Face Of Global Warming Research Articles

Comprehensive phenomic and genomic studies of the species, Pectobacterium cacticida and proposal for reclassification as Alcorniella cacticida comb. nov

IntroductionPectobacterium cacticida was identified as the causative agent of soft rot disease in cacti. Due to a high potential of spread in the face of global warming, the species poses a significant threat to horticultural and crop industry. The aim of this study was to revise the genomic, physiology and virulence characteristics of P. cacticida and update its phylogenetic position within the Pectobacterium genus.MethodsWhole genome sequences of five P. cacticida strains were obtained and subjected to comprehensive genomic and phylogenomic data analyses. We assessed the presence of virulence determinants and genes associated with host and environmental adaptation. Lipidomic analysis, as well as biochemical and phenotypic assays were performed to correlate genomic findings.ResultsPhylogenomic analysis revealed that P. cacticida forms a distinct lineage within the Pectobacterium genus. Genomic evaluation uncovered 516 unique proteins, most of which were involved in cellular metabolism. They included genes of carbohydrate metabolism and transport and ABC transporters. The main differing characteristics from other Pectobacterium species were the lack of a myo-inositol degradation pathway and the presence of the malonate decarboxylase gene. All tested strains were pathogenic towards Opuntia spp., chicory, Chinese cabbage, and potato, but exhibited only mild pathogenicity towards carrot.DiscussionThis study sheds light into the genomic characteristics of P. cacticida and highlights the pathogenic potential of the species. Unique genes found in P. cacticida genomes possibly enhance the species’ survival and virulence. Based on phylogenomic analyses, we propose the reclassification of P. cacticida to a new genus, Alcorniella comb. nov.

Thermal stress-stimulated ZnO toxicity inhibits reproduction of freshwater crustacean Daphnia magna

Elevated temperatures due to climate change pose a variety of environmental risks to the freshwater ecosystem. At the same time, zinc oxide (ZnO) has become widely used and has entered the freshwater environment. As thermal stress may potentially impact the physicochemical properties of ZnO, its toxicity to freshwater organisms in the face of global warming is poorly understood. The potential effects on reproductive performances, including oogenesis, are of particular concern. In this study, we investigate the reproductive performances and related mRNA abundance of the zooplankton Daphnia magna under conditions of ZnO exposure and heat stress. The results revealed that ZnO and elevated temperature delayed maturity and juvenile production of D. magna. Histological observations indicated that oogenesis was inhibited, and the number and size of oocytes were reduced in the condition of ZnO exposure under heat stress. Eventual offspring in the same treatment exhibited decreased numbers, size, and quality. Congenital juvenile anomalies were increased, such as deformed eye, and impaired antenna and tail spine. Moreover, both ZnO and elevated temperature treatments inhibited expression levels of reproduction-related genes (vtg, EcR and VMO1) and induced the dmrt93b gene involved in the production of male offspring. Furthermore, we found that D. magna tried to cope with ZnO and thermal stress by upregulating hsp90, HIF-1α and HIF-1β. ZnO and heat stress inhibited the reproductive capacity of D. magna, produced deleterious effects on reproduction-associated physiological pathways, and damaged reproductive outcomes.

Response of WUE of maize at ear stage to the coupling effect of CO2 and temperature

In the face of global warming, the photosynthesis and transpiration of plants will change greatly, which will ultimately affect the water use efficiency (WUE) of plants. In order to study the coupling effects of CO2 and temperature on WUE of maize at ear stage, ‘Zhengdan 958’ was taken as the research object, and 5 temperatures (20 °C, 25 °C, 30 °C, 35 °C and 40 °C) and 11 CO2 concentration (400, 300, 200, 150, 100, 50, 400, 400, 600, 800 and 1000 μmol mol−1) were set to measure the parameters such as net photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (Gs) and intercellular CO2 concentration (Ci) of single leaves. The response of WUE (Pn/Tr) to CO2 and temperature was evaluated by a CO2 response model. The results show that at the same temperature, Pn and WUE increased with CO2 level, while Tr decreased as CO2 level increases; at the same CO2 concentration, Pn and Tr were both positively correlated with temperature, while WUE decreased with the increase of temperature. The maximum value of WUE was obtained when the CO2 concentration was 1000 μmol mol−1 and the temperature was 20.0 °C. The results suggest that global warming will not improve WUE of maize, which will bring more severe challenges to water-saving agriculture and food security.

