrasted with popular techniques for assessing water quality, including the Single-Factor Evaluation Method, the Fuzzy Comprehensive Evaluation Method, and the Evidential Reasoning Comprehensive Evaluation Method. The findings suggest that the evidence reasoning approach for evaluating water quality that is based on Gaussian distribution is more rational, accurate, and scientific. Additionally, empirical studies on the annual water quality trends in various regions, the upstream, midstream, and downstream trends, and the water quality trends during wet and dry periods are conducted using this method to assess and analyze changes in water quality in the Xiangjiang River Basin during the “11th Five-Year Plan” and “12th Five-Year Plan” periods. The analysis findings demonstrate that, even if the rate of progress has slowed, the Xiangjiang River Basin’s overall water quality has been steadily improving since management and protection measures were put in place. This shows that the preventive and control efforts implemented in the “11th Five-Year Plan” and “12th Five-Year Plan” periods were successful; nevertheless, carrying out the current tactics might only have a limited impact. As a result, more advanced and creative approaches are required to encourage the ongoing enhancement of the water quality in the Xiangjiang River Basin.

Study on the composition and properties of EME-SBS-Nano ZnO high modulus asphalt material

The objective of this research is to address the rut problems in asphalt pavements and to resist the permanent plastic deformation with the increasing heavy traffic loads. In this paper, a new type materials of high modulus asphalt was developed by incorporating styrene–butadiene–styrene (SBS) and zinc oxide nanoparticles (nano ZnO) with an (EME)-type high modulus modifier, guided by the synergistic effects and the preparation methods of High-speed shear. The basic road performance, mechanical response and thermal stability of the new high modulus asphalt materials were analysed through basic physical indicator tests, dynamic shear rheometer tests, thermogravimetric analysis (TGA), the time–temperature superposition principle, the Refutas model, and the Christensen-Andersen-Marasteanu model. The optimal results demonstrate that the optimal blend ratio of the developed asphalt is 12% EME/8% SBS/1.5% ZnO. Under this composition, the road performance indicator values of softening point, penetration and ductility of the modified asphalt met the standard requirements. The dynamic shear rheometer tests demonstrates that the inclusion of SBS and nano ZnO considerably enhanced the shear resistance and recovery deformation capacity of EME, effectively improving the high-temperature deformation resistance of asphalt. Furthermore,the Refutas and the Christensen-Andersen-Marasteanu model fitting results showed that adding SBS and nano ZnO considerably improved the temperature sensitivity of the EME types high modulus modified asphalt and exhibiting low frequency sensitivity. Compared to PR Module-type high modulus modifier(PRM),TGA reveals that the maximum thermal weight loss of EME-SBS-ZnO decreased by 3.5441%, indicating better thermal stability and the major character of SBS,EME and asphalt is physical reaction. Moreover, EME-nano ZnO-SBS high modulus asphalt at 64 °C shows Jnr-diff = 9.5% and passes the "E" extreme traffic grade. Additionally, its cost is 4.67% lower than that of the PRM high modulus modified asphalt, presenting considerable economic benefits.

Assessment of surface irrigation potential and crop water demand in Daramalo Wereda, southern Ethiopia

AbstractAssessing available water and land resources as well as their potential for surface irrigation use is vital for sustainable agricultural development and planning. Agricultural irrigation also plays a crucial role in ensuring food security and reducing poverty in Ethiopia. However, it is dominated by rain‐fed agriculture, with rainfall distribution and intensity vary spatially and temporally. Enhancing agricultural water management and irrigation has the potential to increase agricultural productivity. The objective of the study was to evaluate surface water potential and the irrigation water demand of Zage River sub‐watershed, which were estimated using hydrological model of Soil and Water Assessment Tool (SWAT) and CROPWAT8.0 software, respectively. Slope, soil type, drainage densities, land use/cover, and river proximity were the factors utilized to determine irrigation land suitability. A weighted overlay was completed, with 17.32% of irrigable lands found to be highly suitable, 41.29% moderately suitable, 37.61% marginally suitable, and 3.78% not suitable. The SWAT model result gave very good model performance indicator values of NE = 0.773 and R2 = 0.872 for calibration and NE = 0.771 & R2 = 0.945 for validation. The SWAT model result showed a total of 33.248 million m3 of surface runoff generated annually. Compared with irrigation water demand of 21.068 million m3, this suggests the watershed has high surface water potential for surface irrigation for selected crop types of the watershed. The findings of this research are relevant to improving local water management policies and practices and enable stakeholders to make decisions that enhance agricultural productivity and sustainable agricultural practices and help ensure the food security of local farmers.

