Changes In Weather Patterns Research Articles

Estimating the change in the rational runoff coefficient through history in Jefferson County, Texas

Jefferson County in Texas has experienced devastating storms in recent years resulting in billions of dollars in damages. The county has gone through temporal milestones in terms of population growth and industrial development. Many studies have shown that urban development increases the risk of flooding by decreasing the soil infiltration capacity. The current study focuses on estimating the extent to which the urban development in the county has led to increased imperviousness using a combination of historical and current spatial data. Rational runoff coefficients of the County were estimated and compared at three different times over a span of 120 years. A land survey map for 1898, an aerial imagery map for 1966 and a land parcel map for 2019 were obtained from various sources. The three maps available, each in different format, were analyzed to determine the land use and land cover type for the respective years. The runoff coefficient increased by 21% from 1898 to 1966 and remained the same from 1966 till 2019. The estimates are in correlation with industrial and population growth patterns of the county. These preliminary spatial analyses are useful in estimating the contributions of recent major flooding from overall development, or if they may be more impacted from other factors such as changes in weather patterns.

Rate-induced tipping to metastable Zombie fires

Zombie firesin peatlands disappear from the surface, smoulder underground during the winter, and ‘come back to life’ in the spring. They can release hundreds of megatonnes of carbon into the atmosphere per year and are believed to be caused by surface wildfires. Here, we propose rate-induced tipping (R-tipping) to a subsurface hot metastable state in bioactive peat soils as a main cause of Zombie fires. Our hypothesis is based on a conceptual soil-carbon model subjected to realistic changes in weather and climate patterns, including global warming scenarios and summer heatwaves. Mathematically speaking, R-tipping to the hot metastable state is a genuine nonautonomous instability, due to crossing an elusive quasi-threshold, in a multiple-timescale dynamical system. To explain this instability, we provide a framework combining a special compactification technique with concepts from geometric singular perturbation theory. This framework allows us to reduce an R-tipping problem due to crossing a quasi-threshold to a heteroclinic orbit problem in a singular limit. We identify generic cases of tracking–tipping transitions via: (i) unfolding of a codimension-twoheteroclinic folded-saddle-node type-I singularityfor global warming and (ii) analysis of a codimension-onesaddle-to-saddle hetroclinic orbitfor summer heatwaves, in turn revealing new types of excitability quasi-thresholds.

Improving local adaptive capacity to mitigate the negative impact of climate change: A case study of Tram Kak District, Takeo Province

Climate change is a long-term change in temperature and weather patterns. Drought is one of the two major natural disasters in Cambodia. The study aims to better understand the negative impact of climate change on the rice production of small-scale farmers in two communes in Tram Kak district, Takeo province, by focusing on droughts or water shortages. It was found that (i) the small-scale farmers of Sraeronorng commune mostly cultivated late-cycle rice, and the harvest was completed later than small-scale farmers in the Nhaenghorng commune, and (ii) the impact of drought over a decade affected small-scale farmers in the Nhaenghorng commune more than the Sraeronorng commune, except in 2021 when the impact on rice production in the two communes was similarly high. If a drought or water shortage came, most small-scale farmers would have a dispute over access to water from canals or community ponds to irrigate their rice fields. However, (iii) the small-scale farmers were found to have a high adaptive capacity to droughts or water shortages. The study also found that most small-scale farmers tried to construct their water sources to supply their agricultural cultivation, such as digging their ponds. However, these water sources can only provide small amounts of irrigation to reduce rice damage in the event of a long-term drought or water shortage. In addition, it was very important that all key stakeholders, both at the national and local levels, take more action to ensure the resilience of rural communities. These actions should focus on developing high-quality irrigation systems, training on agricultural techniques, selling drought-resistant rice seeds at a low price, and strengthening small-scale farmers’ capacity to produce their quality seeds. Local development projects must include planning and participation of community members.