Regenerative strategies of Euterpe edulis (Arecaceae) at its altitudinal limits in the Atlantic Forest

AbstractPopulations occurring at the limit of a species' altitudinal distribution undergo strong environmental filtering. Rapid climate change intensifies this process, impacting ecological responses of populations. Understanding the effects of climate change, especially in the early stages of plant development, has become essential to predict vulnerability to extinction. However, few studies have explored initial establishment strategies of plant populations at the limit of their distribution in the face of global warming. We tested the effects of increasing temperatures on germination performance and on initial seedling establishment on two populations of Euterpe edulis, a palm tree widely distributed in the Atlantic Forest between 0 and 1400 m altitude. The tests were conducted in a laboratory, where the seeds were exposed to three conditions for 90 days: control at 25°C, and two treatments at higher temperatures (35 and 40°C). Germination percentage was not affected by population, seed size class or treatments. Average time for germination only increased in the Montane Forest population in the most extreme treatment, while in the sea level Restinga population, time for germination was affected by a small temperature increase. Mortality percentage in the Restinga population was similar in the post‐germination phase and in the temperature treatments. We concluded that E. edulis populations located at their lower altitudinal limit are closer to the species thermal limit, thus being more vulnerable to temperature increase than populations at the upper limit of the species' altitudinal distribution.

Revisiting dynamic linkages among ecological sustainability, tourism, and climate change in China.

The research intends to inquire into the dynamic connections between ecological sustainability, tourism, and climate change. This novel approach aims to investigate the interdependencies among these three important variables. This research aims to examine tourism's effects on environmental sustainability in the face of global warming. We use a large dataset that comprises measures of tourist success, measurements of environmental sustainability, and climate change factors. Applying empirical estimation techniques allows a more detailed look at the data by accounting for variation across quantiles. The results of this study will aid in expanding our knowledge of the relationships among ecological sustainability, tourism, and climate change. To better understand the influence of tourism on ecological sustainability, it is helpful to quantify the interactions at various quantiles. Policymakers, stakeholders in the tourist sector, and environmental groups will find this information essential as they work to establish focused measures to encourage environmentally responsible travel and lessen the impact of climate change. This investigation also provides policy implications by shedding light on the interplay of tourist growth, ecological sustainability, and climate change reduction and offers research-based research solutions for achieving this delicate balancing action.

Elevational patterns of species richness and community structure of understorey birds in an East African montane forest

AbstractMt. Kasigau is the northeastern most of the Eastern Arc Mountains global hotspot and harbours some endemic and threatened species, but little is known about bird community changes along its elevational gradient. We assessed the relationship between bird biodiversity metrics, season, human disturbance, elevation and temperature using mist‐netting data collected bi‐annually over a 10‐year period. Birds were sampled along the mountain's elevational gradient at four elevation levels (858, 1104, 1321 and 1547 m). Bird richness, diversity and evenness decreased with increasing altitude in both dry and wet seasons. Bird abundance declined with increasing elevation for the lower three elevation levels but peaked at the highest elevation. All diversity metrics were higher in the wet season compared to the dry season across all the years. Elevation had a greater effect on species assemblages than season, disturbance and temperature. Temperature had significant effects on abundance, diversity and richness, while disturbance had significant effects on diversity, evenness and richness. We conclude that bird assemblages in Mt. Kasigau are strongly shaped by elevational changes, while temperature and disturbance constitute important factors influencing bird conservation in the face of global warming. Our study highlights that elevation, disturbance and temperature influence bird assemblages along tropical elevational gradients.

Environment security perspective to coral reef protection and management: a comparative study of India and Australia

ABSTRACT Coral reefs are home to a variety of flora and fauna and carry huge potential in serving the national interests of the coastal states that host them. The research uses an environment security theoretical framework to understand how it is the state’s prerogative to protect coral reefs to protect its own national interest. Active state involvement in the protection of reef ecosystems is the most practical option in the face of global warming and climate change, with limited consensus on this environmental problem within the international community. The research explains how a state can actively engage in coral reef management by focusing on pollution control related to tourist activity in the reef areas. A comparative analysis of coral reef management by India and Australia shows how active coral reef management can help protect reef structures, giving maximum return benefits to the state.