Vegetation Dynamics Studies Based on Ellenberg and Landolt Indicator Values: A Review

Understanding the dynamics and system of interrelationships between habitats and plant communities is key to making reliable predictions about sustainable land use, biodiversity conservation and the risks of environmental crises. At the same time, assessing the complex of environmental factors that determine the composition, structure and dynamics of plant communities is usually a long, time-consuming and expensive process. In this respect, the assessment of habitats on the basis of the indicator properties of the plants is of great interest. The aim of our study was to carry out a comprehensive review of vegetation dynamics studies based on the Ellenberg and Landolt indicator values in the last five years (2019–2023). We identified their strengths and priority areas for further research, which will contribute to improving the ecological indicator values for studying vegetation dynamics. The analysis of publications was carried out based on the recommendations of PRISMA 2020 and the VOSviewer software(version 1.6.18). The wide geographical range and high reliability of Landolt and Ellenberg indicator values for the study of different plant communities and variations in their dynamics are demonstrated. At the same time, the application of these environmental indicator values has its peculiarities. For example, the Ellenberg indicator values show a wider research geography and are more often used to study the dynamics of forest ecosystems than the Landolt indicator values, which are more often used to study disturbed landscapes and the dynamics of individual species. However, these methods have been used with almost the same frequency for grasslands, wetlands and coastal vegetation. The citation analysis confirmed the high interest in the environmental indicator values and their widespread use in research, but also revealed the weak development of a network of relationships. This suggests that modern researchers are not well aware of, and rarely use, the results of research carried out in recent years, especially if they are based on indicator values other than those used by them. At the same time, a number of unresolved issues are clearly identified, which require additional research and a consolidation of research teams if they are to be addressed more successfully. We hope that the results of this meta-analysis will provide the impetus for further development of the concept of environmental indicators and help researchers to overcome the current questions around applying indicator values in the study of vegetation dynamics, as well as help researchers to understand the strengths of this methodology.

“Iron chlorosis paradox” in calcicoles and calcifuges from European dry grasslands: A meta-analysis

Iron (Fe) deficiency-related chlorosis (lime chlorosis) and the “paradox of iron chlorosis” in calcicole and calcifuge plants are unresolved problems. We performed a meta-analysis of our previous studies to determine whether calcicoles are more resistant to lime chlorosis than calcifuges are, whether lime chlorosis is Fe chlorosis per se and what is the source of the “paradox of iron chlorosis” in grassland plants. We found that both calcicoles and calcifuges are susceptible to chlorosis when grown on alkaline soil. In general, lime chlorosis does not result from Fe deficiency but is likely associated with manganese (Mn). Additionally, our analyses revealed that Ecological Indicator Values for Europe for soil reaction (R EIVEs) are not random to experimentally determined calcicole/calcifuge behavior but are not straightforward. Ultimately, neither the experimentally determined calcicole index nor the R EIVEs explained the microelemental nutrition of grassland plants in general (except for Zn acquisition), which highlights the need for species ecology-oriented studies to understand these phytocenoses.

Reclaiming Calcicoles: New Insights into Lime Lovers

Calcicoles are never new to the evolutionary life forms in the ecological world. The ramifications of environmental extremes always facilitate the emergence of the functional and structural integrity of plants and calcicoles, which have been exuding through this. The word “calcicole” finds its roots in the writings of Nathaniel Colgan, “The Orchids of Country Dublin,” published in August 1895 in “The Irish Naturalist.” Calcicoles are likely to flourish under calcium-rich soil having a pH of more than five, which otherwise hinders the growth of plant species, causing detrimental effects on their physiology. They are often regarded as lime lovers or acidofuges and are classified based on Ca2+ stress resistance, soluble and insoluble Ca2+ and Mg2+, pH conditions of soil, occurrence, and habitat. There are various variables used to evaluate the calcicoles described in this review, such as the Index of calcifugy, Ellenberg’s indicator values, and Landolt indicator values to predict the influence of environmental factors in determining flora along with changes in vegetation in a particular area considering the ecophysiological or morphological features. Calcicoles have specific in-built mechanisms to cope with stress conditions by producing phytosiderophores (PS) and by involving ecto and ericoid mycorrhizal associations for the absorption of iron and phosphorus, and high control over cytosolic Ca2+ concentrations. Calcicoles are markedly distributed in various plant families like Asteraceae, Brassicaceae, Amaranthaceae, Caryophyllaceae, Ericaceae, Primulaceae, Fabaceae, Gentianaceae, Rubiaceae, Plantaginaceae, Poaceae, Saxifragaceae, etc. The current review focuses on the ecological perspectives, special adaptive features, and phytopharmacological aspects of calcicoles.

