Changing Environmental Conditions Research Articles

Climatic variation and risk assessment in a highly seasonal mammal

Abstract Climate change and its resulting effects on seasonality are known to alter a variety of animal behaviors including those related to foraging, phenology, and migration. While many studies focus on the impacts of phenological changes on physiology or fitness enhancing behaviors, fewer have investigated the relationship between variation in weather and phenology on risk assessment. Fleeing from predators is an economic decision that incurs costs and benefits. As environmental conditions change, animals may face additional stressors that affect their decision to flee and influence their ability to effectively assess risk. Flight initiation distance (FID)–the distance at which animals move away from threats–is often used to study risk assessment. FID varies due to both internal and external biotic and physical factors as well as anthropogenic activities. We asked whether variation in weather and phenology is associated with risk-taking in a population of yellow-bellied marmots (Marmota flaviventer). As the air temperature increased marmots tolerated closer approaches, suggesting that they either perceived less risk or that their response to a threat was thermally compromised. The effect of temperature was relatively small and was largely dependent upon having a larger range in the full data set that permitted us to detect it. We found no effects of either the date that snow disappeared or July precipitation on marmot FID. As global temperatures continue to rise, rainfall varies more and drought becomes more common, understanding climate-related changes in how animals assess risk should be used to inform population viability models.

PEDAGOGICAL CONDITIONS FOR THE FORMATION OF GEOGRAPHY TEACHERSGEOECOLOGICAL COMPETENCE IN THE EDUCATIONAL PROCESS

Today, the formation of competence of geography teachers is an actual task of higher education. To prepare a competitive personality capable of perceiving global problems, to functioning in new socio-economic, socio-cultural conditions, taking into account the modern concept of the joint existence of man and nature. Competence is the ability and knowledge in the field of interaction between geosystems and ecosystems, the influence of human activity on the surrounding nature, as well as the ability to adapt to changing environmental conditions and effectively respond to environmental threats and challenges.The article has an analysis of theoretical and methodological literature, the following concepts are specified and given to the following concepts: “competence”, “competency-based approach”. The pedagogical conditions for the effective formation of the competence of geography teachers in the educational process have been identified and substantiated, and the pedagogical technology for the formation of geography teachers’ competence in the educational process of the university (through the disciplines of the professional cycle, educational and scientific research activity) has been identified.

Impact of mangrove defoliation by Hyblaea puera on diversity of associated crustaceans in the Dharamtar Estuary, Maharashtra, India

Mangrove defoliation, caused by teak defoliator moth (Hyblaea puera), has been reported in India and other countries. However, research on its impact on the associated fauna remains limited. We observed extensive mangrove defoliation from August to October 2019 in the Dharamtar Estuary, Maharashtra, India. Consequently, a study was conducted to assess the impact of this defoliation on the diversity of crustaceans within the mangroves and the surrounding estuarine waters. A total of 27 crustacean species were recorded in the mangrove region exhibiting reduced species richness and abundance during the mangrove defoliation period. Whereas, a total of 32 species of crustaceans were recorded from the estuarine region, where both species richness and abundance were higher during the defoliation period. These findings indicate that the crustaceans on the mangrove floor and in the estuarine waters responded differently to the changing environmental conditions caused by defoliation. Keywords: Crustaceans, Diversity, Estuary, Mangrove defoliation, Moth infestation

Water resources in Pakistan: a comprehensive overview and management challenges

ABSTRACT Pakistan has a range of water resources, including many rivers, large glaciers in the Himalayas, and significant underground water reserves, located throughout the country. However, the country faces considerable challenges in effectively managing these water resources. Employing a comprehensive review methodology, this paper examines policy documents and recent scholarly articles to analyze the current obstacles and propose viable solutions for sustainable water management in Pakistan. Significant challenges, including delayed policy implementation, insufficient regulatory enforcement, and inadequate data collection, hinder water resource management. Furthermore, there is a critical gap in integrating climate adaptation measures into water management strategies, which affects the resilience and efficiency of water resource allocation and utilization amid changing environmental conditions. It recommends significant policy changes that include economic measures such as water pricing, advancements in water recycling technologies, and approaches to improve climate resilience. Furthermore, this study proposes a comprehensive framework designed to tackle the complex challenges of water management. It suggests an integrated approach that combines policy, technology, environmental, and economic strategies to promote sustainable and resilient water use.

