Method and process towards developing a Health Vulnerability Index (HVI) for Extreme Weather Events (EWEs) for local residents in South Africa

An increase in incidence and amplitude of extreme weather events (EWEs) linked to climate change, has resulted in greater human exposure and vulnerability to weather-related health effects. Increases in the occurrence of EWEs, including storms, flooding, extreme heat and wildfires, will impact health globally, with poor and vulnerable populations disproportionately affected. Vulnerability to EWEs, and the ability to adapt to these weather shocks, are influenced by existing physical, social and political limitations of a given region. As such, developing context-specific health vulnerability indices to inform planning and decision-making for policy makers and citizens alike, should be prioritized. The existence and development of health vulnerability indices in South Africa are limited, therefore, this study provides a foundation from which future indices can build. Mixed methods approaches including evidence and data analysis/synthesis and focus groups are used to understand the interconnections between extreme weather events and human health, including citizens' understanding of emergent vulnerabilities linked to these events. The methods employed in this study include: •A rapid evidence review (RER) including data extraction identifying health impacts and indicators.•Development of a draft health vulnerability index (HVI) framework.•Focus groups and individual interviews testing the draft HVI for citizen input and framework refinement.

Organic carbon accumulation in British saltmarshes

Saltmarshes are a crucial component of the coastal carbon (C) system and provide a natural climate regulation service through the accumulation and long-term storage of organic carbon (OC) in their soils. These coastal ecosystems are under growing pressure from a changing climate and increasing anthropogenic disturbance. To manage and protect these ecosystems for C and to allow their inclusion in emissions and natural-capital accounting, as well as carbon markets, accurate and reliable estimates of OC accumulation are required. However, globally, such data are rare or of varying quality. Here, we quantify sedimentation rates and OC densities for 21 saltmarshes in Great Britain (GB). We estimate that, on average, saltmarshes accumulate OC at a rate of 110.88 ± 43.12 g C m-2 yr-1. This is considerably less than widely applied global saltmarsh averages. It is therefore highly likely that the contribution of northern European saltmarshes to global saltmarsh OC accumulation has been significantly overestimated. Taking account of the climatic, geomorphological, oceanographic, and ecological characteristics of all GB saltmarshes and the areal extent of different saltmarsh zones, we estimate that the 451.65 km2 of GB saltmarsh accumulates 46,563 ± 4353 t of OC annually. These low OC accumulation rates underline the importance of the 5.20 ± 0.65 million tonnes of OC already stored in these vulnerable coastal ecosystems. Going forward the protection and preservation of the existing stores of OC in GB saltmarshes must be a priority for the UK as this will provide climate benefits through avoided emissions several times more significant than the annual accumulation of OC in these ecosystems.

Plant size traits are key contributors in the spatial variation of net primary productivity across terrestrial biomes in China

Understanding the spatial variability of ecosystem functions is an important step forward in predicting changes in ecosystems under global transformations. Plant functional traits are important drivers of ecosystem functions such as net primary productivity (NPP). Although trait-based approaches have advanced rapidly, the extent to which specific plant functional traits are linked to the spatial diversity of NPP at a regional scale remains uncertain. Here, we used structural equation models (SEMs) to disentangle the relative effects of abiotic variables (i.e., climate, soil, nitrogen deposition, and human footprint) and biotic variables (i.e., plant functional traits and community structure) on the spatial variation of NPP across China and its eight biomes. Additionally, we investigated the indirect influence of climate and soil on the spatial variation of NPP by directly affecting plant functional traits. Abiotic and biotic variables collectively explained 62.6 % of the spatial differences of NPP within China, and 28.0 %-69.4 % across the eight distinct biomes. The most important abiotic factors, temperature and precipitation, had positive effects for NPP spatial variation. Interestingly, plant functional traits associated with the size of plant organs (i.e., plant height, leaf area, seed mass, and wood density) were the primary biotic drivers, and their positive effects were independent of biome type. Incorporating plant functional traits improved predictions of NPP by 6.7 %-50.2 %, except for the alpine tundra on the Qinghai-Tibet Plateau. Our study identifies the principal factors regulating NPP spatial variation and highlights the importance of plant size traits in predictions of NPP variation at a large scale. These results provide new insights for involving plant size traits in carbon process models.

Association between abusive supervision and nurses' withholding voice about patient safety: the roles of impression management motivation and speak up-related climate

BACKGROUND

Abusive supervision by the nurse manager significantly influences nurses' withholding voice about patient safety. The role of impression management motivation and speak up-related climate is crucial in understanding their connection. This study aimed to explore the relationship between abusive supervision, impression management motivation, speak up-related climate, and withholding voice about patient safety.

METHODS

This cross-sectional study employed a convenience sampling method to recruit 419 clinical nurses from Taizhou Hospital, Zhejiang Province, China, between 1 November 2022 and 31 January 2023. The study adhered to the STROBE checklist. Abusive supervision and impression management motivation were assessed using the Chinese versions of the Abusive Supervision Scale and the Impression Management Motivation Scale, respectively. Withholding voice about patient safety and speak up-related climate were identified using the Chinese version of the Speaking Up about Patient Safety Questionnaire.

RESULTS

Nurse leaders' abusive supervision (β=0.40, p<0.01) and nurses' impression management motivation (β=0.10, p<0.01) significantly and positively influenced nurses' withholding voice about patient safety. We introduced impression management motivation as a mediating variable, and the effect of abusive supervision on nurses' withholding voice decreased (β from 0.40 to 0.38, p< 0.01). Nurses' speak up-related climate played a moderating role between abusive supervision and impression management motivation (β= 0.24, p<0.05).

CONCLUSIONS

Abusive supervision by nursing leaders can result in nurses withholding voice about patient safety out of self-protective impression management motives. This phenomenon inhibits nurses' subjective initiative and undermines their proactive involvement in improving patient safety, and hinders the cultivation of a culture encouraging full participation in patient safety, which should warrant significant attention.

Differential capacity of phragmites ecotypes in remediation of inorganic contaminants in coastal ecosystems: Implications for climate change

Remediating inorganic pollutants is an important part of protecting coastal ecosystems, which are especially at risk from the effects of climate change. Different Phragmites karka (Retz) Trin. ex Steud ecotypes were gathered from a variety of environments, and their abilities to remove inorganic contaminants from coastal wetlands were assessed. The goal is to learn how these ecotypes process innovation might help reduce the negative impacts of climate change on coastal environments. The Phragmites karka ecotype E1, found in a coastal environment in Ichkera that was impacted by residential wastewater, has higher biomass production and photosynthetic pigment content than the Phragmites karka ecotypes E2 (Kalsh) and E3 (Gatwala). Osmoprotectant accumulation was similar across ecotypes, suggesting that all were able to successfully adapt to polluted marine environments. The levels of both total soluble sugars and proteins were highest in E2. The amount of glycine betaine (GB) rose across the board, with the highest levels being found in the E3 ecotype. The study also demonstrated that differing coastal habitats significantly influenced the antioxidant activity of all ecotypes, with E1 displaying the lowest superoxide dismutase (SOD) activity, while E2 exhibited the lowest peroxidase (POD) and catalase (CAT) activities. Significant morphological changes were evident in E3, such as an expansion of the phloem, vascular bundle, and metaxylem cell areas. When compared to the E3 ecotype, the E1 and E2 ecotypes showed striking improvements across the board in leaf anatomy. Mechanistic links between architectural and physio-biochemical alterations are crucial to the ecological survival of different ecotypes of Phragmites karka in coastal environments affected by climate change. Their robustness and capacity to reduce pollution can help coastal ecosystems endure in the face of persistent climate change.

Putative climate adaptation in American pikas (Ochotona princeps) is associated with copy number variation across environmental gradients

Improved understanding of the genetic basis of adaptation to climate change is necessary for maintaining global biodiversity moving forward. Studies to date have largely focused on sequence variation, yet there is growing evidence that suggests that changes in genome structure may be an even more significant source of adaptive potential. The American pika (Ochotona princeps) is an alpine specialist that shows some evidence of adaptation to climate along elevational gradients, but previous work has been limited to single nucleotide polymorphism based analyses within a fraction of the species range. Here, we investigated the role of copy number variation underlying patterns of local adaptation in the American pika using genome-wide data previously collected across the entire species range. We identified 37-193 putative copy number variants (CNVs) associated with environmental variation (temperature, precipitation, solar radiation) within each of the six major American pika lineages, with patterns of divergence largely following elevational and latitudinal gradients. Genes associated (n = 158) with independent annotations across lineages, variables, and/or CNVs had functions related to mitochondrial structure/function, immune response, hypoxia, olfaction, and DNA repair. Some of these genes have been previously linked to putative high elevation and/or climate adaptation in other species, suggesting they may serve as important targets in future studies.