A tactical planning model for fresh produce production considering productive potential and changing weather patterns

A tactical planning model for fresh produce production considering productive potential and changing weather patterns

AI Based Real-Time Weather Condition Prediction with Optimized Agricultural Resources

Purpose: Unpredictable and rapid change in weather patterns has great impact on agricultural activities, especially for precision agriculture that results in worsened water resources availability, decreased soil fertility, use of pesticide as well as decreased yield productivity. In attempt to alleviate these challenges, this study aims at developing a real-time weather and farm field data driven Artificial Intelligence (AI) and Internet of Things (IoT) system that analyze, manage and schedule irrigation and fertigation as well as enabling farmers to interact with their farms via Smart phone or PCs to optimize energy and water resources.
 Methodology: The system employs weather condition monitoring sensors such as atmospheric pressure, air temperature, air humidity and wind speed for collecting real-time farm field data and uses Fuzzy Inference System (FIS) to predict rainfall rate at farm area for 24 hours period. The system also gathers field data such as soil moisture content and soil nutrient content and uses the Machine Learning (ML) algorithms to predict the time for irrigation and fertigation. By combining weather and farm field data, the system schedules the irrigation and fertigation activity. In addition, the mobile application is developed for the farmers to interact, control and monitor the farming activities and the data is presented to the farmers in both graphical and numerical formats.
 Findings: The system prototype deployed and tested in the two hectors Maize farm proved that 55% of water, 51% of energy and 20% of fertilizer were saved as well as increases in 20% of Maize yield production compared to previous season.
 Recommendations: Since the current irrigation and fertigation practices are based on predetermined time of the day and threshold values for automatic irrigation, this solution introduced the new concept of real-time and short-term weather forecasting that enables farmers to balance the irrigation period and weather pattern for water and fertilizer resources optimization.

Genetics of a diverse soft winter wheat population for pre-harvest sprouting, agronomic, and flour quality traits.

Soft winter wheat has been adapted to the north-central, north-western, and south-central United States over hundreds of years for optimal yield, height, heading date, and pathogen and pest resistance. Environmental factors like weather affect abiotic traits such as pre-harvest sprouting resistance. However, pre-harvest sprouting has rarely been a target for breeding. Owing to changing weather patterns from climate change, pre-harvest sprouting resistance is needed to prevent significant crop losses not only in the United States, but worldwide. Twenty-two traits including age of breeding line as well as agronomic, flour quality, and pre-harvest sprouting traits were studied in a population of 188 lines representing genetic diversity over 200 years of soft winter wheat breeding. Some traits were correlated with one another by principal components analysis and Pearson's correlations. A genome-wide association study using 1,978 markers uncovered a total of 102 regions encompassing 226 quantitative trait nucleotides. Twenty-six regions overlapped multiple traits with common significant markers. Many of these traits were also found to be correlated by Pearson's correlation and principal components analyses. Most pre-harvest sprouting regions were not co-located with agronomic traits and thus useful for crop improvement against climate change without affecting crop performance. Six different genome-wide association statistical models (GLM, MLM, MLMM, FarmCPU, BLINK, and SUPER) were utilized to search for reasonable models to analyze soft winter wheat populations with increased markers and/or breeding lines going forward. Some flour quality and agronomic traits seem to have been selected over time, but not pre-harvest sprouting. It appears possible to select for pre-harvest sprouting resistance without impacting flour quality or the agronomic value of soft winter wheat.

Climate change and community psychology: exploring environmental and wider social challenges

Climate and ecological emergencies are already adversely affecting individuals and com-munities globally. In this UK based study, both academics and young people contributed ex-amples of environmental and wider social challenges. The final lists capture many varied ex-amples reflecting both climate change (e.g., changing weather patterns) and wider ecological emergencies (e.g., biodiversity loss; pollution). The wider social challenges list captures other important issues (e.g., poverty, inequality). The paper reminds us both that the climate and ecological emergencies contain more than just climate change alone and that individuals and communities face pressing wider social challenges that may limit their ability to focus on cli-mate change. The discussion highlights the potential role of critical consciousness and the im-portance of focusing at macro levels of change.

