Variable Climatic Conditions Research Articles

Low-temperature perception and modulations in Ocimum basilicum commercial cultivar CIM-Shishir: Biosynthetic potential with insight towards climate-smart resilience

The newly released interspecific hybrid variety CIM-Shishir, resulting from a cross between Ocimum basilicum and Ocimum kilimandscharicum claims to be a multicut, lodging resistant, cold tolerant, high essential oil yielding with linalool rich variety. It has a purple-green stem and has a unique feature and advantage of better survival in the winter season than other O. basilicum varieties, illustrating its physiological mechanisms for cold tolerance. In this study, we subjected both the CIM-Shishir variety and a control plant to cold stress to investigate the impact of low temperatures on various physiological, trichome developments, secondary metabolite constitution aspects related to essential oil production, and gene expression. The analysis revealed a significantly higher density and altered morphology of trichomes on the leaf surface of the variety subjected to low temperatures, indicating its adaptation to cold conditions. Furthermore, when comparing the treated plants under low-temperature stress, it was observed that the relative electrolyte leakage and Malondialdehyde (MDA) contents substantially increased in the control in contrast to the CIM-Shishir variety. This finding suggests that CIM-Shishir exhibits superior cold tolerance. Additionally, an increase in proline content was noted in the variety exposed to low temperatures compared to the control. Moreover, the chlorophyll and anthocyanin content gradually increased with prolonged exposure to low-temperature stress in the newly developed variety, indicating its ability to maintain photosynthetic capacity and adapt to cold conditions. The activities of superoxide dismutase (SOD) also increased under low-temperature conditions in the CIM-Shishir variety, further highlighting its cold tolerance behaviour. In our research, we investigated the comprehensive molecular mechanisms of cold response in Ocimum. We analyzed the expression of key genes associated with cold tolerance in two plant groups: the newly developed hybrid variety known as CIM-Shishir Ocimum, which exhibits cold tolerance, and the control plants susceptible to cold climates that include WRKY53, ICE1, HOS1, COR47, LOS15, DREB5, CBF4, LTI6, KIN, and ERD2. These genes exhibited significantly higher expression levels in the CIM-Shishir variety compared to the control, shedding light on the genetic basis of its cold tolerance. The need for climate-smart, resilient high-yielding genotype is of high importance due to varied climatic conditions as this will hit the yield drastically and further to the economic sectors including farmers and many industries that are dependent on the bioactive constituents of Ocimum.

Greater local cooling effects of trees across globally distributed urban green spaces

Urban green spaces (UGS) are an effective mitigation strategy for urban heat islands (UHIs) through their evapotranspiration and shading effects. Yet, the extent to which local UGS cooling effects vary across different background climates, plant characteristics and urban settings across global cities is not well understood. This study analysed 265 local air temperature (TA) measurements from 58 published studies across globally distributed sites to infer the potential influence of background climate, plant and urban variables among different UGS types (trees, grass, green roofs and walls). We show that trees were more effective at reducing local TA, with reductions 2–3 times greater than grass and green roofs and walls. We use a hierarchical linear mixed effects model to reveal that background climate (mean annual temperature) and plant characteristics (specific leaf area vegetation index) had the greatest influence on cooling effects across UGS types, while urban characteristics did not significantly influence the cooling effects of UGS. Notably, trees dominated the overall local cooling effects across global cities, indicating that greater tree growth in mild climates with lower mean annual temperatures has the greatest mitigation potential against UHIs. Our findings provide insights for urban heat mitigation using UGS interventions, particularly trees across cities worldwide with diverse climatic and environmental conditions and highlight the essential role of trees in creating healthy urban living environments for citizens under extreme weather conditions.