Illuminating patterns of firefly abundance using citizen science data and machine learning models

As insect populations decline in many regions, conservation biologists are increasingly tasked with identifying factors that threaten insect species and developing effective strategies for their conservation. One insect group of global conservation concern are fireflies (Coleoptera: Lampyridae). Although quantitative data on firefly populations are lacking for most species, anecdotal reports suggest that some firefly populations have declined in recent decades. Researchers have hypothesized that North American firefly populations are most threatened by habitat loss, pesticide use, and light pollution, but the importance of these factors in shaping firefly populations has not been rigorously examined at broad spatial scales. Using data from >24,000 surveys (spanning 2008-16) from the citizen science program Firefly Watch, we trained machine learning models to evaluate the relative importance of a variety of factors on bioluminescent firefly populations: pesticides, artificial lights at night, land cover, soil/topography, short-term weather, and long-term climate. Our analyses revealed that firefly abundance was driven by complex interactions among soil conditions (e.g., percent sand composition), climate/weather (e.g., growing degree days), and land cover characteristics (e.g., percent agriculture and impervious cover). Given the significant impact that climactic and weather conditions have on firefly abundance, there is a strong likelihood that firefly populations will be influenced by climate change, with some regions becoming higher quality and supporting larger firefly populations, and others potentially losing populations altogether. Collectively, our results support hypotheses related to factors threatening firefly populations, especially habitat loss, and suggest that climate change may pose a greater threat than appreciated in previous assessments. Thus, future conservation of North American firefly populations will depend upon 1) consistent and continued monitoring of populations via programs like Firefly Watch, 2) efforts to mitigate the impacts of climate change, and 3) insect-friendly conservation practices.

Ambient heat exposure patterns and emergency department visits and hospitalizations among medicare beneficiaries 2008-2019

OBJECTIVE

To assess the association between ambient heat and all-cause and cause-specific emergency department (ED) visits and acute hospitalizations among Medicare beneficiaries in the conterminous United States.

DESIGN

Retrospective cohort study.

SETTING

Conterminous US from 2008 and 2019.

PARTICIPANTS

2% random sample of all Medicare fee-for-service beneficiaries eligible for Parts A, B, and D.

MAIN OUTCOME MEASURES

All-cause and cause-specific (cardiovascular, renal, and heat-related) ED visits and unplanned hospitalizations were identified using primary ICD-9 or ICD-10 diagnosis codes. We measured the association between ambient temperature - defined as daily mean temperature percentile of summer (June through September) - and the outcomes. Hazard ratios and their associated 95% confidence intervals were estimated using multivariable Cox proportional hazards regression, adjusting for individual level demographics, comorbidities, healthcare utilization factors and zip-code level social factors.

RESULTS

Among 809,636 Medicare beneficiaries (58% female, 81% non-Hispanic White, 24% <65), older beneficiaries (aged ≥65) exposed to >95th percentile temperature had a 64% elevated adjusted risk of heat-related ED visits (HR [95% CI], 1.64 [1.46,1.85]) and a 4% higher risk of all-cause acute hospitalization (1.04 [1.01,1.06]) relative to <25th temperature percentile. Younger beneficiaries (aged <65) showed increased risk of heat-related ED visits (2.69 [2.23,3.23]) and all-cause ED visits (1.03 [1.01,1.05]). The associations with heat related events were stronger in males and individuals dually eligible for Medicare and Medicaid. No significant differences were observed by climatic region. We observed no significant relationship between temperature percentile and risk of CV-related ED visits or renal-related ED visits.

CONCLUSIONS

Among Medicare beneficiaries from 2008 to 2019, exposure to daily mean temperature ≥ 95th percentile was associated with increased risk of heat-related ED visits, with stronger associations seen among beneficiaries <65, males, and patients with low socioeconomic position. Further longitudinal studies are needed to understand the impact of heat duration, intensity, and frequency on cause-specific hospitalization outcomes.

Emerging effects of temperature on human cognition, affect, and behaviour

Human body core temperature is tightly regulated within approximately 37 °C. Global near surface temperature has increased by over 1.2 °C between 1850 and 2020. In light of the challenge this poses to human thermoregulation, the present perspective article sought to provide an overview on the effects of varying ambient and body temperature on cognitive, affective, and behavioural domains of functioning. To this end, an overview of observational and experimental studies in healthy individuals and individuals with mental disorders was provided. Within body core temperature at approximately 37 °C, relatively lower ambient and skin temperatures appear to evoke a need for social connection, whereas comparably higher temperatures appear to facilitate notions of other as closer and more sociable. Above-average ambient temperatures are associated with increased conflicts as well as incident psychotic and depressive symptoms, mental disorders, and suicide. With mild hypo- and hyperthermia, paradoxical effects are observed: whereas the acute states are generally characterised by impairments in cognitive performance, anxiety, and irritability, individuals with depression experience longer-term symptom improvements with treatments deliberately inducing these states for brief amounts of time. When taken together, it has thus become clear that temperature is inexorably associated with human cognition, affect, and (potentially) behaviour. Given the projected increase in global warming, further research into the affective and behavioural sequelae of heat and the mechanisms translating it into mental health outcomes is urgently warranted.

Prediction of coccidiosis prevalence in extensive backyard chickens in countries and regions of the Horn of Africa

Coccidiosis is one of the leading morbidity causes in chickens, causing a reduction of body weight and egg production. Backyard chickens are at risk of developing clinical and subclinical coccidiosis due to outdoor housing and scavenging behaviour, jeopardizing food security in households. The objectives of this study were to estimate clinical prevalence of coccidiosis at country and regional levels in the Horn of Africa in extensive backyard chickens. A binomial random effects model was developed to impute prevalence of coccidiosis. Previously gathered prevalence data (n = 40) in backyard chickens was used to define the model. Precipitation (OR: 1.09 (95% CI: 1.05-1.13) and the presence of seasonal rainfall (OR: 1.85, 95% CI: 1.27-2.70) significantly increase prevalence. Results showed an overall prevalence of coccidiosis in the Horn of Africa of 0.21 (95% CI: 0.15-0.29). Ethiopia, the Republic of South Sudan and Kenya showed the highest prevalence and Djibouti the lowest. Significant differences between Djibouti and the countries with highest prevalence were found. However, no evidence of a significant difference between the rest of the countries. Kenya and Ethiopia showed larger prevalence differences between regions. Results could assist with the targeting of testing for coccidiosis, the observation for clinical disease of chickens living in specific regions and as a baseline for the evaluation of future control measures.

Mycorrhizal symbioses in the Andean paramo

The Andean paramo, hereafter "paramo", is a Neotropical high-mountain region between the treeline and permanent snowline (3500-4800 m) and is considered the world's coolest biodiversity hotspot. Because of paramo's high humidity, solar radiation and temperature variation, mycorrhizal symbiosis is expected to be essential for plants. Existing theory suggests that replacement of arbuscular mycorrhizal (AM) by ectomycorrhizal (ECM) and then ericoid mycorrhizal plants (ERM) can be expected with increasing elevation. Previous findings also suggest that non-(NM) and facultatively mycorrhizal (FM) species predominate over obligatory mycorrhizal (OM) species at high elevations. However, these expectations have never been tested outside of the northern temperate zone. We addressed the distribution and environmental drivers of plant mycorrhizal types (AM, ECM and ERM) and statuses (NM, FM and OM) along the paramo's elevational gradient. We used vegetation plots from the VegParamo database, climatic and edaphic data from online repositories, and up-to-date observation information about plant mycorrhizal traits at species and genus level, the latter being proposed as hypotheses. AM plants were dominant along the entire gradient, and ERM plants were most abundant at the lowest elevations (2500-3000 m). The share of FM plants increased and that of OM plants decreased with elevation, while NM plants increased above 4000 m. Temperature and soil pH were positively related to the abundance of AM plants and negatively to ERM plants. Our results reveal patterns that contrast with those observed in temperate northern-hemisphere ecosystems.