Climate dependence of the macrofaunal effect on litter decomposition-A global meta-regression analysis.

Litter decomposition by microorganisms and animals is influenced by climate and has been found to be higher in warm and wet than in cold and dry biomes. We, however, hypothesized that the macrofaunal effect on decomposition should increase with temperature and aridity since larger animals are more tolerant to aridity than smaller organisms. This hypothesis was supported by our global analysis of macrofauna exclusion studies. Macrofauna increased litter mass loss on average by 40%, twofold higher than the highest previous estimation of macrofaunal effect on decomposition. The strongest effect was found in subtropical deserts where faunal decomposition had not been considered important. Our results highlight the need to consider animal size when exploring climate dependence of faunal decomposition, and the disproportionately large role of macrofauna in regulating litter decomposition in warm drylands. This new realization is critical for understanding element cycling in the face of global warming and aridification.

C4 maize and sorghum are more sensitive to rapid dehydration than C3 wheat and sunflower.

The high productive potential, heat resilience, and greater water use efficiency of C4 over C3 plants attract considerable interest in the face of global warming and increasing population, but C4 plants are often sensitive to dehydration, questioning the feasibility of their wider adoption. To resolve the primary effect of dehydration from slower from secondary leaf responses originating within leaves to combat stress, we conducted an innovative dehydration experiment. Four crops grown in hydroponics were forced to a rapid yet controlled decrease in leaf water potential by progressively raising roots of out of the solution while measuring leaf gas exchange. We show that, under rapid dehydration, assimilation decreased more steeply in C4 maize and sorghum than in C3 wheat and sunflower. This reduction was due to a rise of nonstomatal limitation at triple the rate in maize and sorghum than in wheat and sunflower. Rapid reductions in assimilation were previously measured in numerous C4 species across both laboratory and natural conditions. Hence, we deduce that high sensitivity to rapid dehydration might stem from the disturbance of an intrinsic aspect of C4 bicellular photosynthesis. We posit that an obstruction to metabolite transport between mesophyll and bundle sheath cells could be the cause.

Ideal water temperature environment for giant Marimo (Aegagropila linnaei) in Lake Akan, Japan

Aegagropila linnaei is a filamentous green algal species that often forms beautiful spherical shapes called "lake balls" or "Marimo". A. linnaei were once globally distributed around the world, but the population has been declining for several decades. Lake Akan, in Japan, is now the only lake in the world with a colony of giant Marimo (over 20 cm in diameter). Here we show the net growth rate of Marino resulting from photosynthesis and decomposition based on laboratory experiments, MRI analysis, and quantitative element analysis, which show the decomposition rate, the maximum annual Marimo diametric growth rate, and the carbon-to-nitrogen ratio, respectively. We found an explicit dependence of the decomposition rate of Marimo on the cumulative water temperature, with a threshold of 7 °C. MRI analysis showed a high correlation among a Marimo's diameter, surface thickness, and annual diametric growth rate. Moreover, the C/N ratio was high in the exterior side of the surface thickness, indicating that this layer is the main growth area for photosynthesis. These results suggest that the central cavity and the surface thickness represent the change in the growth environment such as water temperature and light intensity. Between the 1980s and the present, Between the 1980s and the present, the cumulative water temperature has increased from about 1250 to about 1600 °C-days. Therefore, the maximum surface thickness has decreased by approximately 1 cm, as estimated by water temperature records and annual diametric growth rates10. As a measure to preserve preferable conditions for colonies of giant Marimo in the face of global warming, the flow of low-temperature river water into Marimo colonies should be protected.