Fresh Water availability and Its Global challenge

Water is prime natural resources fulfilling our needs in a precisious assets.we must acts to preserve and utilize every drop of water.water resources can be assessed on the basis of surface and subsurface water bodies.Climate change impact on ground Water the impact of climate change on ground water has been studied much less than the impact on surface waters. Ground water reacts to climate change mainly due to change in ground water recharge,but also change in river level in response to increase in mean Temperature,precipitation ,variability and sea level as mean precipitations.Changing land use pattern due to increasing ,urbanization, industrialization and agriculture activities are serious issues that causing increase ground water with drawal resulting in depletion of ground water resources and mining of ground water resources,along with deterioration of water quality.Rainfall is highly irregular and erratic and declining year to year due to change climatic conditions as result of serious deforestation global warming etc.Human health is affected by change in biodiversity and ecosystem.Climate change will affect the quality of drinking water and impact of fresh water availability and impact on public health. About 70% of Earth’s surface is water of which 97.5% is salty water and 2.5% is fresh water. Less than 1% of this 2.5% amount of freshwater is accessible. As sea water rise’s , salt water of ocean in filtrate as coastal fresh water due heavy rainfall and flooding waste more fertilizer and municipal sewage mixed with costal fresh water and change alter into more oxygen dead zone. Weather extreme and climate variability is main driver of food production in recent global challenge. Recent global challenge food security, fresh water availability, increase incidence of extreme high sea level. Loss of agriculture reproduction and increase in food prices and changes in weather patterns and alter availability and quality of water in many part of world. Climate change is an on-going phenomenon. This will inevitably bring about numerous environmental problems, including alterations to the hydrological cycle, which is already heavily influenced by anthropogenic activity.Chemical fertlizer’s has been adversely affecting the flora, fauna as well as soil quality . more ever every year plant pathogen are causing loss of 10 to 20% of agricultural production worldwide. Ground water will be vital to alleviate some of the worst drought situations. flooding and contaiminated water supplies, more intense weather events are likely to increase to risk of infectious disease epidemics and erosion of low-lying and costal land. Climate Chang will affect the quality of drinking Water and impact of fresh water availlablity and impact on public health it’s better to use UV Water purifiers.This paper will explore what climate change. Water is prime natural resources fulfilling our needs in a precisious assets.we must acts to preserve and utilize every drop of water.water resources can be assessed on the basis of surface and subsurface water bodies.Climate change imapact on ground Water the impact of climate change on ground water has been studied much less than the impact on surface waters. Ground water reacts to climate change mainly due to change in ground water recharge,but also change in river level in response to increase in mean Temperature,precipitation ,variability and sea level as mean precipitations.Changing land use pattern due to increasing ,urbanization, industrialization and agriculture activities are serious issues that causing increase ground water with drawal resulting in depletion of ground water resources and mining of ground water resources,along with deterioration of water quality.Rainfall is highly irregular and erratic and declining year to year due to change climatic conditions as result of serious global warming .Impacts of sea level rise on salinity intrusion global climate change has resulted in gradual sea level rise. sea level rise can cause saline water to migrate up stream in estuaries and rivers,thereby threating fresh water habitat and drinking- water supplies.Hydrology all the costal margin; fresh ground water flowing in land areas meets with saline ground water from the ocean. the fresh ground water flows from in land areas towards the coast where elevation and groundwater level are lower because salt water has higher content of dissolved salt and minerals. it denser the fresh water,causing it to have hydraulic head than freshwater. hydraulic head refers to the liquid pressure exerted by water column. the higher pressure density of salt water causes it to move into costal aquifiers in a a wedge shape under the freshwater. the salt water and fresh water meets in a transition zone where mixing occurs through dispersion and diffusion.

Synoptic Weather Patterns and Atmospheric Circulation Types of PM2.5 Pollution Periods in the Beijing-Tianjin-Hebei Region

The variation of PM2.5 concentration in the atmosphere is closely related to the variation in weather patterns. The change in weather pattern is accompanied by the corresponding change in atmospheric circulation characteristics. It is necessary to explore the relationship between PM2.5 concentration changes and atmospheric circulation characteristics during pollution periods. In this paper, Lamb-Jenkinson objective classification method is applied to classify daily atmospheric circulation. The pollution periods are calculated and the atmospheric circulation variation rule is obtained. Combined with the physical parameter field (humidity, potential temperature, and potential height), a typical pollution period is analyzed. Additionally, the influence of atmospheric circulation type variation on PM2.5 concentration and transport channel during the pollution period was obtained. The results show that atmospheric circulation types in the study period are dominated by A-type (anticyclonic), N-type (north), and NE-type (northeast), indicating obvious seasonal differences, and the proportion of C-type (cyclonic) circulation was increased significantly in summer. During the pollution period analysis from 2 to 4 January 2019, atmospheric circulation type changed from N-type to NE-type (northeast), the wind direction changed from southeast wind, and the change of pressure gradient was consistent with the trend of the wind field. Moreover, the physical parameter field assisted in verifying the process of the pollution period from the conducive to the accumulation of PM2.5 to conducive to the deposition of pollutants and external transport. The research results would provide theoretical support for PM2.5 prediction during the pollution period and also supply a theoretical and technical basis for the establishment of ecological compensation standards for air pollution and atmospheric environmental control.