Trend and Seasonality of Hip Fractures in Catalonia, Spain: Exploring the Influence of Climate

To describe the secular trend and seasonality of the incidence of hip fracture (HF) and its relationship with climatic variables during the period 2010-2019 in Catalonia in people aged ≥ 65 years. The results were analyzed by sex, age groups (65-74, 75-84, and ≥ 85), and types of fracture (extracapsular and intracapsular). Data on sex, age, type of fracture, year, and month of hospitalization of patients admitted with a diagnosis of HF between January 1, 2010 and December 31, 2019 were collected. Crude and standardized HF incidence (HFi) rates were obtained. Data on the monthly mean of climatological variables (temperature, insolation, icy days, rain, relative humidity, atmospheric pressure, and wind force) were obtained from the network of meteorological stations in Catalonia. Time series analytical statistics were used to identify trends and seasonality. Linear regression and a seasonal autoregressive integrated moving average (ARIMA) were used to analyze the relationship of each climatic parameter with fracture rates. In addition, generalized additive models were used to ascertain the best predictive model. The total number of HF episodes was 90,149 (74.1% in women and 25.9% in men). The total number of HFs increased by 6.4% between 2010 and 2019. The median age (SD) was 84.5 (7.14) and 54% of patients were ≥ 85 years of age. Extracapsular fractures were the most common (55%). The standardized incidence rates decreased from 728.1/100,000 (95% CI 738.6-769.3) to 624.5/100,000 (95% CI 648.7-677.0), which represents a decrease of 14.2% (p < 0.05). The decline was greater at older ages. There were seasonal variations, with higher incidences in autumn (27.2%) and winter (25.7%) and lower rates in summer (23.5%) and spring (23.6%). Seasonality was more pronounced in elderly people and men. In the bivariate regression analysis, high temperatures and greater insolation were negatively associated with the HF rate, while the number of icy days, rainy days, and high relative humidity were associated with a higher incidence of fractures in all age groups and sexes. In the regression analysis using the seasonal ARIMA model, only insolation had a consistently significant association with overall HFi, after adjusting by trend and other climatic parameters. While the global number of HFs grew in Catalonia due to increases in the elderly population, the standardized HF rate decreased during the years 2010-2019. There was a seasonal trend, with predominance in the cold months and correlations with climatic parameters, especially with insolation.

A microbial risk assessor's guide to Valley Fever (Coccidioides spp.): Case study and review of risk factors

Valley Fever is a respiratory disease caused by inhalation of arthroconidia, a type of spore produced by fungi within the genus Coccidioides spp. which are found in dry, hot ecosystems of the Western Hemisphere. A quantitative microbial risk assessment (QMRA) for the disease has not yet been performed due to a lack of dose-response models and a scarcity of quantitative occurrence data from environmental samples. A literature review was performed to gather data on experimental animal dosing studies, environmental occurrence, human disease outbreaks, and meteorological associations. As a result, a risk framework is presented with information for parameterizing QMRA models for Coccidioides spp., with eight new dose-response models proposed. A probabilistic QMRA was conducted for a Southwestern US agricultural case study, evaluating eight scenarios related to farming occupational exposures. Median daily workday risks for developing severe Valley Fever ranged from 2.53 × 10-7 (planting by hand while wearing an N95 facemask) to 1.33 × 10-3 (machine harvesting while not wearing a facemask). The literature review and QMRA synthesis confirmed that exposure to aerosolized arthroconidia has the potential to result in high attack rates but highlighted that the mechanistic relationships between environmental conditions and disease remain poorly understood. Recommendations for Valley Fever risk assessment research needs in order to reduce disease risks are discussed, including interventions for farmers.

Investigation of fire regime dynamics and modeling of burn area over India for the twenty-first century

The characteristics of the vegetation fire (VF) regime are strongly influenced by geographical variables such as regional physiographic settings, location, and climate. Understanding the VF regime is extremely important for managing and mitigating the impacts of fires on ecosystems, communities, and human activities in forest fire-prone regions. The present study thereby aimed to explore the potential effects of the confounding factors on VF in India to offer actionable and achievable solutions for mitigating this concurring environmental issue sustainably. A global burn area (250 m) data (Fire-CCIv5.1) and fire radiative power (FRP) were used to investigate the dynamics of VF across seven different divisions in India. The study also used the maximum and minimum temperatures, precipitation, population density, and intensity of human modification to model forest burn areas (including grassland). The Coupled Model Intercomparison Project-6 (CMIP6) was used to predict the burn area for 2030 and 2050 future climate scenarios. The present study accounted for a sizable increasing trend of VF during 2001-2019 period. The highest increasing trend was found in central India (513 and 343 km2 year-1 in the forest and crop fire, respectively), followed by southern India (364 km2 year-1 in forest fire), and upper Indo-Gangetic plain (128 km2 year-1 in crop fire). The FRP has varied significantly across the divisions, with the north-eastern Himalayas exhibiting the highest FRP hotspot. The maximum and minimum temperatures have the greatest influence on forest fires, according to Random Forest (RF) modeling. The estimated pre-monsoonal burn area for 2050 and 2050 future scenarios suggested a more frequent forest fire occurrence across India, particularly in southern and central India. A comprehensive forest fire control policy is therefore essential to safeguard and conserve forest cover in the regions, affected by forest fire periodically.

Pension funds and fossil fuel phase-out: historical developments and limitations of pension climate strategies

Despite the decades of international climate negotiations and several landmark agreements, global efforts to date to restrict fossil fuel production in line with climate targets have been unsuccessful. As national and international policies continue to fall short of phasing out fossil fuels, increasing attention has been paid to non-state actors, like pension funds, as a potential source of more ambitious climate action. As major asset owners, large shareholders in fossil fuel companies, and historically activist investors, pension funds are theoretically well-placed to contribute to phasing out fossil fuels. Despite growing recognition of this potential role for pension funds and other major investors in climate change mitigation, there has been little attention to pension funds' historical record on climate change, or to how their climate strategies have developed and changed over time. This paper examines how the climate strategies of the largest US and European pension funds have evolved in relation to key developments in international climate agreements and the extent to which these strategies contribute to restricting fossil fuel supply. Through an analysis of the annual, governance, and sustainability reports of 6 pension funds from 1997 to 2022, we examine the strategies pension funds have adopted to address both climate change and fossil fuels. Pension funds have demonstrated responsiveness to the signals of international climate agreements, adopting a range of strategies with respect to climate change (amongst others, integrating ESG principles, increasing their sustainable investments, and setting net zero goals). Their explicit attention to fossil fuels and contribution to supply-side interventions take the form of systematic shareholder engagement, (selective) divestment, and lobbying policymakers. While pension fund climate action is growing , the ambition of their strategies is not aligned with a rapid fossil fuel phaseout; their efforts are often focussed on improving disclosure and transparency and demonstrate complacency with minimal improvements from fossil fuel companies. If pension funds are to significantly contribute to phasing out fossil fuels, redefining pension fund responsibilities and the traditional shareholder role will likely be required.

Analyzing the correlation between quinolone-resistant Escherichia coli resistance rates and climate factors: A comprehensive analysis across 31 Chinese provinces

BACKGROUND

The increasing problem of bacterial resistance, particularly with quinolone-resistant Escherichia coli (QnR eco) poses a serious global health issue.

METHODS

We collected data on QnR eco resistance rates and detection frequencies from 2014 to 2021 via the China Antimicrobial Resistance Surveillance System, complemented by meteorological and socioeconomic data from the China Statistical Yearbook and the China Meteorological Data Service Centre (CMDC). Comprehensive nonparametric testing and multivariate regression models were used in the analysis.

RESULT

Our analysis revealed significant regional differences in QnR eco resistance and detection rates across China. Along the Hu Huanyong Line, resistance rates varied markedly: 49.35 in the northwest, 54.40 on the line, and 52.30 in the southeast (P = 0.001). Detection rates also showed significant geographical variation, with notable differences between regions (P < 0.001). Climate types influenced these rates, with significant variability observed across different climates (P < 0.001). Our predictive model for resistance rates, integrating climate and healthcare factors, explained 64.1% of the variance (adjusted R-squared = 0.641). For detection rates, the model accounted for 19.2% of the variance, highlighting the impact of environmental and healthcare influences.