Assessing the Water Status and Leaf Pigment Content of Olive Trees: Evaluating the Potential and Feasibility of Unmanned Aerial Vehicle Multispectral and Thermal Data for Estimation Purposes

Global warming presents a significant threat to the sustainability of agricultural systems, demanding increased irrigation to mitigate the impacts of prolonged dry seasons. Efficient water management strategies, including deficit irrigation, have thus become essential, requiring continuous crop monitoring. However, conventional monitoring methods are laborious and time-consuming. This study investigates the potential of aerial imagery captured by unmanned aerial vehicles (UAVs) to predict critical water stress indicators—relative water content (RWC), midday leaf water potential (ΨMD), stomatal conductance (gs)—as well as the pigment content (chlorophyll ab, chlorophyll a, chlorophyll b and carotenoids) of trees in an olive orchard. Both thermal and spectral vegetation indices are calculated and correlated using linear and exponential regression models. The results reveal that the thermal vegetation indices contrast in estimating the water stress indicators, with the Crop Water Stress Index (CWSI) demonstrating higher precision in predicting the RWC (R2 = 0.80), ΨMD (R2 = 0.61) and gs (R2 = 0.72). Additionally, the Triangular Vegetation Index (TVI) shows superior accuracy in predicting the chlorophyll ab (R2 = 0.64) and chlorophyll a (R2 = 0.61), while the Modified Chlorophyll Absorption in Reflectance Index (MCARI) proves most effective for estimating the chlorophyll b (R2 = 0.52). This study emphasizes the potential of UAV-based multispectral and thermal infrared imagery in precision agriculture, enabling assessments of the water status and pigment content. Moreover, these results highlight the vital importance of this technology in optimising resource allocation and enhancing olive production, critical steps towards sustainable agriculture in the face of global warming.

Taylor DQN: An Optimization Method for Aircraft Engine Cleaning Schedule

Reducing carbon emissions and improving revenue in the face of global warming and economic challenges is a growing concern for airlines. This paper addresses the inefficiencies and high costs associated with current aero-engine on-wing washing strategies. To tackle this issue, we propose a reinforcement learning framework consisting of a Similar Sequence Method and a Taylor DQN model. The Similar Sequence Method, comprising a sample library, DTW algorithm, and boundary adjustment, predicts washed aero-engine data for the Taylor DQN model. Leveraging the proposed Taylor neural networks, our model outputs Q-values to make informed washing decisions using data from the Similar Sequence Method. Through simulations, we demonstrate the effectiveness of our approach.

Effects of Building Materials on Building Thermal Load in Malaysian Institutional Library

Green building, net-zero energy building, low energy building, and sustainable building are the common terms being used in the building industry nowadays, with the primary aim to produce buildings with low energy and low carbon dioxide (CO2) emissions. Different types of building materials can have significant implications for energy efficiency, especially in the warming climate. The energy crisis, future global warming, and climate change can be mitigated by choosing the right building materials, which will also lower the building's energy consumption and carbon dioxide emissions. This paper presents the effects of different building materials on the cooling capacity and cooling energy consumption of a building for four (4) different climate change weather data, namely, the present time scenario, the 2020s, 2050s, and 2080s time scenario using TRNSYS simulation software. The main library of a university in Petaling Jaya, Malaysia, was chosen as the case study. Three (3) types of building materials were studied, namely, Type 1 (brick walls with single-glazed windows), Type 2 (foam insulation cavity walls with double-glazed windows), and Type 3 (air gap cavity walls with double-glazed windows). The simulation results showed that the Type 2 building materials could reduce the yearly cooling energy consumption by 14.5%, compared with the current building materials (brick walls with single-glazed windows). The Type 3 building materials (air gap cavity walls with double-glazed windows) with the lower installation were wound to reduce the yearly cooling energy consumption by 9% compared with the Type 1 building materials. For architects, designers, politicians, and library administrators, the research's conclusions have immediate practical implications that will help them make decisions and implement energy-saving plans. In the end, this research helps libraries in Malaysia remain sustainable and resilient in the face of global warming and the energy crisis.