Identification of plankton habitats in the North Sea.

The definition of an ecological niche makes it possible to anticipate the responses of a species to changing environmental conditions. Broad tolerance limits and a paucity of readily observable niches in the pelagic zone make it difficult to anticipate responses of the plankton community related to anthropogenic or environmental changes. Plankton distributions are closely linked to climate change and shape the seascape for higher trophic levels, so monitoring plankton distributions and defining ecological niches will help to understand and predict ecosystem responses. Here we apply a machine learning autoencoder and a density-based clustering algorithm to high-frequency datasets sampled with a ROTV Triaxus in the North Sea. The results indicate that in this highly dynamic environment, local hydrography prevents niche-based separation of plankton species at the sub-mesoscale, despite the availability of different habitats. Plankton patches were associated with naturally occurring frontal systems and anthropogenically induced upwelling-downwelling dipoles in the vicinity of offshore wind farms (OWFs).

Analysis of land use changes and soil erosion using the EPM-IntErO model in the Sokobanja Basin, Serbia

Soil erosion, with the progressive loss of fertile topsoil and its negative impact on agricultural productivity, has become a critical global environmental problem. In the second half of the 20th century, many municipalities in Serbia experienced significant changes in land use, vegetation, and environmental conditions. The drive towards industrialization and urbanization aimed to improve the living standards of the population, but as a consequence, it led to substantial depopulation of rural areas and the adoption of inadequate agricultural practices, which, in turn, further intensified soil erosion. This study focuses on the Sokobanjska Moravica River basin (Eastern Serbia), extending to the Bovan Lake Dam and upstream, with a total area of 540.4 km². The basin is situated in a characteristic karst landscape. Changes in erosion intensity and runoff from this basin are analyzed using the Intensity of Erosion and Outflow (IntErO) model, which algorithmically integrates the widely used Erosion Potential Method (EPM) with innovative computational techniques to predict sediment production and runoff from the river basin accurately. This analysis utilizes GIS software and official statistical yearbook data, focusing on the period from the second half of the 20th century, including the analysis of the current state. According to our research, the most intensive changes in land use occurred between 1961 and 1971, marking the beginning of the period of a decline in rural population and, consequently, a decrease in erosion intensity. Key findings indicate that predominant changes in land use and vegetation led to a shift from crop farming to animal husbandry. After 1971, ongoing depopulation, particularly in rural areas, resulted in a gradual and steady decrease in erosion intensity. The primary aim of this study is to support policymakers in developing more effective soil and water conservation regulations. By making recommendations for the protection of vegetation, and thus the soil within this river basin, this research helps ensure their long-term preservation. Future research should focus on the long-term impacts of current land use practices and develop strategies to mitigate erosion in the context of changing climate conditions.

An integrated simulation-optimization modeling approach for coupled risk management of blue water and green water under changing environmental conditions

Due to the impact of global climate change and land use changes, the spatiotemporal distribution and water cycle processes of watershed water resources are affected. In order to sustainably manage watershed water resources, it is necessary to accurately assess the available water volume to meet the coordinated management of the watershed's socio-economic subsystem and eco-environment subsystem. The amount of Bluewater resources (BW) is closely related to the amount of Greenwater resources (GW). BW is directly related to human consumption in the socio-economic subsystem, while GW is used to maintain the health of the ecosystem. A method called the integrated simulation-optimization modeling system (ISOMS) was developed to evaluate adaptive strategies for dealing with the combined effects of climate change and land-use changes. ISOMS not only predicts future hydrological trends under varying environmental conditions but also generates comprehensive risk management plans that incorporate different types of uncertainties, including random and fuzzy factors. The Copula function is introduced to handle the interaction between available BW and available GW. The results showed that: (i) uncertainties in the hydrologic system could result in alterations to the distribution of water resources; (ii) system benefits are, to some extent, affected by land use change and climate change; (iii) the shortage of BW is affected by the level of risk, and the joint risk increases, resulting in an increase in water scarcity; (iv) the planned annual agricultural water consumption is the highest, followed by domestic water consumption, and industrial water consumption is the lowest. Through the results of the model operation, the joint risk assessment and adaptive management of BW and GW in the East River Basin (ERB) under changing environments, as well as the BW allocation plan, are obtained to provide support for scientific and reasonable resource collaborative decision-making and promote the synchronized advancement of the socio-economic subsystem and eco-environment subsystem in the ERB.