CONCLUSION

The study found higher resistance rates in warmer, monsoon climates and areas with more public health facilities, but lower rates in cooler, mountainous, or continental climates with more rainfall. This highlights the strong impact of climate on antibiotic resistance. Meanwhile, the predictive model effectively forecasts these resistance rates using China's diverse climate data. This is crucial for public health strategies and helps policymakers and healthcare practitioners tailor their approaches to antibiotic resistance based on local environmental conditions. These insights emphasize the importance of considering regional climates in managing antibiotic resistance.

Coping with extremes: the rumen transcriptome and microbiome co-regulate plateau adaptability of Xizang goat

The interactions between the rumen microbiota and the host are crucial for the digestive and absorptive processes of ruminants, and they are heavily influenced by the climatic conditions of their habitat. Owing to the harsh conditions of the high-altitude habitat, little is known about how ruminants regulate the host transcriptome and the composition of their rumen microbiota. Using the model species of goats, we examined the variations in the rumen microbiota, transcriptome regulation, and climate of the environment between high altitude (Lhasa, Xizang; 3650 m) and low altitude (Chengdu, Sichuan, China; 500 m) goats. The results of 16 S rRNA sequencing revealed variations in the abundance, diversity, and composition of rumen microbiota. Papillibacter, Quinella, and Saccharofermentans were chosen as potential microbes for the adaptation of Xizang goats to the harsh climate of the plateau by the Spearman correlation study of climate and microbiota. Based on rumen transcriptome sequencing analysis, 244 genes were found to be differentially expressed between Xizang goats and low-altitude goats, with 127 genes showing up-regulation and 117 genes showing down-regulation. SLC26A9, GPX3, ARRDC4, and COX1 were identified as potential candidates for plateau adaptation in Xizang goats. Moreover, the metabolism of fatty acids, arachidonic acids, pathway involving cytokines and their receptors could be essential for adaptation to plateau hypoxia and cold endurance. The expression of GPX3, a gene linked to plateau acclimatization in Xizang goats, was linked to the abundance of Anaerovibrio, and the expression of SLC26A9 was linked to the quantity of Selenomonas, according to ruminal microbiota and host Spearman correlation analysis. Our findings imply that in order to adapt harsh plateau conditions, Xizang goats have evolved to maximize digestion and absorption as well as to have a rumen microbiota suitable for the composition of their diet.

Short-term association between air temperature and mortality in seven cities in Norway: A time series analysis

BACKGROUND

The association between ambient air temperature and mortality has not been assessed in Norway. This study aimed to quantify for seven Norwegian cities (Oslo, Bergen, Stavanger, Drammen, Fredrikstad, Trondheim and Tromsø) the non-accidental, cardiovascular and respiratory diseases mortality burden due to non-optimal ambient temperatures.

METHODS

We used a historical daily dataset (1996-2018) to perform city-specific analyses with a distributed lag non-linear model with 14 days of lag, and pooled results in a multivariate meta-regression. We calculated attributable deaths for heat and cold, defined as days with temperatures above and below the city-specific optimum temperature. We further divided temperatures into moderate and extreme using cut-offs at the 1st and 99th percentiles.

RESULTS

We observed that 5.3% (95% confidence interval (CI) 2.0-8.3) of the non-accidental related deaths, 11.8% (95% CI 6.4-16.4) of the cardiovascular and 5.9% (95% CI -4.0 to 14.3) of the respiratory were attributable to non-optimal temperatures. Notable variations were found between cities and subgroups stratified by sex and age. The mortality burden related to cold dominated in all three health outcomes (5.1%, 2.0-8.1, 11.4%, 6.0-15.4, and 5.1%, -5.5 to 13.8 respectively). Heat had a more pronounced effect on the burden of respiratory deaths (0.9%, 0.2-1.0). Extreme cold accounted for 0.2% of non-accidental deaths and 0.3% of cardiovascular and respiratory deaths, while extreme heat contributed to 0.2% of non-accidental and to 0.3% of respiratory deaths.

CONCLUSIONS

Most of the burden could be attributed to the contribution of moderate cold. This evidence has significant implications for enhancing public-health policies to better address health consequences in the Norwegian setting.

Influence of meteorological variables on the frequency of visits and hospital admission for epistaxis in a city with a cold semi-arid climate (Lorca, Spain)

BACKGROUND AND OBJECTIVES

Epistaxis is a common emergency for otorhinolaryngologists. Although the aetiological factors have been widely studied, they remain subject to debate. The role of meteorological variables has been discussed in recent years, but results have been inconsistent. Given a lack of prior data, the aim of our study was to identify the meteorological variables that influence the frequency of visits and hospital admission for epistaxis in a city with a cold semi-arid climate in Spain.

METHODS

Case-control study.

CASES

patients who attended the accident and emergency department of a secondary level hospital for epistaxis over a 9-year period (2011-2019). Controls were established by simple random sampling among emergency rooms visits in general (patients who attended the same centre over the same period of time). Sociodemographic, clinical and meteorological variables were all taken into account.

RESULTS

2749 patients in the epistaxis group and 2764 in the control group. There were significant differences in the epistaxis group, with a higher proportion of male (62.85%) and older patients. Univariate and multivariate analysis revealed that the daily minimum temperature and maximum wind speed were factors significantly associated with the onset of epistaxis. In addition, logistic regression analysis showed that decreases in minimum temperature and increases in maximum wind speed were associated with an increase in epistaxis (p < 0.01). No association was found between hospital admission and the weather conditions.

CONCLUSION

Our findings suggest that low minimum temperatures and high wind speeds are associated with the number of visits to hospital accident and emergency departments for epistaxis, but not with hospital admission.

Farmers´ sense of the biological impact of extreme heat and seasonality on Swedish high-yielding dairy cows - A mixed methods approach

Supporting dairy farmers in becoming resilient towards extreme weather requires a broad understanding of the experiences and perceived risks associated with these events from those who undergo them. We used a mixed methods approach to explore national trends of biological consequences on dairy cow udder health and fertility, combined with in-depth farmer conversations around extreme weather events, focusing on heat. The aim is to provide a comprehensive picture of how dairy farmer perceptions, priorities and decision-making are related to the season and extreme weather to identify preventive pathways that can reduce biological costs of heat stress on Swedish dairy cattle during summer. Data collected monthly at cow and farm level between 2016-2019 as part of the Swedish milk and disease recording system confirm seasonal trends and show increased somatic cell counts (SCC) and negatively impacted fertility during summers. In addition, transcriptions of 18 interviews with dairy farmers across the country and seasonal variations of SCC and fertility were thematically analysed. The results suggest that farmers have a broad definition of extreme weather and are aware of the negative impacts. Yet handling of extreme weather events can mainly be classified as reactive. Nevertheless, there are long-term effects on the farm economy, health and herd dynamics. Swedish dairy farmers are currently showing resilience, albeit a fragile one. The capability to ensure sufficient feed production in extreme weather is critical for farm self-perceived resilience. However, acknowledging the long-term biological costs related to fertility, currently not perceived by farmers, has the potential to support proactive planning and improve farm resilience and profitability.