Towards a generic solution to onsite wastewater treatment

Decentralized wastewater treatment, specifically onsite treatment, is fundamental to recent wastewater management paradigms. However, onsite solutions often produce inadequate effluent quality for reuse and are ineffective in removing organic micropollutants (OMPs). This study suggests a multistep onsite system for treating wastewater in varying conditions. The system comprises biological treatment in a recirculating vertical-flow bioreactor (RVFB) followed by ozonation and ultrafiltration. The system was constructed on a farm in the Israeli Negev desert and tested year-round for its effluent quality and removal of two model OMPs. Additionally, laboratory-scale experiments were conducted to understand the field data. The system has demonstrated stable performance over varying climate conditions and wastewater qualities during one year of operation. The RVFB reduced the total suspended solid (TSS) concentration by up to 96 %, the dissolved organic carbon by up to 88 %, and the biodegradable OMP, Ibuprofen, by approximately 82 %. Ozonation had limited impact on effluent quality, most likely due to low ozone concentrations, but interestingly efficiently reduced Carbamazepine, a recalcitrant OMP, by around 87 %. Additionally, the laboratory experiments using the farm's wastewater demonstrated the ozone's potential efficiency in improving effluent quality. The final membrane filtration treatment step fully removed the residual TSS and E. coli, achieving effluent quality that meets the standards for wastewater reuse. The membrane exhibited stable performance over one month without chemical cleaning, probably due to the pre-ozonation step. Overall, this study highlights the potential of the suggested system to effectively treat diverse wastewater types and produce high-quality effluent suitable for reuse.

Application of Unconventional Tillage Systems to Maize Cultivation and Measures for Rational Use of Agricultural Lands

Maize (Zea mays L.) is one of the main agricultural crops grown worldwide under very diverse climate and soil conditions. For maize cultivation in a conventional tillage system, autumn plowing is a mandatory condition. Minimum soil tillage or no tillage has been applied in recent years, both in research and in production, for reasons relating to soil conservation and fuel economy. This paper presents the results of the research executed under pedoclimatic conditions at the Agricultural Research and Development Station Turda (ARDS Turda, Romania; chernozem soil) regarding the behavior of the maize hybrid Turda 332 cultivated in four tillage systems and two levels of fertilization during the period of 2016–2022. The following soil tillage systems were applied: a conventional tillage system (CT) and unconventional tillage systems in three variants—a minimum tillage system with a chisel (MTC), a minimum tillage system with a disk (MTD), and a no-tillage system (NT). They were applied with two levels of fertilization: basic fertilization (350 kg ha−1 NPK 16:16:16, applied at sowing) and optimized fertilization (350 kg ha−1 NPK 16:16:16 applied at sowing + 150 kg ha−1 calcium ammonium nitrate with additional fertilization in the phenophase of the maize with 6–7 leaves). The results highlight the fact that under the conditions of chernozem soils with a high clay content (41% clay content), maize does not lend itself to cultivation in MTD and NT, requiring deeper mobilization, with the yield data confirming this fact. This is because under the agrotechnical conditions for sowing carried out in MTD and NT, the seeder used (Maschio Gaspardo MT 6R) does not allow for the high-quality sowing of maize, especially under dry soil conditions. Instead, the MTC system could be an alternative to the conventional tillage system, with the yield difference being below 100 kg ha−1.

Enhanced Lotka-Volterra Equations: A Novel Approach to Investigate Plant Community Dynamics Under Varied Climatic Conditions

Amidst escalating climatic uncertainties, the adaptability of plant communities to varying drought frequencies and intensities emerges as a critical research domain. This study endeavors to decode the potential ramifications of such climatic extremities on plant community dynamics. By harnessing an augmented Lotka-Volterra model, we intricately weave in climatic variables, with a pronounced emphasis on drought indices, to forecast plant community trajectories. Our explorations divulged that specific drought scenarios significantly influence community resilience, with certain species compositions optimally enhancing community robustness. Moreover, through a judicious application of a genetic algorithm, we discerned an optimal species count that maximizes community biomass. This seminal work not only deepens our understanding of plant community dynamics under climatic vicissitudes but also paves the way for informed ecological and environmental policymaking.

A study on factors influencing Chinese farmers’ willingness to input in Jujube planting

