Changing Environmental Conditions Research Articles

Seasonal shifts in gut microbiota and cold tolerance metrics in a northern population of Reticulitermes flavipes (Blattodea: Rhinotermitidae).

Eastern subterranean termites, Reticulitermes flavipes (Kollar), are widely distributed across North America where they are exposed to a broad range of environmental conditions. However, mechanisms for overwintering are not well understood. Wisconsin is a unique location to study mechanisms of cold tolerance as it represents the northern boundary for persistent R. flavipes populations. In this study, we evaluated seasonal shifts in cold tolerance using critical thermal minimum (CTmin) and supercooling point (SCP) and examined how these measurements correlate to changes in the microbial community of the termite gut. Results showed seasonal acclimatization to cold, which is consistent with the use of behavioral freeze-avoidant mechanisms. However, these insects also demonstrated an increased susceptibility to freezing later in the season, which may be tied to changes in gut microbiota. Our results found shifts in the composition of the gut microbiome in R. flavipes between mid- to late summer and early to late fall. These differences may be suggestive of a change in metabolism to adjust to a period of reduced feeding and increased metabolic stress during overwintering. Specifically, results showed an increased abundance of Methanobrevibacter sp. (Euryarchaeota) associated with cold, which may be indicative of a metabolic shift from acetogenesis to methanogenesis associated with overwintering. Further work is needed focusing on specific contributions of certain gut microbes, particularly their role in metabolic adaptability and in providing protection from oxidative stress associated with changes in environmental conditions.

Fabry-perot interferometers with resin scaffolders for high sensitivity temperature sensing

This study explores the development of an innovative Fabry-Perot Interferometer (FPI) designed for temperature sensing and environmental monitoring. The device is constructed by embedding optical fibers within a 3D-printed resin scaffold, forming a structure with an open Fabry-Perot cavity. Intended as an integral component of Cyber-Physical-Social Systems (CPSS), this FPI structure aims to enhance the system’s capacity to sense changes in external environmental conditions. Within the CPSS context, the FPI offers several advantages, including simple manufacturing processes, low production costs, and high sensitivity. These benefits contribute to providing precise environmental feedback to the system, which is essential in implementing effective security and privacy protection strategies. Experimental evaluations have shown that the FPI exhibits a high linear sensitivity of 14.330 nm/°C within a temperature range of 34.9°C–38.5°C, confirming its potential for application in CPSS for temperature monitoring and environmental sensing.

Phenological response of European beech (Fagus sylvatica L.) to climate change in the Western Carpathian climatic-geographical zones.

The paper analyzes the results of 26 years (1996-2021) of phenological observations of the vegetative organs of European beech (Fagus sylvatica L.) in the Western Carpathians. It evaluates the influence of the heterogeneity of this territory, including relief and elevation, based on climatic-geographical types. Phenological stages, including leaf unfolding, full leaves, leaf coloring, and leaf fall, were monitored at 40 phenological stations across eight elevation zones. The study assesses trends in the occurrence of phenological stages, the length of the growing season, and phenological elevation gradients. The results indicate a statistically significant earlier onset of spring phenological phases and delay in autumn phases, resulting in an average extension of the beech growing season by 12 days. Our findings confirm that the lengthening of the growing season due to warming, as an expression of climate change, is predominantly attributed to the warming in the spring months. The detected delayed onset of autumn phenophases was not due to warming in the autumn months, but other environmental factors influence it. The trend of elongation of the growing season (p<0.01) is observed in all elevation zones, with a less significant trend observed only in zones around 400 and 600 m a.s.l, signaling changes in environmental conditions across most of the elevation spectrum. Moreover, the heterogeneity of climatic-geographical types within each elevation zone increases the variability in the duration of the growing season for sites with similar elevations. By extending the growing season, it is assumed that the beech area will be changed to locations with optimal environmental conditions, especially in terms of adverse climatic events (late spring frosts, drought) during the growing season. The phenological elevation gradients reveal an earlier onset of 2.2 days per 100 m for spring phenophases and a delay of 1.1-2.9 days per 100 m for autumn phenophases. These findings highlight the specific environmental conditions of European beech in the Western Carpathians and their potential for anticipating changes in its original area. Additionally, these observations can aid in forecasting the further development of phenological manifestations related to climate change.