Spatiotemporal Precipitation Trends and Associated Large-Scale Teleconnections in Northern Pakistan

The effects of climate change are unparalleled in magnitude, ranging from changing weather patterns that endanger food production to increasing sea levels that increase the likelihood of catastrophic flooding. Therefore, determining the extent of such variations on regional and local scales is imperative. We used monthly precipitation data from 25 meteorological stations in northern Pakistan (NP) to document the observed changes in seasonal and annual precipitation. The station density in the NP is small and unevenly distributed; therefore, ERA-5 reanalysis data were used to supplement the observed dataset to assess the spatial trends in NP. The non-parametric Mann–Kendall (MK), Sen’s Slope estimator (SSE), and Sequential Mann–Kendall (SQMK) tests were performed to assess the trends. In addition, the wavelet analysis technique was used to determine the association of precipitation with various oceanic indices from 1960 to 2016. Results indicate that maximum precipitation was shown in the annual and summer seasons. In NP, annual, winter, spring, and summer precipitation declined, while an increase in autumn was observed at a rate of 0.43 mm/decade between 1989 and 2016. The spatial trends for observed and ERA-5 reanalysis datasets were almost similar in winter, spring, and autumn; however, some disagreement was observed in both datasets in the summer and annual precipitation trends in NP during 1960–2016. Between 1989 and 2016, summer and annual precipitation increased significantly in Region III. However, seasonal and annual precipitation decreased in NP between 1960 and 2016. Moreover, there were no prominent trends in annual precipitation until the mid-1980s, but an apparent increase from 1985 onwards. Annual precipitation increased in all elevations except at the 500–1000 m zone. The ENSO (El Niño–Southern Oscillation) shared notable interannual coherences among all indices above 16–64 months. Inter-decadal coherence with the ENSO, AO (Arctic Oscillation), and PDO (Pacific Decadal Oscillation) in NP for 128 months and above. Generally, AO, AMO (Atlantic Multidecadal Oscillation), and NAO (North Atlantic Oscillation) exhibited less coherence with precipitation in NP. The regression of seasonal and annual precipitation revealed that winter and spring precipitation levels had higher linear regression with the AO and ENSO, respectively, while both the AO and ENSO also dominated at the annual scale. Similarly, the IOD and PDO indices had a higher influence in summer precipitation. The findings may help water resource managers and climate researchers develop a contingency plan for better water resource management policies in the face of changing climate change in Pakistan, particularly in NP.

Plant Disease Detection and Classification: A Systematic Literature Review

A significant majority of the population in India makes their living through agriculture. Different illnesses that develop due to changing weather patterns and are caused by pathogenic organisms impact the yields of diverse plant species. The present article analyzed some of the existing techniques in terms of data sources, pre-processing techniques, feature extraction techniques, data augmentation techniques, models utilized for detecting and classifying diseases that affect the plant, how the quality of images was enhanced, how overfitting of the model was reduced, and accuracy. The research papers for this study were selected using various keywords from peer-reviewed publications from various databases published between 2010 and 2022. A total of 182 papers were identified and reviewed for their direct relevance to plant disease detection and classification, of which 75 papers were selected for this review after exclusion based on the title, abstract, conclusion, and full text. Researchers will find this work to be a useful resource in recognizing the potential of various existing techniques through data-driven approaches while identifying plant diseases by enhancing system performance and accuracy.

The Impact of Increasing Forest Loss Areas on the Global Temperature, and Tourism Industry