Climatic conditions and concentrations of BTEX compounds in atmospheric media

Climatic and meteorological conditions are among the factors affecting the ambient concentrations of BTEX compounds. This systematic review and meta-analysis aimed to interrogate the seasonal effect of climatic conditions on the concentrations of BTEX compounds. Three electronic bibliographic databases including Scopus, PubMed, and Web of Science were systematically searched up to November 14, 2023. The search algorithm followed PRISMA guidance and consisted of three groupings of keywords and their possible combinations. For various climatic conditions, the overall mean and 95% confidence interval (CI) of effect size related to BTEX concentrations were calculated using a random-effect model. In total, 104 articles were included for evaluation in this review. BTEX ambient concentration was higher in winter (ranging from 36 out of 79 relevant studies for xylene to 52 out of 97 relevant studies for benzene) followed by summer and autumn. For humidity conditions, the highest exposure values for BTEX were detected for rainy weather (ranging from 3 out of 5 relevant studies for toluene and xylene to 4 out of 5 relevant studies for benzene and ethyl benzene) compared to dry conditions. The pooled concentration (μg/m3) of benzene, toluene, ethyl benzene, and xylene were computed as 2.61, 7.12, 2.21, and 3.61 in spring, 2.13, 7.53, 1.61, and 2.75 in summer, 3.04, 9.59, 3.14, and 5.50 in autumn, and 3.56, 8.71, 2.35, and 3.91 in winter, respectively. Moreover, the pooled concentrations (μg/m3) of BTEX were measured as 2.98, 7.22, 1.90, and 3.03 in dry weather and 3.15, 6.30, 2.14, and 3.86 in rainy or wet weather, respectively. In most seasons, the ambient concentrations of BTEX were higher in countries with low and middle incomes and in Middle Eastern countries and East/Southeast Asia compared to those in other regions (P < 0.001). The increasing concentrations of BTEX in winter and autumn followed by the summer season and during rainy/wet weather appear to be reasonably consistent despite variations in study methods, quality, or geography. Therefore, it is recommended that more serious control measures are considered for decreasing exposure to BTEX in these climatic conditions.

Towards development of functional climate-driven early warning systems for climate-sensitive infectious diseases: Statistical models and recommendations

Climate, weather and environmental change have significantly influenced patterns of infectious disease transmission, necessitating the development of early warning systems to anticipate potential impacts and respond in a timely and effective way. Statistical modelling plays a pivotal role in understanding the intricate relationships between climatic factors and infectious disease transmission. For example, time series regression modelling and spatial cluster analysis have been employed to identify risk factors and predict spatial and temporal patterns of infectious diseases. Recently advanced spatio-temporal models and machine learning offer an increasingly robust framework for modelling uncertainty, which is essential in climate-driven disease surveillance due to the dynamic and multifaceted nature of the data. Moreover, Artificial Intelligence (AI) techniques, including deep learning and neural networks, excel in capturing intricate patterns and hidden relationships within climate and environmental data sets. Web-based data has emerged as a powerful complement to other datasets encompassing climate variables and disease occurrences. However, given the complexity and non-linearity of climate-disease interactions, advanced techniques are required to integrate and analyse these diverse data to obtain more accurate predictions of impending outbreaks, epidemics or pandemics. This article presents an overview of an approach to creating climate-driven early warning systems with a focus on statistical model suitability and selection, along with recommendations for utilizing spatio-temporal and machine learning techniques. By addressing the limitations and embracing the recommendations for future research, we could enhance preparedness and response strategies, ultimately contributing to the safeguarding of public health in the face of evolving climate challenges.

Variability in weather and site properties affect fuel and fire behavior following fuel treatments in semiarid sagebrush-steppe

Fuel-treatments targeting shrubs and fire-prone exotic annual grasses (EAGs) are increasingly used to mitigate increased wildfire risks in arid and semiarid environments, and understanding their response to natural factors is needed for effective landscape management. Using field-data collected over four years from fuel-break treatments in semiarid sagebrush-steppe, we asked 1) how the outcomes of EAG and sagebrush fuel treatments varied with site biophysical properties, climate, and weather, and 2) how predictions of fire behavior using the Fuel Characteristic Classification System fire model related to land-management objectives of maintaining fire behavior expected of low-load, dry-climate grasslands. Generalized linear mixed effect modeling with build-up model selection was used to determine best-fit models, and marginal effects plots to assess responses for each fuel type. EAG cover decreased as antecedent-fall precipitation increased and increased as antecedent-spring temperatures and surface soil clay contents increased. Herbicides targeting EAGs were less effective where pre-treatment EAG cover was >40 % and antecedent spring temperatures were >9.5 °C. Sagebrush cover was inversely related to soil clay content, especially where clay contents were >17 %. Predicted fire behavior exceeded management objectives under 1) average fire weather conditions when EAG or sagebrush cover was >50 % or >26 %, respectively, or 2) extreme fire weather conditions when EAG or sagebrush cover was >10 % or >8 %, respectively. Consideration of the strong effects of natural variability in site properties and antecedent weather can help in justifying, planning and implementing fuel-treatments.

Dietary fatty acid transfer in pelagic food webs across trophic and climatic differences of Chinese lakes

In eutrophic lake ecosystems, cyanobacteria typically lead to unbalanced phytoplankton community structure and low dietary quality for consumers at higher trophic levels. However, it still remains poorly understood how zooplankton manage to respond to seasonal and spatial differences in lake trophic gradients and temperature factors to retain highly required dietary nutrients from phytoplankton. In this field study, we investigated seston and different size classes of zooplankton of temperate and subtropical large lakes of different trophic conditions in China. We used fatty acids (FA) as dietary nutrients from seston to zooplankton to investigate how eutrophication affects the FA composition of various zooplankton size classes. This study revealed a curvilinear relationship between total phosphorus (TP) and polyunsaturated fatty acids (PUFA) contents of edible phytoplankton ("seston") across 3 seasons and 2 climatic areas. The PUFA content of seston increased until mesotrophic lake conditions (TP: 11-20 μg L-1), after which the dietary provision of PUFA for respective consumers declined. Seston FA, rather than trophic condition or water temperature, primarily predicted changes in zooplankton FA, while this predictive power decreased with zooplankton size. Despite increasing eutrophic lake conditions, LC-PUFA content of the zooplankton consistently increased per unit biomass. The results indicate that the nutritional value of phytoplankton was highest in mesotrophic lakes, and lake zooplankton selectively increased their LC-PUFA retention with body size and/or were able to convert dietary FA endogenously to meet their size-specific FA demands, independent of lake location or time (season) or the measured trophic condition of the lake (from oligo- to eutrophic).

Investigating the Associations between Drought, Poverty, High-Risk Sexual Behaviours, and HIV Incidence in Sub-Saharan Africa: A Cross-Sectional Study

Climate change is increasing the likelihood of drought in sub-Saharan Africa, where HIV prevalence is high. Drought could increase HIV transmission through various mediating mechanisms; we investigated these associations. We used data on people aged 15-59 from Population-Based HIV Impact Assessment surveys from 2016 in Eswatini, Lesotho, Tanzania, Uganda, and Zambia. Survey data were geospatially linked to precipitation data for 2014-2016, with local droughts defined as cumulative rainfall between 2014 and 2016 being in < 15th percentile of all 2-year periods over 1981-2016. Using multivariable logistic regression, stratified by sex and rural/urban residence, we examined associations between (a) drought and poverty, (b) wealth quintiles and sexual behaviours (transactional, high-risk, and intergenerational sex), (c) sexual behaviours and recently acquiring HIV, and (d) drought and recent HIV. Among 102,081 people, 31.5% resided in areas affected by drought during 2014-2016. Experiencing drought was positively associated with poverty for women and men in rural, but not urban, areas. For each group, increasing wealth was negatively associated with transactional sex. For rural women, intergenerational sex was positively associated with wealth. Women reporting each sexual behaviour had higher odds of recent HIV, with strong associations seen for high-risk sex, and, for urban women, intergenerational sex, with weaker associations among men. Women in rural areas who had been exposed to drought had higher odds of having recently acquired HIV (2.10 [95%CI: 1.17-3.77]), but not women in urban areas, or men. Droughts could potentially increase HIV transmission through increasing poverty and then sexual risk behaviours, particularly among women in rural areas.

Geospatial prediction of total soil carbon in European agricultural land based on deep learning

Accurate geospatial prediction of soil parameters provides a basis for large-scale digital soil mapping, making efficient use of the expensive and time-consuming process of field soil sampling. To date, few studies have used deep learning for geospatial prediction of soil parameters, but there is evidence that it may provide higher accuracy compared to machine learning methods. To address this research gap, this study proposed a deep neural network (DNN) for geospatial prediction of total soil carbon (TC) in European agricultural land and compared it with the eight most commonly used machine learning methods based on studies indexed in the Web of Science Core Collection. A total of 6209 preprocessed soil samples from the Geochemical mapping of agricultural and grazing land soil (GEMAS) dataset in heterogeneous agricultural areas covering 4,899,602 km2 in Europe were used. Prediction was performed based on 96 environmental covariates from climate and remote sensing sources, with extensive comprehensive hyperparameter tuning for all evaluated methods. DNN outperformed all evaluated machine learning methods (R2 = 0.663, RMSE = 9.595, MAE = 5.565), followed by Quantile Random Forest (QRF) (R2 = 0.635, RMSE = 25.993, MAE = 22.081). The ability of DNN to accurately predict small TC values and thus produce relatively low absolute residuals was a major reason for the higher prediction accuracy compared to machine learning methods. Climate parameters were the main factors in the achieved prediction accuracy, with 23 of the 25 environmental covariates with the highest variable importance being climate or land surface temperature parameters. These results demonstrate the superiority of DNN over machine learning methods for TC prediction, while highlighting the need for more recent soil sampling to assess the impact of climate change on TC content in European agricultural land.