Detecting Shoreline Changes on the Beaches of Hainan Island (China) for the Period 2013–2023 Using Multi-Source Data

This study presents an in-depth analysis of the dynamic beach landscapes of Hainan Island, which is located at the southernmost tip of China. Home to over a hundred natural and predominantly sandy beaches, Hainan Island confronts significant challenges posed by frequent marine natural disasters and human activities. Addressing the urgent need for long-term studies of beach dynamics, this research involved the use of CoastSat to extract and analyze shoreline data from 20 representative beaches and calculate the slopes of 119 sandy beaches around the island for the period from 2013 to 2023. The objective was to delineate the patterns of beach evolution that contribute to the prevention of sediment loss, the mitigation of coastal hazards, and the promotion of sustainable coastal zone management. By employing multi-source remote sensing imagery and the CoastSat tool, this investigation validated slope measurements across selected beaches, demonstrating consistency between the calculated and actual distances despite minor anomalies. The effective use of the finite element solution (FES) in the 2014 global tidal model for tidal corrections further aligned the coastlines with the mean shoreline, underscoring CoastSat’s utility in enabling precise coastal studies. The analysis revealed significant seasonal variations in shoreline positions, with approximately half of the monitored sites showing a seaward progression in summer and a retreat in winter, which were linked to variations in wave height. The southern beaches exhibited distinct seasonal variations, which contrasted with the general trend due to differing wave impacts. The western and southern shores showed erosion, while the northern and eastern shores displayed accretion. The calculated slopes across the island indicated that the southern beaches had steeper slopes, while the northern areas exhibited more pronounced slope variations due to wave and tidal impacts. These findings highlight the critical role of integrated coastal management and erosion control strategies in safeguarding Hainan Island’s beaches. By understanding the mechanisms driving seasonal and regional shoreline changes, effective measures can be developed to mitigate the impacts of erosion and enhance the resilience of coastal ecosystems amidst changing environmental conditions. This research provides a foundational basis for future efforts aimed at the sustainable development and utilization of coastal resources on Hainan Island.

New sporadic nesting sites of Loggerhead Turtles (Caretta caretta) on the western Antalya coast, Türkiye

Greece and Türkiye hold the most important nesting populations of marine turtles in the Mediterranean. In Turkey, the nesting population encompasses 21 beaches across the Aegean and Mediterranean regions, with 15 identified as crucial nesting sites for Loggerhead Turtles (Caretta caretta). However, sporadic nesting also occurs beyond these beaches. To evaluate the significance of these sporadic nests for the overall population, a comprehensive survey was conducted along a 200 km coastline in the western Antalya province over two years. This effort led to the identification of three sporadic nesting sites. A total of 112 adult female Loggerhead Turtle emergences were recorded on these beaches, resulting in 54 instances of egg-laying. Although sporadic nesting is estimated to contribute only 1-2% to Türkiye’s total nests annually, these nesting areas serve as crucial reservoirs of turtles, vital for adapting to changing environmental conditions. The discovery of these sporadic nesting sites is credited to enhanced monitoring and conservation endeavors in Türkiye.

Homogenization of rammed earth walls under changing environmental conditions

Construction with rammed earth walls is a technique used for the construction of structures that has been increasing and by its nature requires in-depth knowledge due to the exposure of its materials (soil) to environmental factors, such as precipitation and solar radiation. This causes its structural elements to experience humidity fluctuations that affect the soil that constitutes them, resulting in a structure built with a material with heterogeneous properties, a fact that makes it difficult to understand its behaviour. The use of simulations in numerical models has helped to understand the internal dynamics of these elements. However, these procedures can present challenges in model construction and can also be computationally expensive, depending on the complexity of the model. In this context, the present research focuses on examining the behaviour of rammed earth walls against seismic action, when despite being made up of a single material, its composition is considered heterogeneous due to the humidity variations inherent to its exposure. Next, these models were subjected to a homogenization process of its properties using the Hashin and Shtrikman homogenization bounding theory. The objective is to find equivalent properties that facilitate the analysis of structural behaviour, assuming the homogeneity of the material. This homogenization process was extended to all parameters defined within the Pressure Independent Multi-yield material model employed in OpenSees, encompassing shear modulus, bulk modulus and density. As a result, applying Hashin and Shtrikman's upper bound to homogenize rammed earth walls produces remarkably similar results to those obtained using simulations of heterogeneous walls. This research provides valuable insights to understand rammed earth wall homogenization techniques and their behaviour, with important implications for their design and analysis.