Agriculture, the basis of a country's economic and social development, is restricted by natural climate conditions. Characteristic agriculture varies as different regions have diverse climate conditions. Due to its outstanding drought tolerance and adaptability in arid and semi-arid marginal areas and barren saline–alkali land, the jujube fruit is considered an important characteristic of agriculture in nine provinces along the Yellow River in China. It plays an important role in economic development and farmers' income; however, due to the constraints of capital, technology, price fluctuations and other aspects, farmers in these provinces are unwilling to invest in jujubes and the further development of the jujube industry is restricted. Based on this, this study selected 11 factors that may affect farmers' willingness to input in jujube as variables; the influence of these independent variables was quantitatively analysed using the survey data of 984 farmers in main producing provinces with SPSSAU software and principal component analysis method. Three principal components were extracted according to each variable's characteristic roots and variance interpretation rate, and the influencing factors were classified into three factors according to the load coefficient of these principal components. Three relevant components are agricultural incentive measures (technical training, agricultural loans, agricultural insurance and government subsidies), jujube planting input and output (average income and input cost per acre) and jujube sales status (sales difficulty and sales income trend). Furthermore, the multiple linear regression model was used to perform regression analysis on the eight key factors involved under the three categories and the results showed that R2 was 0.756, p values were all <0.01 and VIF values were all <5. The results indicated that the model was effective and verified that these eight key factors impacted farmers' willingness to plant jujubes. This study aimed to quantitatively describe each independent variable's influence on farmers' willingness to invest in jujube planting and propose corresponding incentive measures according to their influence effects. The study can provide new ideas for improving farmers' willingness to invest in jujube and a practical basis for the agricultural sector to implement accurate policies and has direct guiding significance and value for promoting the development of the jujube industry. Meanwhile, the results also have a certain reference value for the research of fruit planting input in other regions.

Real-time and modelled performance assessment and validation studies of PV modules operating in varied climatic zones

With the increasing adoption of solar energy as a sustainable power source, it is crucial to evaluate the performance of photovoltaic (PV) modules under diverse environmental conditions to ensure optimal energy production and system efficiency. Present work gives a comprehensive overview of performance assessment and validation studies conducted on different PV module technologies such as multi-crystalline silicon (mc-Si), cadmium telluride (CdTe), copper indium gallium selenide (CIGS), amorphous silicon (a-Si), heterojunction with intrinsic thin layer (HIT) and interdigitated back contact (IBC) operating under varied climatic conditions at different locations in India. To ensure accuracy and reliability, rigorous data collection and analysis methodologies were employed. The performance assessment has been computed through simulation using PVSOL software. Moreover, the performance ratio (PR) of all the PV module technologies was found to vary from 0.76 to 1.04. The present work validates the efficacy of the software as we have compared the computed results with real-time data obtained for all the PV modules, which were installed at NISE (National Institute of Solar Energy), Gurugram India. The performance ratio of all the PV module technologies has been evaluated through both the PVSOL and using real time data. The results show that the mean percentage change in PR values has been estimated approximately to be 2% in CdTe, CIGS, and a-Si modules technologies and 3% in mc-Si, HIT and IBC module technologies.

Soil Carbon Sequestration in the Age of Climate Change: A Review

Soil carbon sequestration has garnered attention as a pivotal strategy in mitigating climate change. Its relevance is accentuated by the soil's dual role in both storing carbon and supporting agriculture, thereby contributing to both environmental and food security. The purpose of this review is to analyze the various facets of soil carbon sequestration in the Indian context, specifically focusing on case studies that highlight both successes and failures in this realm. Key findings indicate that multifaceted approaches, such as agroforestry models in Tamil Nadu and community-led natural farming in Andhra Pradesh, have been effective in enhancing soil carbon stocks. These approaches are not only beneficial for carbon sequestration but also demonstrate positive implications for farm yield and biodiversity. However, the study also uncovers shortcomings in soil management practices, evident in the decline of soil carbon levels in regions such as Punjab due to monoculture and excessive fertilizer use. The consequences of such practices manifest in reduced soil fertility, emphasizing the urgent need for sustainable agricultural methods. In fragile ecosystems like the Himalayan region, soil erosion has further reduced the soil's ability to act as a carbon sink, indicating the necessity for immediate conservation efforts. These findings imply that an integrated approach, coupling agricultural innovation with policy support, can substantially improve the effectiveness of soil as a carbon sequester. Moreover, it is essential for policies to be adaptive and region-specific, accounting for the diverse geographical and climatic conditions across India. This review aims to serve as a comprehensive guide for policymakers, researchers, and agricultural practitioners, emphasizing that soil carbon sequestration is not an isolated goal but must be integrated into broader environmental and agricultural objectives.