Pavement Temperature Forecasts Based on Model Output Statistics: Experiments for Highways in Jiangsu, China

Forecasts on transportation meteorology, such as pavement temperature, are becoming increasingly important in the face of global warming and frequent disruptions from extreme weather and climate events. In this study, we propose a pavement temperature forecast model based on stepwise regression—model output statistics (SRMOS) at the short-term timescale, using highways in Jiangsu, China, as examples. Experiments demonstrate that the SRMOS model effectively calibrates against the benchmark of the linear regression model based on surface air temperature (LRT). The SRMOS model shows a reduction in mean absolute errors by 0.7–1.6 °C, with larger magnitudes observed for larger biases in the LRT forecasts. Both forecasts exhibit higher accuracy in predicting minimum nighttime temperatures compared to maximum daytime temperatures. Additionally, it overall shows increasing biases from the north to the south, and the SRMOS superiority is greater over the south with larger initial LRT biases. Predictor importance analysis indicates that temperature, moisture, and larger-scale background are basically the key predictors in the SRMOS model for pavement temperature forecasts, of which the air temperature is the most crucial factor in the model’s construction. Although larger-scale circulation backgrounds are generally characterized by relatively low importance, their significance increases with longer lead times. The presented results demonstrate the considerable skill of the SRMOS model in predicting pavement temperatures, highlighting its potential in disaster prevention for extreme transportation meteorology events.

Лось (Alces alces) на південній межі ареалу: стан популяції Центрального Полісся, хижацтво вовка та вразливість до потепління клімату

In the latter less hot years after the decline in the number of elk (2019–2020), the stabilisation and increasing trend in the number of this species have been observed throughout the study area. Due to migrations, the winter elk population exceeds the summer one and amounts to 2 individuals/thousand hectares (40 individuals; against 1.3 individuals/1 thousand hectares in summer) in the Polissia Reserve, and 1–6 individuals/1 thousand hectares (940 individuals) in the Chornobyl Reserve. Data on the vulnerability of elk to climate change are presented. In hot weather at different times of the year, elks may show signs of heat stress. In summer, elk can be inactive, and in the leafless period, when chased by wolves, they can get heat stress and die. In the heat of the day, elk choose swamps, waterlogged forests with a dense tree canopy and better cooling, which are comfortable for these ungulates in the face of global warming. Climate change causes marshes to dry up and overgrow, reduces the moisture content of habitats, and worsens the fodder capacity of the land. In case of even partial restoration of lowland marshes in the Chornobyl Biosphere Reserve, the reserves of summer and winter food for elk may increase by 2–3 times. In the Polissia Reserve, in 2011–2013, lowland bogs with bush willows (Salix) were restored on fallow land near the Zholobnytsia drainage system, creating highly productive habitats for the elk, which is a promising measure for different areas of Polissia. Climate warming has led to an increase in the red deer (Cervus elaphus) population and a decrease in the elk population in the Polissia, and if no special measures are taken, these trends will intensify. Outside of protected areas, given the lack of a high legal status for wolves (Canis lupus), a strategy for conserving the elk population and reducing predation mortality in combination with other elk habitat management strategies can be recommended to hunting ground users, including limiting poaching, restoring the natural regime of forest fires in reserves, improving winter provision of branch fodder, reducing the disturbance factor, and introducing a ban on staying in the forest with dogs for berry and mushroom pickers.

Global transportation infrastructure exposure to the change of precipitation in a warmer world

Transportation infrastructures are generally designed to have multi-decadal service lives. Transport infrastructure design, however, is largely based on historical conditions. Yet, in the face of global warming, we are likely going to experience more intense and frequent extreme events, which may put infrastructure at severe risk. In this study, we comprehensively analyze the exposure of road and railway infrastructure assets to changes in precipitation return periods globally. Under ~2 degrees of warming in mid-century (RCP 8.5 scenario), 43.6% of the global transportation assets are expected to experience at least a 25% decrease in design return period of extreme rainfall (a 33% increase in exceedance probability), which may increase to 69.9% under ~4 degrees of warming by late-21st century. To accommodate for such increases, we propose to incorporate a safety factor for climate change adaptation during the transportation infrastructure design process to ensure transportation assets will maintain their designed risk level in the future. Our results show that a safety factor of 1.2 would work sufficient for most regions of the world for quick design process calculations following the RCP4.5 path.