Trade‐Off Between Light Deprivation and Desiccation in Intertidal Seagrasses Due To Periodic Tidal Inundation and Exposure: Insights From a Data‐Calibrated Model

AbstractSome seagrass species thrive in shallow intertidal zones globally, adapting to periodic tidal inundation and exposure with distinctive physiological traits and offering crucial ecosystem services. However, predicting the responses of intertidal seagrasses to external stressors is hampered by the complexity of the dynamic and harsh environments they occupy. Intertidal seagrass growth models, especially those incorporating dynamic physiological responses, are scarce in the literature. Our study comprehensively collated relevant data from the literature to parameterize the relationship between air exposure, seagrass leaf water content and photosynthetic efficiency to inform new growth rate functions for generalizable intertidal seagrass growth models. We tested the applicability of these model formulations for scenarios with varying physiological process assumptions, seagrass species, tidal conditions, meadow elevations and water turbidity. We found that neglecting air‐exposed physiological responses (i.e., leaf water content loss and reduced photosynthetic efficiency) can substantially overestimate seagrass growth rates. We also observed a trade‐off between light deprivation and desiccation on intertidal seagrass growth under specific tidal ranges and turbidity conditions. This can yield an “optimal” elevation where overall stress of desiccation (increasing with meadow elevation) and light deprivation (decreasing with meadow elevation) are minimized. The predicted optimal elevation, that is, the most suitable habitat for intertidal seagrass, moves upward as water turbidity increases. Our study provides conceptual and quantitative guidance for ecological modelers to include air exposure responses of intertidal seagrasses in coastal ecosystem models. The model also helps to evaluate the viability of intertidal seagrass habitats and inform decisions on coastal ecosystem management under changing environmental conditions.

IJCM_278A: Forecasting of Dengue Cases and Deaths in India: An application of Auto Regressive Integrated Moving Average Model

Background: Dengue is a mosquito borne viral disease caused by Dengue virus (DENV). Nearly about half of global population is at risk now with an estimated 100-400 million infections occurring every year. South East Asia (SEA) countries are at more risk for having Dengue infections due to its temperate climate. In India also, the cases are rising every year due to change in environmental and climatic conditions. Objectives: 1. To assess the trend of Dengue in India, 2. To forecast Dengue cases and deaths in India Methodology: For this time series analysis study, data on Dengue were collected from National Health Profile 2005-2022 and NVBCDCP; and a secondary data analysis was done. Gretl software was used to develop the model and to forecast Dengue cases and deaths. Data were checked for stationarity and appropriate ARIMA (Auto Regressive Integrated Moving Average) model for the available data was developed. Using the developed model, the cases and deaths are forecasted for next 3 years (2023-2025). Results: The available data showed an increasing trend of Dengue cases and deaths in India. The three years forecasted data for Dengue cases &amp; deaths also shows an increasing trend. The predicted Dengue cases for 2025 are 278513 (95% CI; 208898-348128) and the Dengue deaths for 2025 are 308 (95% CI; 166-450). Conclusion: From the time series analysis of the data, it is clear that the public health burden of Dengue is on an increasing trend. Hence, it is recommended that the policy makers &amp; health workers need to focus more on planning &amp; implementing effective preventive interventions to reduce the public health burden of Dengue cases &amp; deaths.

Assessing the economic value of Posidonia oceanica (L.) at Tremiti Islands (Mediterranean Sea): An ecosystem condition-based approach

In the context of limiting global warming, the seagrass Posidonia oceanica (L.) gained the centrality of several international climate change mitigation projects being the most effective carbon storage sink among Mediterranean seagrasses. To assess and monitor the change of environmental conditions and economic values of natural resources, the present study moves from the insights of the System of Environmental-Economic Accounting – Ecosystem Accounting to assess the economic value of the carbon sequestration and storage capacity of the Mediterranean-endemic seagrass P. oceanica at the Tremiti Islands Marine Protected Area. The economic value is compared across: i. the reference study by Pergent-Martini et al.; ii. the ecological condition-based approach; and iii. the unit value transfer. Based on the obtained outcomes, an ecosystem-based approach would prevent biases in the accounting of the ecosystem-service provision capacity of P. oceanica and help the policy maker to implement adequate public investment policies to mitigate its overall degradation.