The competitive effect of neighbouring plants on the growth of two eucalypts is stronger in dry conditions

Abstract Plant growth is influenced by interactions with neighbouring plants. The strength and direction of the cumulative neighbourhood effect on growth can depend on neighbour properties, such as their abundance, size and proximity, as well as the degree of similarity between interacting plants and their traits, which can be captured by the species identity of neighbours. Such interactions are also influenced by the local environmental conditions that are largely determined by climate. Because neighbour and climatic effects are typically explored in isolation, particularly in long‐lived species such as trees, it is unclear how the impacts of neighbours on plant growth shift in response to temporal variation in climatic conditions. Here, we explored how neighbouring plants impact the annual growth of two eucalypts, Eucalyptus delegatensis and Eucalyptus regnans, over three growing seasons in an experimental forest in south‐east Tasmania, Australia. We assessed whether eucalypt growth rates could be described by the number, size, proximity, and species identity of neighbours, and how the strength of this effect was influenced by the growing season climatic conditions. We found that climate and neighbouring plants had an interactive impact on eucalypt growth. Neighbours had a consistent, competitive effect on the growth of both eucalypts in all three growing seasons which was strongly related to the cumulative neighbourhood biomass. The identity of neighbours was important in determining E. regnans growth only, whereby distinguishing neighbours according to functional group best described growth. Over all three growing seasons, we predicted that, on average, neighbours reduced E. delegatensis and E. regnans mean annual growth by 60.5% and 48.4%, respectively. However, the strength of the competitive effect of neighbours on eucalypt growth was related to growing season climate, being strongest when conditions were hot and dry and weakest in cool, wet conditions. Synthesis: Given the consistent results observed in two co‐occurring eucalypts, our findings suggest that drier and hotter climatic conditions increase the strength of competitive effects on tree growth. This has implications for future forest productivity given projected increased temperatures and variation in rainfall patterns globally.

Investigating the Importance and Goals of Economic Fish Farming in Faryab Province

This research is about the importance and goals of fish farming in Faryab province, considering the world's population which is constantly increasing and its growth will not stop at any time, there is no doubt that the world's current food industry will not meet the needs and humans must Think about food sources for new protein sources.&#x0D; Fish is one of the most important resources for humans, especially food sources: major fishermen and people who catch fish only for a living catch these animals from the wild.&#x0D; The importance of this current research on the importance of fish farming in our Faryab, regardless of the fact that it provides part of the food rich in protein needed by our country. It is an important source of employment for unemployed people in the rural areas of Faryab province. On the other hand, Faryab Province, with its diverse climatic conditions, and abundant natural facilities, has a good background for breeding activities of freshwater and warm water fish. It can be seen that different districts of Faryab Province have a blessed sea that has prepared a colorful table for thousands of living creatures.&#x0D; The main purpose of conducting research is to obtain information about the importance and objectives of fish farming in Faryab province, and with the increase in population, the demand for aquatic products, especially fish meat, is increasing. At present, fish meat food is promoted in many restaurants in Faryab province and fish meat has a good market in this province, so in this regard, every day tens of kilos of high-quality raw fish enter Faryab province from the provinces and districts of Afghanistan. This is proof of having a good domestic market for fish meat in Faryab province.&#x0D; Fish resources are renewable resources. A large number of people in developed and developing countries are busy working in this sector. Fish breeding and hunting are one of the most beneficial jobs for the people of the world, Afghanistan, and especially the people of Faryab province. Fish meat provides approximately 14 percent of the animal protein needed by the world's population. In a number of developing countries, fish is a supplementary food component of the people's diet. Fish farming and fishing are a source of employment and foreign currency income in developed and developing countries. The necessary information about the background of this research was collected from books, articles, and authentic scientific journals, and in the findings section, the necessary information was collected using a questionnaire, and the results after analysis were included in the findings section.

Review of Sponge City implementation in China: performance and policy.

Urban flooding is a major problem for large cities around the world. Rapid urbanization in China has tremendously increased, resulting in more frequent incidences of urban flooding. In 2013, China launched a program of 30 pilot sponge cities (SPCs) to establish integrated urban stormwater management. However, today, after several years of implementation, some sponge cities still experience flooding. This study provides answers and solutions to these problems, by evaluating the overall performance of SPC in China from a systematic perspective considering the variable climatic conditions. This paper also highlights the limitations associated with implementing the current SPC. The adoption of overseas models, before adhering them to Chinese catchment properties, has generated significant uncertainty for simulation outputs and material provision challenges at various stages of the implementation process. Furthermore, hydrological connectivity between neighboring catchments has been neglected in most SPC projects. Developing local models based on local conditions and needs would address these issues and open new research windows for exploring more effective stormwater management initiatives. That includes the advancement of cost-effective evaluation studies, modern optimum efficiency design studies, and the analysis of groundwater contamination due to high infiltration rates and so on.