Tidal levels significantly change bacterial community composition in a tropical estuary during the dry season

AbstractEstuaries are usually characterized by strong spatial and temporal variability in water physicochemical conditions and are often largely affected by human activities. One important source of variability is caused by tides that can swiftly alter not only physicochemical conditions but also the abundance and composition of the biota. The effect of the diurnal tidal cycle on microbial community composition during different seasons remains uncertain, although this knowledge underlies having effective monitoring programs for water quality and potential identification of health risk conditions. In this study, we assessed the bacterioplankton community composition and diversity across four tidal water levels in a tropical estuary characterized by a mixed semidiurnal tide regime (i.e., two high and two low tides of varying amplitudes) during both dry and wet seasons. The bacterial community composition varied significantly among the four tidal levels, but only during the dry season, when the influence of the seawater intrusion was largest. Bacterial indicators’ taxa identified using the Indicator Value Index were found within Cyanobacteria, Actinobacteriota, Bacteroidota, and Proteobacteria. The indicator taxon Cyanobium sp. had a prominent presence across multiple tidal levels. The main predicted phenotypes of the bacterial communities were associated with potential pathogenicity, gram-negative, and biofilm formation traits. While there were no marked predicted phenotypic differences between seasons, pathogenic and gram-negative traits were more prevalent in the dry season, while biofilm formation traits dominated in the wet season. Overall, our findings underscore the intricate relationship between river hydrodynamics and bacterial composition variability and hint a significant human impact on the water quality of the Bangpakong River.

Quantifying perceived risk in driving: A Monte Carlo approach for obstacle avoidance

Objective This study aims to develop a model for quantifying perceived risk in obstacle avoidance, emphasizing how drivers’ perceived risk characteristics influence their driving decisions. The research addresses the lack of attention given to modeling risk from the perspective of drivers’ risk perceptions. Methods Monte Carlo methods are employed to account for the uncertainties and complexities of driving behavior, restoring the probabilistic nature of risk. The proposed method quantifies perceived risk by incorporating drivers’ fuzzy perceptions, enabling a quantitative evaluation during obstacle avoidance. A logit model is used to link perceived risk with driving decisions, identifying key factors influencing driver behavior in obstacle avoidance scenarios. Results Experimental data revealed significant variations in vehicle trajectories and speed distributions due to differences in drivers’ experience and proficiency. The perceived risk indicator (PRI) values for leftward bypasses were higher compared to rightward bypasses, and the receiver operating characteristic (ROC) curve confirmed the PRI’s strong predictive ability with an area under the curve (AUC) of 0.820. The logit model showed that both PRI and speed significantly influenced the probability of choosing a rightward bypass, achieving 90% accuracy. Building on the model, the study predicted and visualized the probability of vehicles turning right to avoid obstacles at different positions and speeds within 200 m of the obstacle. Conclusions The research offers a framework for traffic professionals to understand driver-perceived risk and decision-making mechanisms. This understanding is beneficial for improving traffic safety and highlights the importance of considering drivers’ risk perceptions in modeling driving behavior.

Thermal regime of peatlands in Western Siberia near the southern border of the permafrost

Relevance. The permafrost degradation under the effect of global warming. It determines the necessity for a predictive assessment of permafrost stability to minimize disturbances to engineering installations in the permafrost zone. Aim. To assess the stability of frozen peatlands in the southern part of the zone of insular distribution of permafrost. Objects. Soils of flat-mound and high-mound palsa mires, which preserve permafrost on the southern border of the insular permafrost zone. Methods. Measurements of the temperature of peat and mineral soil in geocryological boreholes from 0 to 10 m deep using the SAM-N automatic monitoring surveillance network; determination of surface temperature from thermal channels of MODIS satellite images from 2000 to 2022; analysis of meteorological indices and determination of air temperature trends for predictive assessment of permafrost stability; calculation of indicator values of permafrost state, such as freezing degree-days and thawing degree-days, frost index, freezing and thawing N-factors. Results. Numerous features of unstable permafrost have been observed. In particular, the mean annual temperature of the surface layer was positive in all studied boreholes (+0.8...+1.3°C), and the temperature at the depth of zero amplitudes (10 m) is close to the melting point (with the predominance of temperatures in the range of –0.2...–0.3°C). Besides, a layer of soil that does not freeze throughout the year (non-merging permafrost) was identified. The thawing degree-days and frost number values correspond to areas with unfrozen soils. Positive trends in air temperature, Earth's surface temperature, and snow depth were observed. For 2000–2022, surface air temperature increased by 0.76°C/10 years on average. The land surface temperature increased in summer by an average of 0.42°C/10 years. If the positive trend in surface air temperatures continues, frozen peatlands in the southern part of the permafrost zone will completely melt in 50–70 years.