Unveiling the epigenetic landscape of plants using flow cytometry approach.

Plants are sessile creatures that have to adapt constantly changing environmental circumstances. Plants are subjected to a range of abiotic stressors as a result of unpredictable climate change. Understanding how stress-responsive genes are regulated can help us better understand how plants can adapt to changing environmental conditions. Epigenetic markers that dynamically change in response to stimuli, such as DNA methylation and histone modifications are known to regulate gene expression. Individual cells or particles' physical and/or chemical properties can be measured using the method known as flow cytometry. It may therefore be used to evaluate changes in DNA methylation, histone modifications, and other epigenetic markers, making it a potent tool for researching epigenetics in plants. We explore the use of flow cytometry as a technique for examining epigenetic traits in this thorough discussion. The separation of cell nuclei and their subsequent labeling with fluorescent antibodies, offering information on the epigenetic mechanisms in plants when utilizing flow cytometry. We also go through the use of high-throughput data analysis methods to unravel the complex epigenetic processes occurring inside plant systems.

Photosvaltable Characteristics Monitoring System Using the Internet of Things (IOT)

&#x0D; &#x0D; &#x0D; &#x0D; Continuous monitoring of solar panel performance is essential to ensure effective and efficient generation of electrical energy. Developing a monitoring system such as an I-V characteristic curve tracker enables real-time monitoring and identification of potential problems or efficiency improvements. The system utilizes a circuit switching system for accurate and continuous measurement, providing insight into how the solar panel responds to changing environmental and load conditions. The data recorded by temperature, light intensity, current, and voltage sensors on the solar panel provides valuable information about its condition and the environmental factors affecting it. Utilizing IoT technology allows real-time monitoring of the data, accessible via a web page and presented graphically. The data is also stored in Excel format for further analysis, so users can access and monitor continuously as long as they are connected to the internet. From the experimental results, the Voc of the solar panel ranged from 18.7 V to 20.42 V, and Isc between 0.0727 A to 0.2145 A, which were tested under solar irradiation ranging from 100 to 500 W/m². This research demonstrates the importance of continuous monitoring and the effectiveness of the developed monitoring system in providing real-time data for analysis and optimization of solar panel performance. The system has been tested to meet the IEC No. 13B-23 standard for accuracy classes 0.2 and 0.5. A comparison between manual testing and sensor testing shows that despite the difference in accuracy levels, the sensor measurements have a relatively low average error (1.04% for voltage and 0.64% for current) compared to manual measurements, indicating that the sensor is reliable in providing accurate data. This demonstrates the reliability and effectiveness of using the sensor in the solar panel characteristics monitoring system.&#x0D; &#x0D; &#x0D; &#x0D;

Intrinsic and extrinsic drivers of organic matter processing along phosphorus and salinity gradients in coastal wetlands

Abstract Climate change is accelerating sea‐level rise and saltwater intrusion in coastal regions world‐wide and interacting with large‐scale changes in species composition in coastal wetlands. Quantifying macrophyte litter breakdown along freshwater‐to‐marine coastal gradients is needed to predict how carbon stores will respond to shifts in both macrophyte communities and water chemistry under changing environmental conditions. To test the interactive drivers of changing species identity and water chemistry, we performed a reciprocal transplant of four macrophyte litter species in seven sites along freshwater‐to‐marine gradients in the Florida Coastal Everglades. We measured surface water chemistry (dissolved organic carbon, total nitrogen and total phosphorus), litter chemistry (% nitrogen, % phosphorus, change in N:P molar ratio, % cellulose and % lignin as proxies for recalcitrance) and litter breakdown rates (k/degree‐day). Direct effects of salinity and surface water nutrients were the strongest drivers of k, but unexpectedly, litter chemistry did not correlate with litter k. However, salinity strongly correlated with changes in litter chemistry, whereby litter incubated in brackish and marine wetlands was more labile and gained more phosphorus compared with litter in freshwater marshes. Our results suggest that litter k in coastal wetlands is explained by species‐specific interactions among water and litter chemistries. Water nutrient availability was an important predictor of breakdown rates across species, but breakdown rates were only explained by the carbon recalcitrance of litter in the species with the slowest breakdown (Cladium jamaicense), indicating the importance of carbon structure, and species identity on breakdown rates. Synthesis. In oligotrophic ecosystems, nutrients are often the primary driver of organic matter breakdown. However, we found that variation in macrophyte breakdown rates in oligotrophic coastal wetlands was also explained by salinity and associated seawater chemistry, emphasising the need to understand how saltwater intrusion will alter organic matter processing in wetlands. Our results suggest that marine subsidies associated with sea‐level rise have the potential to accelerate leaf litter breakdown. The increase in breakdown rates could either be buffered or increase further as sea‐level rise also shifts macrophyte community composition to more or less recalcitrant species.