Household energy use response to extreme heat with a biophysical model of temperature regulation: An Arizona case study

Rising temperatures associated with climate change are impacting household energy use. Many of today’s industrial-technological-urban humans thermoregulate in the face of varying temperatures using extra-metabolic energy use for heating and cooling our indoor microclimates. Previously, household energy use as a function of temperature change over seasons and time has been described using a three-part model of thermoregulation, the Extra-Metabolic Scholander-Irving model (EMSI), where energy use is lowest in the thermal neutral zone around room temperature and increases in colder and hotter temperatures. However, the EMSI model has only been evaluated for moderately warm cities to date, covering only two parts of the three-part model and lacking evaluation of data for extremely hot temperatures. We show that household energy use in Arizona, a U.S. state that includes hot semi-arid environments, varies across topography, and increases in response to the hottest summer months–exemplifying the third part of the EMSI model. Additionally, household energy use is lowest in the spring and fall and increases in response to colder temperatures in the winter. This relationship has hysteresis related to differences in household income; service regions with lower-income households delay the onset of extra-metabolic energy use for cooling. We use this model to gain predictive insights into energy use demand due to ongoing warming in the context of the desert city of Yuma, Arizona, where a relatively small increase in mean temperatures of ~1.5°C since the Industrial Revolution produced a 20-day increase (6%) in cooling days annually. Our study expands the EMSI model of thermal regulation to the previously missing hot part of the model, thereby gaining insights into the unique challenges of sustaining extra-metabolic thermoregulation in the face of global warming.

Elevated temperature induces contrasting transformation of exogenous copper to soil solution and solid phases in an arable soil

Heavy metal contamination of soils has been a global environmental issue over the past decades, threatening food security and human health. Understanding the migration and transformation of heavy metals in soils is critical for restoring an impaired environment and developing sustainable agriculture, particularly in the face of global warming. However, little effort has been devoted to investigating the impact of elevated temperatures on the migration and distribution of exogenous heavy metals in soils. This study experimented with a 180-day incubation at 15 °C, 30 °C, and 45 °C with an arable soil (Alfisol) of Huang-Huai-Hai River Basin, China, which was initially spiked with copper (Cu). A comparison of the results revealed that the percentage of soil water-soluble Cu doubled at 45 °C compared with 15 °C. The percentage of protein-like substances in dissolved organic matter (DOM) was the highest at 45 °C, suggesting that proteinaceous components play a more significant role in controlling the dissolution of Cu into DOM. Moreover, by sequential extraction and micro-X-ray fluorescence (μ-XRF), Cu was facilitatively transformed from exchangeable, and specifically adsorbed fractions, to iron (Fe)/manganese (Mn) oxides bound species by 7.75%23.63% with the elevation of temperature from 15 °C to 45 °C. The conversion of Cu speciation is attributed to the significant release of organic carbon from Fe/Mn oxides, especially the Mn oxide components, which are available for Cu binding. The findings of this work will provide an in-depth understanding of the fate of Cu in soils, which is fundamental for the risk assessment and remediation of Cu-polluted soils in the Huang-Huai-Hai River Basin under the context of global warming.

Green supply chain transformation and emission reduction based on machine learning.

Artificial intelligence techniques provide more possibilities for supply chain transformations in the face of global warming and environmental degradation. This study examines the Cournot game model of two competing supply chains with various carbon emission technologies as well as the possibility of upgrading machine learning technology. The investment risk of a supply chain's technology upgrade is either symmetric or asymmetric information. In the case of symmetric information, results show that the machine learning technology upgrade risk does not affect the market equilibrium outcomes of the duopoly model. However, in the case of asymmetric information, technology upgrade risk is vital in determining the quantities and prices of competition equilibrium. To achieve the goal of green supply chain transformation, the government should provide more technology and financial support to traditional supply chains to upgrade their machine learning technology on carbon emissions.

Development of a Carbon Financial Performance Assessment Model for the Power Generation Industry

In the face of global warming, sustainable development has become a universal choice for all countries in the world. China has put forward the goal of "double carbon" and promoted the low-carbon transformation of traditional energy enterprises, which has put forward higher requirements for their energy saving and emission reduction. In this context, this paper presents a comprehensive analysis of the challenges and opportunities of carbon finance development at the micro level. And for power generation enterprises, a financial performance evaluation system is constructed from three dimensions: economic, social and environmental. The data of 18 indicators of 32 listed companies in power generation industry are selected as samples, and the mathematical model is assigned by CRITIC method, and the comprehensive financial performance evaluation of the above companies is carried out by TOPSIS method. It provides theoretical support and referential decisions for low-carbon transformation of power generation enterprises, with a view to improving the comprehensive efficiency of enterprises.