Economic losses caused by mastitis and the influence of climate variation on the occurrence of the disease in a dairy cattle farm in southern Brazil

This study evaluated the economic impacts caused by mastitis in a small dairy farm with similar characteristics and production to most dairy farms in southern Brazil and investigated if climatic variations influenced mastitis occurrence in the region. A farm with, on average, 45 lactating Holstein cattle was monitored from November 2021 to October 2022, and data on mastitis cases, bulk tank milk somatic cell count, animal treatment costs, milk production, animal disposal costs, and production losses were collected. Monthly averages of temperature, relative humidity (RH), and rainfall in the region were obtained. The greatest loss was related to the drop in milk production, resulting in 63.8% of total losses, followed by animal disposal (29.5%), milk disposal (4.6%), and treating animals with mastitis (2.0%), totaling a 10.6% reduction in the annual gross income. There were negative correlations between the clinical mastitis rate and monthly RH and between subclinical mastitis and temperature; the occurrence of subclinical mastitis and average RH were positively correlated. Our findings showed that mastitis negatively impacted the economy and that climate influenced mastitis occurrence.

Stabilizing machine learning prediction of dynamics: Novel noise-inspired regularization tested with reservoir computing

Recent work has shown that machine learning (ML) models can skillfully forecast the dynamics of unknown chaotic systems. Short-term predictions of the state evolution and long-term predictions of the statistical patterns of the dynamics ("climate") can be produced by employing a feedback loop, whereby the model is trained to predict forward only one time step, then the model output is used as input for multiple time steps. In the absence of mitigating techniques, however, this feedback can result in artificially rapid error growth ("instability"). One established mitigating technique is to add noise to the ML model training input. Based on this technique, we formulate a new penalty term in the loss function for ML models with memory of past inputs that deterministically approximates the effect of many small, independent noise realizations added to the model input during training. We refer to this penalty and the resulting regularization as Linearized Multi-Noise Training (LMNT). We systematically examine the effect of LMNT, input noise, and other established regularization techniques in a case study using reservoir computing, a machine learning method using recurrent neural networks, to predict the spatiotemporal chaotic Kuramoto-Sivashinsky equation. We find that reservoir computers trained with noise or with LMNT produce climate predictions that appear to be indefinitely stable and have a climate very similar to the true system, while the short-term forecasts are substantially more accurate than those trained with other regularization techniques. Finally, we show the deterministic aspect of our LMNT regularization facilitates fast reservoir computer regularization hyperparameter tuning.

Heatstroke presentations to urban hospitals during BC's extreme heat event: lessons for the future

BACKGROUND

Climate change is leading to more extreme heat events in temperate climates that typically have low levels of preparedness. Our objective was to describe the characteristics, treatments, and outcomes of adults presenting to hospitals with heatstroke during BC's 2021 heat dome.

METHODS

We conducted a review of consecutive adults presenting to 7 hospitals in BC's Lower Mainland. We screened the triage records of all patients presenting between June 25th and 30th, 2021 for complaints related to heat, and reviewed the full records of those who met heatstroke criteria. Our primary outcome was in-hospital mortality. We used Mann-Whitney U tests and logistic regression to investigate associations between patient and treatment factors and mortality.

RESULTS

Among 10,247 consecutive presentations to urban hospitals during the extreme heat event, 1.3% (139; 95% confidence intervals [CI] 1.1-1.6%) met criteria for heatstroke. Of heatstroke patients, 129 (90.6%) were triaged into the two highest acuity levels. Patients with heatstroke had a median age of 84.4 years, with 122 (87.8%) living alone, and 101 (84.2%) unable to activate 911 themselves. A minority (< 5, < 3.6%) of patients presented within 48 h of the onset of extreme heat. Most patients (107, 77.0%) required admission, and 11.5% (16) died in hospital. Hypotension on presentation was associated with mortality (odds ratio [OR] 5.3).

INTERPRETATION

Heatstroke patients were unable to activate 911 themselves, and most presented with a 48-h delay. This delay may represent a critical window of opportunity for pre-hospital and hospital systems to prepare for the influx of high-acuity resource-intensive patients.

Quantifying climate change impacts on future water resources and salinity transport in a high semi-arid watershed

High salinity mobilization and movement from salt-laden deposits in semi-arid landscapes impair soils and water resources worldwide. Semi-arid regions worldwide are expected to experience rising temperatures and lower precipitation, impacting water supply and spatio-temporal patterns of salinity loads and affecting downstream water quality. This study quantifies the impact of future climate on hydrologic fluxes and salt loads in the Gunnison River Watershed (GRW) (14,608 km2), Colorado, using the APEX-MODFLOW-Salt hydro-chemical watershed model and three different CMIP5 climate models projection downscaled by Multivariate Adaptive Constructed Analogs (MACA) for the period 2020-2099. The APEX-MODFLOW-Salt model accounts for the reactive transport of major salt ions (SO42-, Cl-, CO32-, HCO3-, Ca2+, Na+, Mg2+, and K+) to streams via surface runoff, rainfall erosional runoff, soil lateral flow, quick return flow and groundwater-stream exchange. Model results are analyzed for spatial and temporal trends in water yield and salt loading pathways. Although streamflow is primarily derived from surface runoff (65%), the predominant source of salt loads is the aquifer (73%) due to elevated concentrations of groundwater salt. Annual salt loading from the watershed is 582 Mkg, approximately 10% of the salt load in the Colorado River measured at Lee's Ferry, AZ. For future climate scenarios, annual salt loads from the watershed increased between 4.1% and 9.6% from the historical period due to increased salt loading from groundwater and quick return flow. From the results, applying the APEX-MODFLOW-Salt model with downscaled future climate forcings can be a helpful modeling framework for investigating hydrology and salt mobilization, transport, and export in historical and predictive settings for salt-affected watersheds.

Weather in two climatic regions shapes the diversity and drives the structure of fungal endophytic community of bilberry (Vaccinium myrtillus L.) fruit

BACKGROUND

Bilberry (Vaccinium myrtillus L.) is one of the most important economic and natural resources in Northern Europe. Despite its importance, the endophytic fungal community of the fruits has rarely been investigated. Biogeographic patterns and determinants of the fungal diversity in the bilberry fruit are poorly understood, albeit fungal endophytes can have a close relationship with the host plants. Here, we investigated the effect of climatic regions, and their weather conditions within growth season and soil properties on fungal endophytic communities of bilberry fruits collected from northern and southern regions of Finland using high-throughput sequencing technology targeting the internal transcribed spacer 2 ribosomal DNA region for fungi.

RESULTS

Species richness and beta diversity (variation in community structure) were higher in the southern compared to the studied northern region. The weather condition of the growth season drove both fungal richness and community structure. Furthermore, abundance of the genera Venturia, Cladosporium, and Podosphaera was influenced by the weather, being different between the south and north regions.

CONCLUSIONS

We conclude that diversity and assembly structure of the fungal endophytes in bilberry fruits follow similar patterns as for foliar fungal endophytes, being shaped by various environmental factors, such as the climate and surrounding vegetation.

Water stress changes the relationship between photosynthesis and stomatal conductance

Understanding the relationship between stomatal conductance (gs) and photosynthesis (An) under water stress conditions can improve the accuracy of land surface models for estimating the gas exchange of crop canopies with the atmosphere. However, little is known about the effect of water stress on this relationship in crops. A glasshouse experiment was, therefore, conducted to investigate changes in the linear relationship between gs and An owing to water stress in rice and the association with soil moisture content. Severe (SWS), mild (MWS), and no water stress (NWS) conditions were applied from flowering onwards and the gas exchange in fully developed flag leaves was assessed weekly. The Ball-Woodrow-Berry linear model was used to assess the relationship between gs and An under different treatments. SWS had a significant effect and reduced the slope of the linear relationship between gs and An by 30 % compared with NWS. Only in SWS were An and gs strongly correlated with soil water content. Our study revealed that changes in the linear relationship through a reduction in the slope imply a conservative water-use strategy for rice under intense water stress. We propose that crop models that use the linear relationship should consider the impact of water stress conditions when simulating yields and estimating CO2 and H2O fluxes from crop canopies.