Asymmetrically superwetting Janus membrane constructed by laser-induced graphene (LIG) for on-demand oil–water separation and electrothermal anti-/de-icing

Superwetting functional surfaces based on laser-induced graphene (LIG) have a wide range of applications in many fields. However, single wettability LIG films are difficult to respond to complex and changing environmental conditions. Despite the large number of experiments were carried out to demonstrate the formation of LIG, there is a lack of studies on the process and formation mechanisms of LIG. In this study, the conversion of PEI to graphene was systematically investigated by both experimental and molecular dynamics simulations. A new method for obtaining Janus membranes with both superhydrophobicity and superhydrophilicity by ethanol and plasma treatment of LIG is proposed. The asymmetrically superwetting Janus membrane are shown to realize the on-demand controllable separation of light oil–water and heavy oil–water. In addition, the superhydrophobic LIG is used as a coating material with excellent electrothermal properties, which provide the performance of anti-icing and electrothermal de-icing. The asymmetrically superwetting Janus membranes prepared by the proposed simple and environmentally friendly method are shown to have a variety of prospective applications.

Climate change and zoonotic diseases: a conceptual framework for predicting and managing health risks in the USA

The executive summary will provide a concise overview of the conceptual framework aimed at understanding the relationship between climate change and zoonotic diseases in the USA. It will highlight the significance of addressing this issue, the objectives of the framework, expected outcomes, and the proposed methodology for research and implementation. It encapsulates the essence of the proposed framework, highlighting its significance, objectives, methodology, and expected outcomes. Climate change poses a significant threat to public health, exacerbating the emergence and transmission of zoonotic diseases across the USA. This executive summary underscores the critical need for a proactive approach to understanding and managing the complex interplay between climate change and zoonotic diseases to safeguard the health of communities. The framework aims to address this pressing issue by elucidating the mechanisms through which climate change influences the dynamics of zoonotic diseases. By integrating multidisciplinary research, predictive modeling, and public health strategies, the framework seeks to enhance the nation's capacity to predict, prevent, and mitigate the health risks associated with climate change-driven zoonotic diseases. Key objectives of the framework include developing predictive models to identify high-risk areas and vulnerable populations, elucidating the pathways of disease transmission, and proposing evidence-based interventions to mitigate health risks. By fostering collaboration among researchers, policymakers, and public health practitioners, the framework aims to translate research findings into actionable strategies and policies that protect public health and promote resilience in the face of climate change. Expected outcomes of the framework include improved understanding of the complex relationship between climate change and zoonotic diseases, enhanced surveillance and early warning systems, and informed decision-making to guide public health interventions. Ultimately, the framework seeks to empower communities and decision-makers with the knowledge and tools needed to adapt to changing environmental conditions and mitigate the health impacts of zoonotic diseases in the USA.

IOT based smart street light fault detection management system

In the contemporary landscape of urbanization and technological progress, efficient resource management, particularly in energy consumption, is paramount. Street lighting stands out as a significant energy consumer in urban environments. This paper proposes a Smart Street Light Fault Detection System utilizing Internet of Things (IoT) technology, a NodeMCU microcontroller, Light Dependent Resistor (LDR), street lights, and the ThingSpeak. The system employs the NodeMCU microcontroller to monitor ambient light conditions through the LDR sensor, enabling automatic control of street lights to optimize energy usage. Furthermore, it integrates fault detection mechanisms to identify abnormalities in street light operations, such as constant light levels amidst changing environmental conditions, indicative of potential faults. Through the ThingSpeak, users can remotely monitor real-time LDR readings, receive notifications about detected faults, and take necessary actions, empowering city authorities or maintenance personnel with timely information for addressing issues and ensuring smooth infrastructure operation. This smart system offers advantages like energy efficiency, automated control, and proactive fault detection, facilitating significant energy savings, reduced maintenance costs, and enhanced sustainability in urban environments, thereby showcasing a practical implementation of IoT technology for smarter and more sustainable cities.