Aerotolerancy of Campylobacter spp.: A Comprehensive Review.

Campylobacter spp. constitute a group of microaerophilic bacteria that includes strains that are aerotolerant and capable of surviving in aerobic conditions. Recent studies have shown that aerotolerant strains are highly prevalent in meats, animals, and clinical settings. Changes in growth media and other environmental conditions can affect the aerotolerance of Campylobacter strains and must be considered when studying their aerotolerance in vitro. Polymicrobial interactions and biofilms also play a significant role in the ability of Campylobacter to survive oxygen exposure. Continuous subculturing may foster aerotolerance, and studies have demonstrated a positive correlation between aerotolerance and virulence and between aerotolerance and the ability to survive stressful environmental conditions. Various mechanisms and genetic origins for aerotolerance have been proposed; however, most of the potential genes involved in aerotolerance require further investigation, and many candidate genes remain unidentified. Research is also needed to investigate if there are any clinical implications for Campylobacter aerotolerance. Understanding the aerotolerance of Campylobacter remains an important target for further research, and it will be an important step towards identifying potential targets for intervention against this clinically important food-borne pathogen.

The method of forming ensembles of complex signals based on multi-scale decomposition of time intervals at different levels of detail

This article addresses the challenges of forming signal ensembles in dynamic cognitive radio environments, focusing on the limitations of traditional methods. The study proposes a new approach based on multiscale time interval decomposition, which allows for the creation of signal ensembles at varying levels of temporal detail. The key innovation of this method is its ability to improve signal reproduction accuracy, reduce inter-symbol and inter-channel interference, and enhance the overall efficiency of data processing. The method's adaptability to changing environmental conditions is also a core advantage, enabling better use of bandwidth and reduced transmission delay. Through the decomposition of time intervals into coarse, intermediate, and fine levels, this method allows for the detailed analysis of short-term, medium-term, and long-term signal components. Experimental results demonstrate the superiority of this approach in terms of signal recovery accuracy, noise resilience, and processing speed. These findings highlight the potential for optimizing signal processing in cognitive radio networks, particularly in environments with high levels of noise and interference. Future research aims to integrate machine learning algorithms to further enhance adaptability in real-time scenarios.

Movements of the bearded seal in the White Sea monitored by satellite telemetry

Movements and distribution data of the bearded seal (Erignathus barbatus) in the White Sea during summer and autumn were obtained as a result of tagging with satellite telemetry transmitters (STT). Russian-made Pulsar STTs operated in the Argos system. Catching and tagging of bearded seals was carried out in the Onega and Mezen bays in 2014, 2015 and 2017. Altogether, 7 STTs were installed on seals of different ages and sexes. Analysis of satellite telemetry data showed that during the non-ice period bearded seals were tied to local habitat areas, and the dynamics of their movements differed in the inner and open parts of the sea. The STT data suggest that these differences in distribution are due to lability in feeding and show good adaptation of the bearded seal in the conditions of poorly accessible feed base of the White Sea. The diverse feeding strategy of the bearded seal in the White Sea, and its adaptation to the difficult feeding conditions of the sea, may help the species to survive in the region and ensure stable population numbers in changing environmental conditions.