This paper aims to investigate the relationship between deforestation, climate change, and the tourism industry, and to explore the potential impacts of decreasing forest areas on these phenomena. The background of the study is that deforestation has become a major environmental problem in many parts of the world, with significant consequences for the global climate and natural ecosystems. Climate change, in turn, has a range of impacts on human societies, including changes in weather patterns, rising sea levels, and altered ecosystems.
 The study found that decreasing forest areas have a significant impact on increasing global temperatures, as forests play a critical role in absorbing and storing carbon dioxide, one of the main greenhouse gases responsible for climate change. As a result, deforestation contributes to the release of carbon dioxide into the atmosphere, which contributes to global warming. The study also highlighted the impact of climate change on the tourism industry, which can alter weather patterns and affect the availability of natural attractions.
 In terms of concrete values, the study provides specific data on the forest area and the annual change in forest area for six countries, including Brazil, Indonesia, the Democratic Republic of Congo, Peru, Thailand, and Costa Rica. The study also provides data on the average annual temperature increase from 1990 to 2019 for these countries, as well as international tourist arrivals in 2019.
 The study further emphasizes the role of sustainable forest management and eco-tourism in mitigating the negative impacts of deforestation on the tourism industry. This includes promoting responsible tourism practices, such as minimizing environmental impacts, supporting local communities, and conserving natural resources. Overall, the study provides valuable insights into the complex relationship between forest conservation, climate change, and the tourism industry, and highlights the importance of sustainable practices for the long-term viability of both the natural environment and the tourism sector.

RaspberrySet: Dataset of Annotated Raspberry Images for Object Detection

The RaspberrySet dataset is a valuable resource for those working in the field of agriculture, particularly in the selection and breeding of ecologically adaptable berry cultivars. This is because long-term changes in temperature and weather patterns have made it increasingly important for crops to be able to adapt to their environment. To assess the suitability of different cultivars or to make yield predictions, it is necessary to describe and evaluate berries’ characteristics at various growth stages. This process is typically carried out visually, but it can be time-consuming and labor-intensive, requiring significant expert knowledge. The RaspberrySet dataset was created to assist with this process, and it includes images of raspberry berries at five different stages of development. These stages are flower buds, flowers, unripe berries, and ripe berries. All these stages of raspberry images classified buds, damaged buds, flowers, unripe berries, and ripe berries and were annotated using ground truth ROI and presented in YOLO format. The dataset includes 2039 high-resolution RGB images, with a total of 46,659 annotations provided by experts using Label Studio software (1.7.1). The images were taken in various weather conditions, at different times of the day, and from different angles, and they include fully visible buds, flowers, berries, and partially obscured buds. This dataset is intended to improve the efficiency of berry breeding and yield estimation and to identify the raspberry phenotype more accurately. It may also be useful for breeding other fruit crops, as it allows for the reliable detection and phenotyping of yield components at different stages of development. By providing a homogenized dataset of images taken on-site at the Institute of Horticulture in Dobele, Latvia, the RaspberrySet dataset offers a valuable resource for those working in horticulture.

Smallholder Farmers’ Coping Strategies to Perceived Climate Change and Variability in Isingiro District, South Western Uganda

Climate change and variability pose a major challenge facing the agricultural sector around the world and trends are feared to intensify by 2050. This is likely to complicate agricultural decisions affecting local communities who depend on the sector for their livelihood. Seasonal changes in weather patterns are projected to reduce food production due to the reduction in average yields of common food crops. With the majority of smallholder farmers in Uganda depending on agriculture for survival, building their adaptive capacity to climate change is vital to ensure household food and income security. This study aimed at establishing the smallholder farmers’ perceptions of climate change and their initiatives to cope with and manage the associated risks. A sample of 126 farming households were randomly selected from three Sub counties in Isingiro District and studied using field observations and questionnaires. Key informant interviews were also conducted with three extension workers. The collected data was analysed using Stata 14 and Excel. The findings revealed that there was increasing awareness of the climate change and variability challenge among smallholder farmers with the increasing need to take on adaptation strategies. The results showed that the major perceived changes were, increased intensity and frequency of droughts (98%), increase in daytime temperatures (92.7%), decrease in rainfall intensity (92.1%) and changes in rainfall distribution patterns (90%). It also showed that different initiatives had been taken by farmers to cope with the changes like changing planting dates (92.1%), growing crop variety mixtures (73.8%) and practising soil and water conservation (62.7%). Based on the findings of this study, smallholder farmers greatly perceived climate change and variability with negative impacts imposed on their farming operations. Although farmers have tried to adapt, there is still a need to support their coping strategies through appropriate policies. This will facilitate increased adoption of adaptation measures, thereby reducing the negative consequences of climate change in future