Analysis of water quality influencing factors under multi-source data fusion based on PLS-SEM model: An example of East-Liao River in China

Owing to alterations in the environment and human activities, the quality of surface water is declining. Despite a substantial number of studies on the factors that impact water quality, there is still a need for a better understanding of the major causes of water quality degradation. This study fused multi-source data using partial least squares structural equation modeling to evaluate the effects of weather, soil composition, and geographical features on the water quality of the East Liao River (ELR), Jilin Province, China. The impacts of land-use practices on water quality at different buffer scales were analyzed. The most significant correlation between land use and water quality was observed at a distance of 4 km. The severity of water pollution was significantly influenced by soil type, with a path coefficient of 0.689 (p < 0.001). Conversely, landscape factors exhibited a notable adverse effect, indicated by a path coefficient of -0.608 (p < 0.001). Additionally, meteorological factors exhibited a significant impact, with a path coefficient of 0.463 (p < 0.001). The indirect effects of landscape elements on water quality were also examined. Water quality could be indirectly influenced by landscape through soil factors, as evidenced by a path coefficient of -0.572 (p < 0.01). In this study, new ideas for studying water quality drivers using multi-source data fusion are introduced. Managers can leverage the findings of this study to improve their decision-making and effectively address water quality issues in ELR located in Jilin Province, China.

Herb hydraulics: Variation and correlation for traits governing drought tolerance and efficiency of water transport

Hydraulic traits dictate plant response to drought, thus enabling better understanding of community dynamics under global climate change. Despite being intensively documented in woody species, herbaceous species (graminoids and forbs) are largely understudied, hence the distribution and correlation of hydraulic traits in herbaceous species remains unclear. Here, we collected key hydraulic traits for 436 herbaceous species from published literature, including leaf hydraulic conductivity (Kleaf), water potential inducing 50 % loss of hydraulic conductivity (P50), stomatal closure (Pclose) and turgor loss (Ptlp). Trait variation of herbs was analyzed and contrasted with angiosperm woody species within the existing global hydraulic traits database, as well as between different growth forms within herbs. Furthermore, hydraulic traits coordination was also assessed for herbaceous species. We found that herbs showed overall more negative Pclose but less negative Ptlp compared with angiosperm woody species, while P50 did not differ between functional types, regardless of the organ (leaf and stem). In addition, correlations were found between Kleaf and P50 of leaf (P50leaf), as well as between Pclose, P50leaf and Kleaf. Within herbs, graminoids generally exhibited more negative P50 and Ptlp, but lower Kleaf, relative to forbs. Within herbs, no clear pattern regarding hydraulic traits-climate relationship was found. Our analysis provided insights into herb hydraulic, and highlighted the knowledge gaps need to be filled regarding the response of herbs to drought.

Wheat yield response to elevated O3 concentrations differs between the world's major producing regions

Ground-level ozone (O3) concentration is rising in Asia, which accommodates the world's top-two wheat producers (China and India). Because wheat is among the species of high O3 sensitivity, yield loss due to rising O3 in Asia is a major threat to global wheat supply. We estimated the relationships between O3 dose on AOT40 (accumulated daytime O3 concentrations above 40 ppb for 90 days) and relative wheat yield for four wheat producing regions: China, India, Europe and North America using results of O3 elevation experiments conducted therein. When compared on the same AOT40, the estimated yield loss was greatest in China followed by India, Europe, and North America in this order. In China, Europe and North America, the yield loss was primarily due to the reduction of single grain weight, whereas in India reduction of the number of grains contributed more to the yield loss than single grain weight. The greater response of the number of grains to O3 in India can be explained by the earlier start of O3 elevation, but the seasonal change in O3 concentrations cannot explain the lower yield loss in North America than China and India. Referring to the past reports of lower yield sensitivity to O3 in older cultivars, we compared the year of release of cultivars between the regions. In North America, they used cultivars released in 1980s or earlier, whereas in China they used cultivars released in 2000s. In Europe and India, most cultivars were released between those in North America and China. The difference in cultivars could therefore be a cause the differential yield response among the regions. We argue that the O3-induced yield loss should be quantified using the dose-response relationships for each region accounting for the effects of seasonal change in O3 concentrations, cultivars and climate on the yield response.

Understanding faculty perceptions and experiences related to climate, diversity, equity, and inclusion at a college of pharmacy: A pilot study

INTRODUCTION

A climate survey was piloted to obtain an understanding of the perceptions and personal experiences of faculty for intentional planning of future meaningful, effective, and sustainable diversity, equity, and inclusion (DEI) efforts at a college of pharmacy.

METHODS

A 48-item, four section, online survey was developed and administered to 69 faculty between October and November 2021. Likert-like five-point scales and free-text items were included to determine an overall assessment of climate, as well as perceptions and/or personal experiences for each domain of DEI, and demographics.

RESULTS

Thirty-nine (57%) faculty completed the survey. For climate, every attribute had at least one respondent that observed someone make an insensitive or disparaging remark "rarely," "occasionally," and "frequently." The response pattern was similar for personal experience with insensitive remarks. For participation in diversity activities, "awareness without participation" was selected by 56% of respondents. For perceptions of diversity, "fairly" or "very" was selected by 38% to 54% of respondents. For equity, "attainable for some" to "not attainable" was identified for 15% to 26% of respondents.

CONCLUSIONS

These pilot climate survey results inform climate improvement as it relates to DEI and informs survey instrument refinement.

The response of heat shock proteins in honey bees to abiotic and biotic stressors

Honey bees, Apis mellifera, are the most important managed pollinators worldwide. They are highly impacted by various abiotic and biotic stressors, especially temperature extremes, which can lead to cellular damage and death. The induction of heat shock proteins (HSPs) has been recorded in honey bees as a response to various types of stressors. HSPs are classified into different gene families according to their molecular weights. HSPs play an important role in maintaining cellular protein homeostasis due to their contribution as molecular chaperones or co-chaperones. HSPs in honey bees have complex functions with induction even under normal colony conditions. Previous studies have suggested various functions of HSPs to protect cells from damage under exposure to environmental stressors, pollutants, and pathogens. Surprisingly, HSPs have also been found to play roles in larval development and age-related tasks. The expression of HSPs varies depending on tissue type, developmental stage, age, and stress period. This article reviews studies on HSPs (sHSPs, HSP40, HSP60, HSP70, and HSP90) in honey bees and highlights gaps in the available knowledge. This review is crucial for honey bee research, particularly in the face of climate change challenges.

Long-term oscillations in the normalized biomass-size spectrum reveal the impact of oligotrophication on zooplankton trophic structure in the North Atlantic Subtropical Gyre

Ocean warming of the North Atlantic Subtropical Gyre (NASG) induced oligotrophication and a decrease in integrated net primary production during the 2010s, potentially affecting higher trophic levels. We analyzed long-term records (1994-2019) of daytime and nighttime zooplankton biomass in five size classes from the NASG. Daytime biomass decreased in the three largest size classes during the 2010s, while decrease in nighttime biomass was less evident due to the relative stability in diel vertical migrator biomass. We used the normalized biomass size spectrum (NBSS) to estimate the relative transfer efficiency between trophic levels. The steepness of the NBSS slope at the end of the time series increased by 14% (daytime) and 24% (nighttime) from the maximum observed annual average values (2011 and 2009, respectively). This suggests oligotrophication during the 2010s led to a significant reduction in the transfer of biomass across trophic levels, with negative impacts on the NASG planktonic food web.