Comprehensive in silico analysis of the underutilized crop tef (Eragrostis tef (Zucc.) Trotter) genome reveals drought tolerance signatures

BackgroundTef (Eragrostis tef) is a C4 plant known for its tiny, nutritious, and gluten-free grains. It contains higher levels of protein, vitamins, and essential minerals like calcium (Ca), iron (Fe), copper (Cu), and zinc (Zn) than common cereals. Tef is cultivated in diverse ecological zones under diverse climatic conditions. Studies have shown that tef has great diversity in withstanding environmental challenges such as drought. Drought is a major abiotic stress severely affecting crop productivity and becoming a bottleneck to global food security. Here, we used in silico-based functional genomic analysis to identify drought-responsive genes in tef and validated their expression using quantitative RT-PCR.ResultsWe identified about 729 drought-responsive genes so far reported in six crop plants, including rice, wheat, maize, barley, sorghum, pearl millet, and the model plant Arabidopsis, and reported 20 genes having high-level of GO terms related to drought, and significantly enriched in several biological and molecular function categories. These genes were found to play diverse roles, including water and fluid transport, resistance to high salt, cold, and drought stress, abscisic acid (ABA) signaling, de novo DNA methylation, and transcriptional regulation in tef and other crops. Our analysis revealed substantial differences in the conserved domains of some tef genes from well-studied rice orthologs. We further analyzed the expression of sixteen tef orthologs using quantitative RT-PCR in response to PEG-induced osmotic stress.ConclusionsThe findings showed differential regulation of some drought-responsive genes in shoots, roots, or both tissues. Hence, the genes identified in this study may be promising candidates for trait improvement in crops via transgenic or gene-editing technologies.

Assessment of Public Perception and Awareness on Water Management Practices in Maharashtra

Water management in Maharashtra faces complex challenges due to its varied climatic conditions and diverse population. This research aims to fill a critical gap by assessing public perception and awareness regarding existing water management practices in both urban and rural areas of the state. Through a survey-based methodology, the study explores the public's understanding of water scarcity, policy effectiveness, and their roles in sustainable water management. The findings indicate a significant disparity in awareness levels between rural and urban communities and offer insights into the public's willingness to engage in water-saving behaviors. These results have important implications for policymakers, suggesting a need for targeted educational and awareness campaigns. By understanding public perception and awareness, this study hopes to contribute to the development of more effective, community-oriented water management strategies in Maharashtra.

Prevention of psoroptosis of sheep in Dagestan Republic in winter

Relevance. Sheep breeding in Dagestan has its own distinctive features compared to other regions, territories and republics of our country. They are associated with extremely diverse natural and climatic conditions of various geographical zones of the republic. Currently, preventive measures against psoroptosis of sheep and goats in the Caspian region of Russia are carried out by practitioners and workers of farms of various forms of ownership using outdated acaricidal agents of past generations. The main peak of psoroptosis of sheep in the Republic of Dagestan falls on the autumn-spring period — from November to mid-December and from March to May. At this time, bathing activities are not possible, the injection method is not always convenient, especially taking into account pregnant queens and young animals, spraying is ineffective and carries the risk of hypothermia of animals. It follows from the above that the search for acaricidal agents capable of preventing psoroptosis of sheep in winter on the territory of the Caspian region of Russia is of great scientific and practical importance.Results. The experimental data obtained allow us to conclude that the preventive use of the acaricidal agent Delcid 7.5 in a dosage of 10 ml per 50 kg of live weight provides protection against Psoroptes ovis for up to 23 days, Sanofly — up to 18, which is 5 days less. Delcid 7.5 turned out to be 10% more effective in acaricidal action, as well as in the number of new lesions on average per animal with an indicator of 1, whereas after Sanoflaya, this indicator reached 2 after 23 days of the experiment. The reasons for the results obtained are various main active substances and their acaricidal effect against the Psoroptes ovis tick, in Delcid 7.5 it is deltametrin, in Sanoflaya it is cyflutrin.