Hybrid intelligent algorithm aided energy consumption optimization in smart grid systems with edge computing

The rapid proliferation of smart grid systems necessitates efficient management of energy resources, particularly in the context of mobile edge computing (MEC) networks. This paper presents a novel approach to optimize the energy consumption in smart grid systems with the integration of edge computing, employing a hybrid intelligent algorithm (HIA) empowered by particle swarm optimization (PSO). The primary objective is to enhance the sustainability and operational efficiency of smart grid infrastructures by minimizing the energy consumption in the MEC networks. The proposed HIA utilizes PSO to dynamically allocate computational tasks and manage resources among edge devices based on real-time demand fluctuations. This adaptive approach aims to achieve the optimal load balancing and energy efficiency across the smart grid ecosystem. By leveraging the PSO’s ability to iteratively refine solutions and adapt to changing environmental conditions, the algorithm optimizes the energy consumption while maintaining requisite service levels and reliability. Simulation experiments and case studies validate the effectiveness of the proposed PSO-based HIA in reducing the energy consumption without compromising system other performances. The results demonstrate substantial improvements in the energy efficiency, illustrating the feasibility and benefits of employing intelligent algorithms tailored for edge computing environments within smart grid systems. This research contributes to advancing sustainable smart grid technologies by introducing a robust framework for energy optimization through hybrid intelligent algorithms.

The role of technology in modern industrial processes: a comparative analysis of automated, automatic and mechanical systems

In the modern technological sphere, systems are categorized into various types based on their level of complexity and functional capabilities. The primary types are mechanical, automatic, and automated systems. Each of these types has its unique characteristics and areas of application. Mechanical systems are the simplest of all. They consist primarily of physical components such as gears, levers, and springs, which interact to perform specific tasks. These systems typically lack built-in control or regulation mechanisms, and their operation is based on basic mechanical principles. Examples of mechanical systems include simple clock mechanisms or traditional measuring devices. Automatic systems represent an evolutionary step beyond mechanical systems, as they include elements for automatic control. These may be electrical or electronic components that enable the system to perform certain operations without direct human intervention. For example, automatic doors or thermostats that regulate room temperature are examples of such systems. They can respond to changing conditions and perform tasks based on predefined parameters. Automated systems, in turn, are the most complex and integrated. They combine automatic control with software and advanced management systems, allowing them to adapt to changing environmental conditions and make decisions independently. Automated systems may include elements of artificial intelligence and machine learning, enabling them to perform complex tasks such as data processing or optimizing production processes. Examples include industrial robotic lines or management systems in distribution networks. Thus, the main differences between these systems lie in their level of complexity and functional capabilities: mechanical systems are based on simple physical principles, automatic systems contain elements of automatic control, and automated systems provide a high level of integration and autonomy.

Seasonal Variations of Ice-Covered Lake Ecosystems in the Context of Climate Warming: A Review

The period of freezing is an important phenological characteristic of lakes in the Northern Hemisphere, exhibiting higher sensitivity to regional climate changes and aiding in the detection of Earth’s response to climate change. This review systematically examines 1141 articles on seasonal frozen lakes from 1991 to 2021, aiming to understand the seasonal variations and control conditions of ice-covered lakes. For the former, we discussed the physical structure and growth characteristics of seasonal ice cover, changes in water environmental conditions and primary production, accumulation and transformation of CO2 beneath the ice, and the role of winter lakes as carbon sources or sinks. We also proposed a concept of structural stratification based on the differences in physical properties of ice and solute content. The latter provided an overview of the ice-covered period (−1.2 d decade−1), lake evaporation (+16% by the end of the 21st century), the response of planktonic organisms (earlier spring blooming: 2.17 d year−1) to global climate change, the impact of greenhouse gas emissions on ice-free events, and the influence of individual characteristics such as depth, latitude, and elevation on the seasonal frozen lakes. Finally, future research directions for seasonally ice-covered lakes are discussed. Considering the limited and less systematic research conducted so far, this study aims to use bibliometric methods to synthesize and describe the trends and main research points of seasonal ice-covered lakes so as to lay an important foundation for scholars in this field to better understand the existing research progress and explore future research directions.