Modeling market value of land plots using GIS

This work examines the regulatory framework for expert monetary valuation of land plots. Scientific research on the development and improvement of economic-statistical methods for mass monetary valuation of land plots is analyzed. The peculiarities and advantages of using GIS in the valuation procedure are considered. A structure of the valuation database is developed for the effective selection of comparable plots during valuation by comparing sales prices and market analysis. The valuation database is formed based on data on land plot sales. Price formation factors are analyzed in order to construct an economic-statistical model of market value for land plots in Rivne. Scales of indicator values are proposed for formalizing the assessment of price formation factors. Functions of the ArcGIS are used to establish indicator values. The market value of land plots is modeled using multiple regression analysis. Additionally, a surface of land plot values is constructed, which serves to determine the approximate market value. The model has been verified using GIS tools. An accuracy assessment of the developed model has been carried out.

Brown and red shades in the riverbed of the Nera River (Serbia) – update on the distribution and ecology of the association Hildenbrandio rivularis–Heribaudielletum fluviatilis Fritsch 1929 corr. Täuscher 2020 in Southeastern Europe

Heribaudiella fluviatilis (Areschoug) Svedelius is one of the rare representatives of freshwater brown algae, and its range is restricted to the Northern Hemisphere. Hildenbrandia rivularis (Liebmann) J. Agardh is still one of the endangered red algae species in Europe, although its indicator value and distribution have recently been questioned. The association Hildenbrandio rivularis– Heribaudielletum fluviatilis Fritsch 1929 corr. Täuscher 2020 occurs mainly in Northern and Central Europe, while its occurrence and ecology in Southern Europe are poorly researched. The lower reaches of the Nera River near the small town of Bela Crkva, Serbia, were searched for macroalgae in August 2021 and June 2022, when stones with macroalgal crusts were collected. Environmental parameters were measured in situ and water samples were collected for further analysis. A sample of the epilithic diatom community was collected to calculate diatom indices. We present the occurrence of the association Hildenbrandio rivularis–Heribaudielletum fluviatilis in the lower course of the Nera River in Serbia, relating the ecology of the species and habitat to previous findings from the Southeast European region. We discuss potential indicator values of macroalgae associations, rather than of a single species.

UKRAINE AND REPUBLIC OF MOLDOVA IN COOPERATION WITH THE EU AFTER 2014 YEAR: MODELS AND IMPACTS

Abstract. The paper is devoted to solving the problem of co-integration between Ukraine and the Republic of Moldova in the context of foreign trade. The study of co-integration makes it possible to determine common trends in the development of foreign trade and, based on the analysis of the dynamics of the development of one country, to forecast the development of foreign trade in another country. The study of the main indicators of foreign trade was carried out: volumes of exports, imports, trade balance. The share of export-import operations with the EU in the total volume of foreign trade of Ukraine and Moldova was chosen as the studied indicator. The article proposes to consider cointegrations both between long-term trends, which characterize the trend of foreign trade development, and between short-term trends, which reflect the cyclical component. A co-integration research mechanism has been developed, which includes three blocks: a block of analysis of literary sources, a block of mathematical tools, and a block of applied use. The use of decomposition models, trend models, spectral analysis, orthogonality indicators and pairwise correlations is proposed as a mathematical toolkit. Using the Foster-Stewart method, an analysis of the presence of a trend in the variance and average was carried out. The above calculations showed the presence of a trend and cyclical component, which allowed the use of additive decomposition models. For the study of long-term trends, a linear trend model was chosen for both Moldova and Ukraine. A spectral analysis of the cyclic component was carried out, which made it possible to identify five main harmonics with a unique frequency and amplitude. The combination of these harmonics caused 95.8% and 90.4% of the cyclical component for Moldova and Ukraine, respectively. An analysis of cointegration between short-term and long-term trend functions was conducted, which revealed medium cointegration in the long-term trend and high cointegration in the short-term trend. The cointegration analysis of the indicator values proved a high degree of cointegration for both long-term and short-term trends.