Plant functional traits are dynamic predictors of ecosystem functioning in variable environments

Abstract A central goal at the interface of ecology and conservation is understanding how the relationship between biodiversity and ecosystem function (B–EF) will shift with changing climate. Despite recent theoretical advances, studies which examine temporal variation in the functional traits and mechanisms (mass ratio effects and niche complementarity effects) that underpin the B–EF relationship are lacking. Here, we use 13 years of data on plant species composition, plant traits, local‐scale abiotic variables, above‐ground net primary productivity (ANPP), and climate from the alpine tundra of Colorado (USA) to investigate temporal dynamics in the B–EF relationship. To assess how changing climatic conditions may alter the B–EF relationship, we built structural equation models (SEMs) for 11 traits across 13 years and evaluated the power of different trait SEMs to predict ANPP, as well as the relative contributions of mass ratio effects (community‐weighted mean trait values; CWM), niche complementarity effects (functional dispersion; FDis) and local abiotic variables. Additionally, we coupled linear mixed effects models with Multimodel inference methods to assess how inclusion of trait–climate interactions might improve our ability to predict ANPP through time. In every year, at least one SEM exhibited good fit, explaining between 19.6% and 57.2% of the variation in ANPP. However, the identity of the trait which best explained ANPP changed depending on winter precipitation, with leaf area, plant height and foliar nitrogen isotope content (δ15N) SEMs performing best in high, middle and low precipitation years, respectively. Regardless of trait identity, CWMs exerted a stronger influence on ANPP than FDis and total biotic effects were always greater than total abiotic effects. Multimodel inference reinforced the results of SEM analysis, with the inclusion of climate–trait interactions marginally improving our ability to predict ANPP through time. Synthesis. Our results suggest that temporal variation in climatic conditions influences which traits, mechanisms and abiotic variables were most responsible for driving the B–EF relationship. Importantly, our findings suggest that future research should consider temporal variability in the B–EF relationship, particularly how the predictive power of individual functional traits and abiotic variables may fluctuate as conditions shift due to climate change.

Rhizobiome of ‘Ōhi‘a Lehua (Metrosideros polymorpha) Offers Insight into Plant-Microbe-Invertebrate Interactions in the Subsurface