11 Impact of a Cache Valley Fever Outbreak on Lambing Performance in a Landrace Hair Sheep Flock: A Case Study

Abstract Cache Valley Fever (CVF) is a mosquito-born, viral disease endemic to North America. While generally not associated with clinical symptoms in ewes, it affects fetal development during the first trimester of pregnancy resulting in malformations and pregnancy loss. A suspected outbreak of CVF was recorded in a flock of Barbados Blackbelly and St. Croix hair sheep managed under an 8-mo, accelerated mating system with ewes bred in March, July and November. The outbreak was associated with a July breeding, in a summer with unusually high rainfall and standing water in pastures. There had been no previous occurrence of CVF or other abortion storms in the flock (20+ years). Lambing outcome associated with the suspected outbreak of CVF was compared with that of the three prior July matings (CON). Ewes (n = 32-35) were managed in a pasture-based system under rotational grazing. Ewes were mated in two single sire groups of 16 to 18 ewes to like-breed sires each breeding season. Pregnancy was determined by transrectal ultrasound at end and 21 d after the 25-day breeding season. Ewes lambed on pasture, and lambs were tagged, and birth weights recorded within 24 hours. Blood samples were collected from all ewes following the CVF lambing and submitted for CVF antibody testing. All ewes showed CVF antibody titers. Pregnancy rate for the CVF lambing was not different from CON (85.7 vs. 89.8%; P = 0.512), whereas lambing rate was less in CVF for both ewes exposed (74.3 vs. 88.8%; P = 0.039) and ewes lambing (86.7 vs. 98.9%; P = 0.004). Incidence of stillborn and neonatal death of lambs was greater in CVF than CON (37.0 vs.5.6%; P = 0.002), as was the number of malformed lambs (13.0 vs. 0%; P < 0.001). Malformed lambs were associated with breech presentations. Litter size was not different in the CVF lambing (1.77 vs 1.86; P = 0.471), but lamb birth weight tended to be less (2.80 vs. 3.04 kg; P = 0.055) while ewe postpartum weight was not different (45.3 vs. 47.0 kg; P = 0.384). The outbreak of CVF reduced the lambing rate and increased the incidence of neonatal death and malformations. The outbreak occurred during a summer with unusually high rainfall and may be associated with changing weather patterns linked to climate change. Delaying summer breeding may be considered a mitigation strategy if feasible.

Climate Change and Climate Justice in Rural Sindh: Evidences and Experiences from the Rural-Based Population of Khairpur District

The present research study was carried out to collect the evidences of the climate change impact on the local communities of district Khairpur and to understand the views of people how they experience the climate change impact on their lives. The current study was undertaken employing the qualitative research methodology with a small sample size of villages aging from 25 to 65 age from a single union council. Qualitative research cannot be generalized as qualitative findings are generalized where large sample size is selected to collect the data. The study was carried out on four major areas of the climate change stressors which are Changes in weather patterns, floods, heat waves and heavy rains. All four stressor have direct severed effect on the lives of rural-based population. The findings of the study reveal that climate change has severe impact on the lives of common people which bear lots of pain in terms of agriculture loss where their standing crops are vanished away , their homes are destroyed completely, livestock is dying off due to the diseases spread and lack of pastures in the vicinity where flooded water stand. Other than this, findings tell us that the role of government seems very pathetic towards the affected people of district Khairpur where score of people have no food items to eat, no shelter to live in and other temporary things at the time of heavy rains and floods. This study can be a torch bearer for the policy makers, governments to formulate the policies according to the ground realities. The vulnerabilities of people due to these climate change stressors are visible to governments. Hence, Climate disasters are affecting every corner of the Sindh, and its marginalized communities are left to face a disproportionate share of the impacts of climate change which is violation of UN Framework for climate change.

Endemic crop wild relatives in Chile towards the end of the 21st century: Protected areas and agricultural expansion

AbstractClimate change is expected to change weather patterns in Chile significantly. Preserving the taxonomic and genetic diversity of crop wild relatives (CWR) is critical to ensure the availability of crops for future human food. However, many CWR are threatened in their natural habitats and underrepresented in gene banks. This research aimed to analyze the current and future climatic suitability under climate change of Chilean endemic CWR, the role of protected areas in their conservation, and possible conflicts of land use with agricultural production. The climatic suitability of 30 species was modeled with present and future bioclimatic variables using a species distribution modeling approach. The climatically suitable areas of all endemic CWR species analyzed are projected to change; 26 increased their suitable areas in the future and four decreased (Ribes integrifolium Phil., Dioscorea fastigiata Gay, Solanum chilense (Dunal) Reiche, Lupinus oreophilus Phil.). Specific conflict with agricultural land use is projected to occur between Valparaiso and Biobio regions, where zones not in protected areas with more than 15 CWR species intersect with those that will be more suitable to produce food crops. Careful and informed planning is required to protect the future distribution of endemic CWR in Chile, especially for species whose climatically suitable area decreases. This effort should comprise a coordinated approach that includes both in situ and ex situ conservation strategies to preserve genetic diversity.