Mechanical Profiling of Biopolymer Condensates through Acoustic Trapping.

Characterizing the mechanical properties of single colloids is a central problem in soft matter physics. It also plays a key role in cell biology through biopolymer condensates, which function as membraneless compartments. Such systems can also malfunction, leading to the onset of a number of diseases, including many neurodegenerative diseases; the functional and pathological condensates are commonly differentiated by their mechanical signature. Probing the mechanical properties of biopolymer condensates at the single particle level has, however, remained challenging. In this study, we demonstrate that acoustic trapping can be used to profile the mechanical properties of single condensates in a contactless manner. We find that acoustic fields exert the acoustic radiation force on condensates, leading to their migration to a trapping point where acoustic potential energy is minimized. Furthermore, our results show that the Brownian motion fluctuation of condensates in an acoustic potential well is an accurate probe for their bulk modulus. We demonstrate that this framework can detect the change in the bulk modulus of polyadenylic acid condensates in response to changes in environmental conditions. Our results show that acoustic trapping opens up a novel path to profile the mechanical properties of soft colloids at the single particle level in a non-invasive manner with applications in biology, materials science, and beyond.

Identification of the Novel Small Compound Stress Response Regulators 1 and 2 That Affect Plant Abiotic Stress Signaling.

Abiotic stresses, such as drought, salinity, and extreme temperatures, limit plant growth and development, reducing crop yields. Therefore, a more comprehensive understanding of the signaling mechanisms and responses of plants to changing environmental conditions is crucial for improving sustainable agricultural productivity. Chemical screening was conducted to find novel small compounds that act as regulators of the abiotic stress signaling pathway using the ABA-inducible transgenic reporter line. Small molecules called stress response regulators (SRRs) were isolated by screening a synthetic library composed of 14,400 small compounds, affecting phenotypes such as seed germination, root growth, and gene expression in response to multiple abiotic stresses. Seeds pretreated with SRR compounds positively affected the germination rate and radicle emergence of Arabidopsis and tomato plants under abiotic stress conditions. The SRR-priming treatment enhanced the transcriptional responses of abiotic stress-responsive genes in response to subsequent salt stress. The isolation of the novel molecules SRR1 and SRR2 will provide a tool to elucidate the complex molecular networks underlying the plant stress-tolerant responses.

Smart surveillance: deploying drones for efficient and adaptive monitoring solutions

The growing need for real-time and adaptable surveillance solutions has prompted the investigation of cutting-edge technologies within security and monitoring frameworks. This paper introduces an innovative surveillance approach that utilizes drones to improve situational awareness and operational efficiency across various domains, including public safety, border security, and environmental monitoring. The proposed system integrates autonomous drones equipped with sophisticated imaging capabilities, data processing techniques, and machine learning algorithms, facilitating real-time monitoring, threat identification, and comprehensive data analysis. Notable features of this system include autonomous path planning, the ability to adapt to changing environmental conditions, and effective communication with ground control stations. By merging drone technology with AI-enhanced analytics, this approach provides a scalable and cost-efficient surveillance solution that minimizes the need for human intervention while enhancing accuracy and response times. In this paper, we detail the design, implementation, and performance assessment of our system, underscoring its potential to transform conventional surveillance practices.

Body-size reductions in dacryoconarid tentaculitoids during Late Devonian warming