Roots are common features in basaltic lava tube caves on the island of Hawai‘i. For the past 50 years, new species of cave-adapted invertebrates, including cixiid planthoppers, crickets, thread-legged bugs, and spiders, have been discovered from root patches in lava tubes on different volcanoes and across variable climatic conditions. Assessing vegetation on the surface above lava tube passages, as well as genetic characterization of roots from within lava tubes, suggest that most roots belong to the native pioneer tree, ‘ōhi‘a lehua (Metrosideros polymorpha). Planthoppers are the primary consumers of sap at the base of the subsurface food web. However, root physicochemistry and rhizobiome microbial diversity and functional potential have received little attention. This study focuses on characterizing the ‘ōhi‘a rhizobiome, accessed from free-hanging roots inside lava tubes. Using these results, we can begin to evaluate the development and evolution of plant-microbe-invertebrate relationships. We explored lava tubes formed in flows of differing elevations and ages, from about 140 to 3000 years old, on Mauna Loa, Kīlauea, and Hualālai volcanoes on Hawai‘i Island. Invertebrate diversity was evaluated from root galleries and non-root galleries, in situ fluid physicochemistry was measured, and root and bare rock fluids (e.g., water, sap) were collected to determine major ion concentrations, as well as non-purgeable organic carbon (NPOC) and total nitrogen (TN) content. To verify root identity, DNA was extracted, and three sets of primers were used. After screening for only Metrosideros spp., the V4 region of the 16S rRNA gene was sequenced and taxonomy was assigned. Root fluids were viscous and ranged in color from clear to yellow to reddish orange. Root fluids had 2X to 10X higher major ion concentrations compared to rock water. The average root NPOC and TN concentrations were 192 mg/L and 5.2 mg/L, respectively, compared to rock water that had concentrations of 6.8 mg/L and 1.8 mg/L, respectively. Fluids from almost 300 root samples had pH values that ranged from 2.2 to 5.6 (average pH 4.63) and were lower than rock water (average pH 6.39). Root fluid pH was comparable to soil pH from montane wet forests dominated by ‘ōhi‘a (Selmants et al. 2016), which can grow in infertile soil with pH values as low as 3.6. On Hawai‘i, rain water pH averages 5.2 at sea level and systematically decreases with elevation to pH 4.3 at 2500 m (Miller and Yoshinaga 2012), but root fluid pH did not correlate with elevation, temperature, relative humidity, inorganic and organic constituents, or age of flow. Root fluid acidity is likely due to concentrated organic compounds, sourced as root exudates, and this habitat is acidic for the associated invertebrates. From 62 root samples, over 66% were identified to the genus Metrosideros. A few other identifications of roots from lava tube systems where there had been extensive clear-cutting and ranching included monkey pod tree, coconut palm, Ficus spp., and silky oak. The 16S rRNA gene sequence surveys revealed that root bacterial communities were dominated by few groups, including Burkholderiaceae, as well as Acetobacteraceae, Sphingomonadaceae, Acidobacteriaceae, Gemmataceae, Xanthobacteraceae, and Chitinophagaceae. However, most of the reads could not be classified to a specific genus, which suggested that the rhizobiome harbor novel diversity. Diversity was higher from wetter climates. The root communities were distinct from those described previously from ‘ōhi‘a flowers and leaves (Junker and Keller 2015) and lava tube rocky surfaces (Hathaway et al. 2014) where microbial groups were specifically presumed capable of heterotrophy, methanotrophy, diazotrophy, and nitrification. Less can be inferred for the rhizobiome metabolism, although most taxa are likely aerobic heterotrophs. Within the Burkholderiaceae, there were high relative abundances of sequences affiliated with the genus Paraburkholderia, which includes known plant symbionts, as well as the acidophilic genera Acidocella and Acidisoma from the Acetobacteraceae, which were retrieved predominately from caves in the oldest lava flows that also had the lowest root pH values. It is likely that the bacterial groups are capable of degrading exudates and providing nutritional substrates for invertebrate consumers that are not provided by root fluids (i.e., phloem) alone. As details about the biochemistry of ‘ōhi‘a have been missing, characterizing the rhizobiome from lava tubes will help to better understand potential plant-microbe-invertebrate interactions and ecological and evolutionary relationships through time. In particular, the microbial rhizobiome may produce compounds used by invertebrates nutritionally or that affect their behavior, and changes to the rhizobiome in response to environmental conditions may influence invertebrate interactions with the roots, which could be important to combat climate change effects or invasive species introductions.

Machine learning approaches for real-time forecasting of solar still distillate output

Solar stills provide a promising avenue for freshwater production in regions grappling with water scarcity, especially remote locales. However, their efficiency is often constrained by the variable climatic conditions. Conventional prediction methods fall short in consistently forecasting the yield, leaving a significant gap in optimizing solar still operations. Recognizing this, the introduction of machine learning becomes pivotal. With a robust predictive model, operators can avoid inefficiencies, inconsistent outputs, and sub-optimal resource utilization. The primary objective of this research is to determine the most suitable machine learning model tailored for predicting solar still output under specific environmental conditions. This research work assessed various machine learning models, including linear regression, decision trees, random forest, support vector machines, and multilayer perceptron. Evaluation metrics encompassed Mean Absolute Error (MAE), cross-validation, grid search, and randomized search techniques. Our results identified the Decision Tree model, registering a MAE of 5.43 and 5.74 through random and grid search methods, respectively, as the preeminent predictor for our dataset. This machine learning-centric methodology elevates the precision of solar still output predictions and paves the way for enhanced solar still designs and superior optimization of solar energy conversion mechanisms.