Chemical engineering and the circular water economy: Simulations for sustainable water management in environmental systems

In the face of escalating water scarcity and environmental degradation, the imperative for sustainable water management has never been more urgent. Chemical engineering emerges as a pivotal discipline in the pursuit of solutions to these pressing challenges. This review explores the role of chemical engineering in advancing the circular water economy paradigm through simulations aimed at fostering sustainable water management within environmental systems. The circular water economy concept advocates for the efficient utilization, recycling, and reclamation of water resources to minimize waste and maximize resource efficiency. Chemical engineering techniques play a fundamental role in realizing this vision through the design and optimization of water treatment processes, resource recovery systems, and advanced simulation methodologies. This review delves into the application of computational simulations within the realm of chemical engineering to model and analyze various aspects of the water cycle. Such simulations enable the assessment of complex environmental systems, aiding in the identification of optimal strategies for water resource allocation, pollution control, and ecosystem preservation. Key areas of focus include the simulation of wastewater treatment processes, such as biological, physical, and chemical treatment methods, to enhance pollutant removal efficiency and promote water reuse. Furthermore, advanced modeling techniques facilitate the evaluation of innovative technologies like membrane filtration, adsorption, and electrochemical processes for the purification and desalination of water resources. Moreover, chemical engineering simulations enable the assessment of integrated water management strategies, encompassing aspects of urban water systems, industrial processes, and agricultural practices. By considering the interconnectedness of various sectors, holistic approaches to water resource management can be formulated, promoting resilience and sustainability in the face of changing environmental conditions. The integration of chemical engineering simulations into the framework of the circular water economy offers a promising avenue for advancing sustainable water management practices. Through comprehensive modeling and analysis, informed decision-making can pave the way towards a more resilient and equitable water future, ensuring the long-term viability of our environmental systems.

Common bean under different water availability reveals classifiable stimuli-specific signatures in plant electrome

ABSTRACT Plant electrophysiology has unveiled the involvement of electrical signals in the physiology and behavior of plants. Spontaneously generated bioelectric activity can be altered in response to changes in environmental conditions, suggesting that a plant’s electrome may possess a distinct signature associated with various stimuli. Analyzing electrical signals, particularly the electrome, in conjunction with Machine Learning (ML) techniques has emerged as a promising approach to classify characteristic electrical signals corresponding to each stimulus. This study aimed to characterize the electrome of common bean (Phaseolus vulgaris L.) cv. BRS-Expedito, subjected to different water availabilities, seeking patterns linked to these stimuli. For this purpose, bean plants in the vegetative stage were subjected to the following treatments: (I) distilled water; (II) half-strength Hoagland’s nutrient solution; (III) −2 MPa PEG solution; and (IV) −2 MPa NaCl solution. Electrical signals were recorded within a Faraday’s cage using the MP36 electronic system for data acquisition. Concurrently, plant water status was assessed by monitoring leaf turgor variation. Leaf temperature was additionally measured. Various analyses were conducted on the electrical time series data, including arithmetic average of voltage variation, skewness, kurtosis, Probability Density Function (PDF), autocorrelation, Power Spectral Density (PSD), Approximate Entropy (ApEn), Fast Fourier Transform (FFT), and Multiscale Approximate Entropy (ApEn(s)). Statistical analyses were performed on leaf temperature, voltage variation, skewness, kurtosis, PDF µ exponent, autocorrelation, PSD β exponent, and approximate entropy data. Machine Learning analyses were applied to identify classifiable patterns in the electrical time series. Characterization of the electrome of BRS-Expedito beans revealed stimulus-dependent profiles, even when alterations in water availability stimuli were similar in terms of quality and intensity. Additionally, it was observed that the bean electrome exhibits high levels of complexity, which are altered by different stimuli, with more intense and aversive stimuli leading to drastic reductions in complexity levels. Notably, one of the significant findings was the 100% accuracy of Small Vector Machine in detecting salt stress using electrome data. Furthermore, the study highlighted alterations in the plant electrome under low water potential before observable leaf turgor changes. This work demonstrates the potential use of the electrome as a physiological indicator of the water status in bean plants.