Body size is an essential factor in an organism’s survival, and when paired with paleoenvironmental proxies, size trends can provide insights into a lineage’s evolutionary responses to changing environmental conditions. This study explores the diversity and body-volume trends of dacryoconarid tentaculitoids, globally abundant marine zooplankton, in the Devonian of the Appalachian Basin (eastern United States), spanning the late Givetian through the middle Frasnian punctata carbon isotope excursion. Using statistical approaches to model trends, we find evidence of a gradual, within-lineage reduction in styliolinid adult body sizes starting at the Givetian-Frasnian boundary. This reduction is followed by a significant decrease in both adult and initial chamber volumes during the punctata excursion. At the Givetian-Frasnian boundary, annulated forms (nowakiids) become rare and smooth forms (styliolinids) begin to dominate the assemblage. Using pre-existing geological and geochemical data sets, we consider environmental factors, including sea level, anoxia, nutrient availability, and temperature, as potential drivers of body-size reductions. Bottom-water anoxia most likely did not influence body-size trends of this pelagic group, but frequent water-column overturning in the Frasnian or other exchange between deep and shallow water may have affected taxonomic composition, favoring styliolinids. Sea-surface temperature correlates inversely with body size, suggesting that warming beginning in the early Frasnian may have contributed to gradual, long-term size reductions. Rising temperatures through the middle Frasnian may have led to the disappearance of dacryoconarids in the northern Appalachian Basin after the excursion.

Inspection of the accuracy of Fringe Projection Profilometry by using Hybrid Methods

Fringe Projection Profilometry- FPP system is widely used for three-dimensional(3D) imaging. This system is promising. However, for the changing environmental conditions, the measurement object, system noise, and strong backlighting changing, it is difficult to obtain 3D image accurately by fringe analyzing methods such as Traditional Fourier Transform Method-TFFT in FPP System. Therefore, in this paper, the TFFT method is combined with various method and hybrid methods are formed. The aim is to investigate how these methods affect the accuracy of FPP system. To make this determination, from simulated fringe pattern, phase is calculated. Then the error values are obtained using these phase values. Consequently, it is seen from error results that TFFT with two Dimensional Empirical Mode Decomposition method-2D-EMD-FFT which gives the lowest error, is the most insensitive to the disruptive effects mentioned above. Moreover, it is the most stability and least affected by the geometric of the object under test.

Resource-based modelling approach to studying evolutionary rescue.

In this paper, we present an in-depth investigation into the dynamics of evolutionary rescue using a resource-based modelling approach. Utilizing classical consumer-resource models, we aim to understand how species can adapt to abrupt environmental changes that alter the availability of substitutable resources. Through both analytical solutions and simulation-based techniques, we explore the conditions under which populations can recover from critical sizes and avoid extinction. Our findings highlight the importance of minimum viable population sizes, mutation rates, and the adaptive capacity of metabolic strategies in influencing population resilience. We demonstrate that while increased mutation rates can facilitate faster recovery by enabling populations to evolve new metabolic strategies suited to the altered resource landscape, populations starting with smaller sizes or facing severe reductions in resource availability are more susceptible to extinction. This study offers valuable insights into the interplay between ecological dynamics and evolutionary mechanisms, providing a comprehensive framework for predicting population persistence and informing conservation strategies under changing environmental conditions.

Growth rate as a link between microbial diversity and soil biogeochemistry.

Measuring the growth rate of a microorganism is a simple yet profound way to quantify its effect on the world. The absolute growth rate of a microbial population reflects rates of resource assimilation, biomass production and element transformation-some of the many ways in which organisms affect Earth's ecosystems and climate. Microbial fitness in the environment depends on the ability to reproduce quickly when conditions are favourable and adopt a survival physiology when conditions worsen, which cells coordinate by adjusting their relative growth rate. At the population level, relative growth rate is a sensitive metric of fitness, linking survival and reproduction to the ecology and evolution of populations. Techniques combining omics and stable isotope probing enable sensitive measurements of the growth rates of microbial assemblages and individual taxa in soil. Microbial ecologists can explore how the growth rates of taxa with known traits and evolutionary histories respond to changes in resource availability, environmental conditions and interactions with other organisms. We anticipate that quantitative and scalable data on the growth rates of soil microorganisms, coupled with measurements of biogeochemical fluxes, will allow scientists to test and refine ecological theory and advance process-based models of carbon flux, nutrient uptake and ecosystem productivity. Measurements of in situ microbial growth rates provide insights into the ecology of populations and can be used to quantitatively link microbial diversity to soil biogeochemistry.