Prevalence and diversity of ascarid and strongylid nematodes in Australian Thoroughbred horses using next-generation sequencing and bioinformatic tools

The study presents the results of a cross-sectional survey to describe the epidemiology of ascarid and strongylid nematodes in horses, the impact of diverse climatic conditions on parasite diversity and the levels of faecal egg shedding in different age groups of managed Thoroughbred horses. Individual faecal samples (n = 1377) collected from 62 Thoroughbred farms across four climatic zones in Australia were analysed using the modified McMaster technique for faecal egg counts (FECs) and strongylid nematodes were identified utilising PCR-directed next-generation sequencing (NGS) of the second internal transcribed spacer of the nuclear ribosomal DNA (ITS-2). Across all age groups, the prevalence of ascarid and strongylid nematodes was 12% (95% confidence interval 10–14%) and 72% (70–74%), respectively. Based on strongylid FECs, yearlings had the highest prevalence (89%) followed by weanlings (83%), foals (79%), wet mares (61%), dry mares (59%) and stallions (54%). However, for Parascaris spp., foals had the highest prevalence (46%) followed by weanlings (32%) and yearlings (13%). The highest mean FECs for Parascaris spp. were observed in foals (418 eggs per gram [EPG] of faeces) while those for strongylids were in yearlings (1002 EPG). Of the adult horses (mares and stallions), 67% (489 of 729) and 11% (77 of 729) were low (i.e., ≤250 EPG) and moderate (i.e., 251–500 EPG) strongylid egg-shedders, respectively. Strongylid egg shedding varied across climatic zones, with the highest mean FECs in the summer rainfall (723 EPG) followed by non-seasonal rainfall (629 EPG), winter rainfall (613 EPG), and Mediterranean (606 EPG) rainfall zones. Twenty-three nematode species were detected using NGS, with Cylicostephanus longibursatus (28%), Cylicocyclus nassatus (23%) and Coronocyclus coronatus (23%), being the most abundant species. Three species of Strongylus (i.e., S. vulgaris, S. equinus and S. edentatus) were also detected. The nemabiome composition, species richness and relative abundance varied within horse age and between climatic zones. These empirical findings provide a comprehensive understanding of the prevalence of parasites within horse populations and the multifaceted factors that influence their occurrence, thereby allowing for the formulation of tailored strategies aimed at parasite control in domestic horses.

A method to derive satellite-based extreme precipitation return levels in poorly gauged areas

Precipitation frequency analysis based on satellite products is still limited by estimation errors and by the use of statistical methods inadequate for these products. However, when it comes to poorly gauged areas of the world, satellite products can be a vital source of information. We present here a new method to derive satellite-based estimates of extreme precipitation quantiles with long return period in poorly gauged areas. The method relies on the identification of relations between statistics of the satellite estimation error and errors in the parameters of a non-asymptotic extreme value distribution. We show an application of the method in three areas with diverse climatic conditions in Austria and in the South-eastern Mediterranean, showcasing results for different scenarios of rain gauge density. We find that simple linear relations can explain 35–90% of the variance in the error of the parameters of the non-asymptotic extreme value distribution. Using these relations, we derive estimates of extreme return levels with drastically reduced bias and dispersion with respect to the ones directly obtained from the satellite estimates.

Solar-off-grid atmospheric water harvesting system: Performance analysis and evaluation in diverse climate conditions

Global warming, climate change, and conflicts have collectively exacerbated the pressing issue of water scarcity on a global scale. Addressing this critical challenge and ensuring equitable access to water for all necessitates a heightened commitment and the introduction of groundbreaking initiatives. In light of the growing global awareness surrounding this issue, this study introduces an innovative, grid-independent, solar-powered approach to atmospheric water harvesting. The simulations yield valuable insights that can serve as a foundation for further investigations by fellow researchers. Central to this study is the exploration and examination of the influence of dew point temperature, a pivotal factor in condensing atmospheric water, as it shapes the water collection process. The credibility of the results is reinforced through meticulous cross-referencing with existing literature, following extensive exploration and analysis of various parameters. The study's adaptability is put to the test across three distinct climatic locations: a coastal, a typical, and a desert environment. In desert conditions, the system achieves an average daily water collection of 45 l, while in coastal climates, this figure escalates to an impressive 100 ll per day. Remarkably, July emerges as the most prolific month for water collection across all simulated regions. To comprehensively evaluate the system's efficiency in capturing water vapor, a comparative analysis is conducted against alternative designs. The proposed approach excels in terms of water harvested per kilowatt of energy consumed, boasting values of 3.248 kg/kWh, 2.689 kg/kWh, and 1.871 kg/kWh for coastal, typical, and desert regions, respectively. Notably, the coastal area stands out as the most effective, owing to its consistently hot and humid climate. With similar meteorological conditions in place, this system holds the potential for global replication, facilitating the collection of water volumes comparable to those observed in coastal regions.