The caspase family: molecular bases of interaction in apoptosis and pyroptosis

Both apoptotic and inflammatory caspases play a significant role in developing and maintaining an organism’s homeostasis. Recently, various studies have described various cross-interactions among various caspases. For instance, interleukin-1β activation is initiated by caspase-1 and caspase-8. Programmed cell death is launched not exclusively by internal and external factors to serve as a foundation for physiological development and realization of cellular and organism functions. The caspases involved in this process provide a complicated function related to cell homeostasis regulation. Caspases also participate in adaptation processes associated with changing environmental conditions, including microgravity.&#x0D; Phenotypical analysis of knockdown laboratory animals can reveal the physiological functions of caspases, giving preference to mice. For instance, this approach allows us to determine the role of caspases in the pathogenesis of different pathologic conditions, such as malignancies and autoimmune and infectious diseases. Caspases are considered by a wide spectrum of authors as therapeutic targets.&#x0D; In general, the topic of caspases and their functions is very broad. In this review, we only discuss some aspects of the impact of caspases on various types of cell death.

Rare taxa as the microbial taxa more sensitive to environmental changes drive alterations of daqu microbial community structure and function

Microbial interactions and environmental conditions determine the evolution of microbial communities and their functions during Nongxiangxing daqu (daqu) fermentation. In this study, the sensitivity of rare microbial taxa, conditionally rare-abundant microbial taxa and abundant microbial taxa, to environmental changes, as well as the impact of their presence on the microbial community structure and function during daqu fermentation were elucidated by using high-throughput sequencing technology combined with environmental and volatile metabolites analysis. The results indicated that rare taxa, which were the predominant microbial taxa, were more heterogeneous during the daqu fermentation process. It is necessary to note that rare taxa were more sensitive to changing environmental conditions. The microbial molecular ecological network and within-module connectivity and among-module connectivity analysis showed that most of the key nodes (∼63% of operational taxonomic units) located in the networks determining microbial interactions belong to rare taxa. Furthermore, rare taxa were significantly associated with more volatile metabolites, and rare taxa were particularly important for the synthesis of pyrazines and alcohols. The present study demonstrated that rare taxa, as the microbial taxa more susceptible to environmental variation, drive alterations in the structure of microbial communities and their functions.

Hierarchical foraging strategies of migratory short-tailed shearwaters during the non-breeding stage

Foraging specialisations are common in animal populations, because they increase the rate at which individuals acquire food from a known and reliable source. Foraging plasticity, however, may also be important in variable or changing environments. To better understand how seabirds might respond to changing environmental conditions, we assessed how plastic the foraging behaviours of short-tailed shearwaters (Ardenna tenuirostris) were during their non-breeding season. To do this, we tracked 60 birds using global location sensing loggers (GLS) over a single year between 2012 and 2016 with the exception of 8 individuals that were tracked over 2 consecutive years. Birds predominantly foraged in either the Sea of Okhotsk/North Pacific Ocean (Western strategy) or the southeast Bering Sea/North Pacific (Eastern strategy). The eight birds tracked for 2 consecutive years all returned to the same core areas, indicating that these birds were faithful to foraging areas between years, although the time spent there varied, probably in response to local changes in food availability. Overall, 50% of the birds we tracked left their core area towards the end of the non-breeding period, moving into the Chukchi Sea, suggesting that the birds have flexible intra-seasonal foraging strategies whereby they follow prey aggregations. We hypothesise that seasonal declines in chlorophyll a concentrations in their primary core foraging areas coincide with changes in the availability of large-bodied krill, an important food source for short-tailed shearwaters. Decreasing prey abundance likely prompts the movement of birds out of their core foraging areas in search of food elsewhere. This strategy, through which individuals initially return to familiar areas but disperse if food is limited, provides a mechanism that allows the birds to respond to the effects of climate variability.