Impact of run-of-river damming on increasing phytoplankton biomass and species shift in a large Amazonian river

Run-of-river (ROR) dams, often perceived as having minimal environmental impact, can induce significant hydrodynamic changes that alter aquatic ecosystems. We investigated the impacts of an ROR dam on the Madeira River, the largest Amazon tributary, focusing on phytoplankton communities, their ecological implications, and related environmental factors. Our study examined changes in biomass and environmental factors (using General Linear Mixed Models - GLMM), species composition (using PERMANOVA) before and after damming, in both the main channel and tributaries (N = 549 samples). We also identified indicator species associated with different damming phases and regions through an indicator value analysis. The results showed that, following dam construction, the phytoplankton community changed in both the main channel and tributaries, with a shift from lotic diatoms to lentic phytoflagellates. This transition was likely facilitated by altered hydrodynamics and possibly influenced by the decomposition of flooded vegetation in the dam's influence zone. The decomposition of this vegetation could explain both the observed increase in oxygen consumption and the subsequent rise in phytoflagellate biomass after damming. However, despite the overall increase in phytoplankton biomass, the values remained within oligotrophic to mesotrophic conditions, consistent with the low nutrient concentrations recorded. However, we caution that the dam-created hydrodynamic conditions are optimal for phytoplankton growth, potentially exacerbating nutrient-related issues in the future. We recommend proactive management strategies to prevent nutrient enrichment from activities such as agriculture and livestock in isolated Amazon areas affected by dams, thereby mitigating potential degradation of water quality linked to increased phytoplankton biomass.

Early impact of domestication on aggressiveness, activity, and stress behaviors in zebrafish (Danio rerio) using mirror test and automated videotracking

Fish domestication progresses through five levels: from the initial acclimatization to captivity (Level 1), to the life cycle completion in captivity (Level 4), and even to the implementation of selective breeding programs (Level 5). Domestication leads to phenotypic changes over generations, sometimes from the very first generation. Behavioral traits are among the first to change. However, in fish, potential behavioral changes during early domestication have been little studied. Therefore, we studied potential behavioral changes among early and advanced levels of domestication in a model species, the zebrafish (Danio rerio), using a mirror test experiment, commonly used to assess traits involved in activity, aggressiveness, and stress in this species. We compared these traits between wild zebrafish in captivity (F0; Level 1), the first generation of their captive-born offspring (F1; Level 4), and three laboratory strains (AB, TU, and WIK; Level 5). Each fish was individually filmed and tracked using an automated procedure for 5 min. Nine behavioral traits and one activity-related trait were characterized for each individual based on the movements and positioning of the fish. We applied a principal component analysis (PCA) and tested the significance of potential differences between groups using an analysis of similarities (ANOSIM). We applied an indicator value analysis (IndVal) to determine which traits were most expressed by each group. We detected differences between groups and across domestication levels. More specifically, we highlighted differentiations between different levels of domestication (e.g. between F1, AB, TU, and WIK) as early as the beginning of the domestication process (i.e. F0 vs. F1), but also within the same level of domestication (i.e. AB vs. TU). Based on PCA and IndVal, (i) F0 and F1 tended to show stronger expression of stress-related traits than the other groups, (ii) F0 was more active than others, and (iii) TU was more aggressive than AB. Our results confirmed that domestication can change fish behavior, even in the first generation born in captivity, although these modifications remain limited. In contrast, we did not observe any general trends correlated with domestication levels, given that AB and TU diverged in their aggressiveness levels, and WIK differed only from F1. This result needs to be generalized to other species but also considered for domestication for aquaculture. If future studies confirm that the changes observed at the beginning of the domestication process remain limited and that there is no consistent evolutionary trend across generations in fish, this would highlight the crucial importance of selecting the right species from the outset of domestication. It would also emphasize the need to design selective breeding programs that shape fish stocks with the most desirable characteristics. To our knowledge, this study is one of the few to examine the behavior of wild zebrafish alongside laboratory strains, offering a unique insight into the early stages of domestication.