Water consumption behaviour and the use of technology among households in Durban, South Africa

Abstract Freshwater resources remain under constant pressure due to population growth, economic development, and changing weather patterns. Water supply utilities generally struggle to keep up with the growing demand for freshwater resources and consequently adopt demand management policies to address supply challenges. As water consumers, households can play a major role in water conservation. This paper examines the impact of biographic characteristics on water consumption behaviour and the adoption of water-efficient technologies in the city of Durban, South Africa. Probit regression models are estimated using survey data collected from 300 household heads sampled across the city. Among other results, the study finds income as the most consistent determinant of water consumption behaviours and the adoption of water-efficient technologies. Furthermore, the level of education was also found to be a consistent determinant of the adoption and installation of water-efficient technologies. These results are significant and serve to guide water utilities when implementing demand management water policies.

Comparison of Melioidosis Indirect Hemagglutination Assay between Three Testing Laboratories in Australia.

Melioidosis caused by Burkholderia pseudomallei causes significant morbidity and mortality in Southeast Asia and northern Australia. Clinical manifestations remain diverse, including localized skin infection, pneumonia, and chronic abscess formation. Culture remains the gold standard of diagnosis, with serology and antigen detection tests playing a role if culture is unfeasible. Serologic diagnosis remains challenging, with limited standardization across different assays. In areas of endemicity, high rates of seropositivity have been documented. The indirect hemagglutination assay (IHA) is one of the more widely used serologic tests in these areas. In Australia, only three centers perform the test. Annually, laboratory A, laboratory B, and laboratory C perform approximately 1,000, 4,500, and 500 tests, respectively. A comparison of a total of 132 sera was analyzed from the routine quality exchange program between these centers from 2010 until 2019. Overall, 18.9% of sera tested had an interpretative discrepancy between laboratories. IMPORTANCE This study found significant discrepant results between three Australian centers offering the melioidosis indirect hemagglutination assay (IHA), despite testing the same samples. We have highlighted that the IHA is a nonstandardized test, which had different source antigens at each of the different laboratories. Melioidosis is a global disease, is associated with significant mortality, and is perhaps under recognized. It is likely to have increasing impact with changing weather patterns. The IHA has been used frequently as an adjunct to the diagnosis of clinical disease and is the mainstay of determining seroprevalence within populations. Despite its relative ease of use, especially in low resource settings, our study highlights the significant limitations of the melioidosis IHA. It has wide ranging implications, serving as an impetus for developing better diagnostic tests. This study is of interest to practitioners and researchers working in the various geographic regions affected by melioidosis.

Behavioral circatidal rhythms require Bmal1 in Parhyale hawaiensis

Organisms living in the intertidal zone are exposed to a particularly challenging environment. In addition to daily changes in light intensity and seasonal changes in photoperiod and weather patterns, they experience dramatic oscillations in environmental conditions due to the tides. To anticipate tides, and thus optimize their behavior and physiology, animals occupying intertidal ecological niches have acquired circatidal clocks. Although the existence of these clocks has long been known, their underlying molecular components have proven difficult to identify, in large part because of the lack of an intertidal model organism amenable to genetic manipulation. In particular, the relationship between the circatidal and circadian molecular clocks, and the possibility of shared genetic components, has been a long-standing question. Here, we introduce the genetically tractable crustacean Parhyale hawaiensis as a system for the study of circatidal rhythms. First, we show that P.hawaiensis exhibits robust 12.4-h rhythms of locomotion that can be entrained to an artificial tidal regimen and are temperature compensated. Using CRISPR-Cas9 genome editing, we then demonstrate that the core circadian clock gene Bmal1 is required for circatidal rhythms. Our results thus demonstrate that Bmal1 is a molecular link between circatidal and circadian clocks and establish P.hawaiensis as a powerful system to study the molecular mechanisms underlying circatidal rhythms and their entrainment.