The association between climate and emergency department visits for renal and urinary disease in Charlottesville, Virginia

Diseases of the kidney and urinary tract impose a significant portion of the total disease burden, and linkages to high temperature exposure suggest that this burden may increase in the near future. We examined the association between climate and daily emergency department (ED) visits for kidney and urinary disease at the University of Virginia main hospital in Charlottesville, Virginia from 2005 to 2020. Generalized additive models and distributed lag nonlinear models were used to examine these associations over a 21-day lag period. After testing a variety of weather variables from observations taken at the Charlottesville, Albemarle County Airport weather station, 1 p.m. temperature was found to have the strongest association with ED visits for renal and urinary visits while controlling for seasonal and trend factors, air quality, day of the week, and wintry weather. The relative risk of ED visits exhibited a stronger association with high temperatures compared to low temperatures. The heat response was pronounced at short lags (0-1 days) with the relative risk (RR) increasing when 1 p.m. temperatures exceeded 20°C and peaking at 29°C (RR = 1.28). By comparison, low temperatures (≤0°C) exhibited a negative association (RR = 0.80 at -10°C) at short lags (0-1 day), with evidence of a weak RR increase at lags of 2-3 and 9-14 days. These results for ED visitation are consistent with other studies linking high temperatures to acute kidney injury, chronic kidney disease, the development of kidney stones, and other associated illnesses. A better understanding of the impact of temperature extremes in generating or exacerbating existing conditions could assist medical health professionals in the prevention and management of these diseases during extreme weather events.

Single-use accessories and endoscopes in the era of sustainability and climate change-A balancing act

Gastrointestinal (GI) endoscopy is among the highest waste generator in healthcare facilities. The major reasons include production of large-volume non-renewable waste, use of single-use devices, and reprocessing or decontamination processes. Single-use endoscopic accessories have gradually replaced reusable devices over last two decades contributing to the rising impact of GI endoscopy on ecosystem. Several reports of infection outbreaks with reusable duodenoscopes raised concerns regarding the efficacy and adherence to standard disinfection protocols. Even the enhanced reprocessing techniques like double high-level disinfection have not been found to be the perfect ways for decontamination of duodenoscopes and therefore, paved the way for the development of single-use duodenoscopes. However, the use of single-use endoscopes is likely to amplify the net waste generated and carbon footprint of any endoscopy unit. Moreover, single-use devices challenge one of the major pillars of sustainability, that is, "reuse." In the era of climate change, a balanced approach is required taking into consideration patient safety as well as financial and environmental implications. The possible solutions to provide optimum care while addressing the impact on climate include selective use of disposable duodenoscopes and careful selection of accessories during a case. Other options include use of disposable endcaps and development of effective high-level disinfection techniques. The collaboration between the healthcare professionals and the manufacturers is paramount for the development of environmental friendly devices with low carbon footprint.

Contrasting compositions of PM2.5 in Northern Thailand during La Niña (2017) and El Niño (2019) years

There have been a very limited number of systematic studies on PM2.5 compositions and their source contribution in Southeast Asia. This study aims to explore the characteristics of PM2.5 composition collected in Chiang Mai (Thailand) during La Niña and El Niño years and to apportion their sources during smoke haze and non-haze periods. The average PM2.5 concentration of smoke haze episode in 2019 (El Niño) was much higher than in 2017 (La Niña). The ratios of organic carbon (OC) to elemental carbon (EC), as well as K (biomass burning (BB) tracer) to PM2.5, were higher during smoke haze episodes in 2019 than in 2017 indicating a significant influence from BB. The ratios of secondary organic carbon (SOC) levels to primary organic carbon (POC) levels during smoke haze episodes were higher than those in non-haze period, which indicated greater SOC contributions or more photo-oxidation of precursors in haze episodes with high ambient temperatures. However, the ratios of soil markers (Ca and Mg) during non-haze period were high implying that soil source contributed more to PM2.5 concentrations when there less BB occurred. The positive Matrix Factorization (PMF) model revealed that the source of BB, characterized by high K fractions, was the largest contributor during smoke haze episodes accounting for 50% (2017) and 79% (2019). Climate conditions influence meteorological patterns, particularly during incidences of extreme weather such as droughts, which affect the scale and frequency of open burning and thus air pollution levels.

Ambient temperature and kidney function in primary care patients

INTRODUCTION

Exposure to high ambient temperatures is associated with a risk of acute kidney injury. However, evidence comes from emergency departments or extreme weather exposures. It is unclear whether temperature-related adverse kidney outcomes can also be detected at a community level in a temperate climate zone.

METHODS

In a 9.5-year retrospective cohort study we correlated estimated glomerular filtration rate (eGFR) values of Swiss adult primary care patients from the FIRE cohort (Family medicine Research using Electronic medical records) with same-day maximum local ambient temperature data. We investigated 5 temperature groups (< 15 °C, 15-19 °C, 20-24 °C, 25-29 °C and  ≥ 30 °C) as well as possible interactions for patients with increased kidney vulnerability (chronic heart failure, diabetes, chronic kidney disease, therapy with renin-angiotensin-aldosterone-system (RAAS) inhibitors, diuretics or non-steroidal anti-inflammatory drugs).

RESULTS

We included 18,000 primary care patients who altogether provided 132,176 creatinine measurements. In the unadjusted analysis, higher ambient temperatures were associated with lower eGFR across all age and vulnerability groups. In the adjusted models, we did not find a consistent association.The highest ambient temperature differences (> 25 or > 30 versus < 15 °C) were associated with marginally reduced kidney function only in patients with ≥ 3 risk factors for kidney vulnerability, with a maximum estimated glomerular filtration rate reduction of -2.9 ml/min/1.73m2 (SE 1.0), P 0.003.

DISCUSSION

In a large primary care cohort from a temperate climate zone, we did not find an association between ambient temperatures and kidney function. A marginal inverse association in highly vulnerable patients is of unclear clinical relevance.

Heat-shock proteins, oxidative stress, and antioxidants in one-humped camels

One-humped camels (Camelus dromedarius) exhibit remarkable adaptability to harsh desert environments through various physiological adaptations. This study aimed to assess variations and reference values of Heat-shock proteins (HSPs), physiological parameters, mineral concentrations, total antioxidant capacity (TAC), and malondialdehyde (MDA) in 90 healthy female one-humped camels from Zabol's outskirts in Iran. The objective was to understand how these camels adapt to heat stress. Blood samples were collected from camels located at five geographical regions and analyzed using standard kits and methods. Reference intervals for heat-shock protein 30 (HSP30), heat-shock protein 40 (HSP40), heat-shock protein 70 (HSP70), and heat-shock protein 90 (HSP90) were determined using the reference value advisor (RVA). The study found significant differences among different regions for HSPs (P < 0.05), MDA (P = 0.021), and TAC (P = 0.042) levels, indicating variations in adaptation mechanisms. However, no notable differences were observed for other measured parameters between these regions. There were no significant differences observed in the evaluated parameters between the age categories of > 36 months and < 36 months. The positive correlation between HSPs and MDA levels (ranging from 0.754 to 0.884) suggests that the synthesis of HSPs is triggered as a response to oxidative stress caused by an imbalance between the production of reactive oxygen species (ROS) and the body's antioxidant defenses. This oxidative stress, in turn, is a consequence of thermal stress. Additionally, the study reveals a negative association between TAC and HSP levels (ranging from - 0.660 to - 0.820), emphasizing the role of antioxidants in mitigating heat stress. The findings of this research offer compelling support for the critical role that HSPs play in protecting cells from heat-induced damage. Additionally, the presence of higher levels of HSPs in regions with more severe climate conditions serves as evidence of camels' adaptation to heat stress. These findings emphasize the substantial impact of environmental factors on HSP production and further reinforce the crucial role of HSPs in bolstering the resilience of camels. Further research is needed to explore HSP expression and mechanisms to effectively manage and enhance camel resilience in extreme temperatures.

Short-term mediating effects of PM2.5 on climate-associated COPD severity

The impact of short-term exposure to environmental factors such as temperature, relative humidity (RH), and fine particulate matter (PM2.5) on chronic obstructive pulmonary disease (COPD) remains unclear. The objective of this study is to investigate PM2.5 as a mediator in the relationship between short-term variations in RH and temperature and COPD severity. A cross-sectional study was conducted on 930 COPD patients in Taiwan from 2017 to 2022. Lung function, COPD Assessment Test (CAT) score, and modified Medical Research Council (mMRC) dyspnea scale were assessed. The mean and differences in 1-day, 7-day, and 30-day individual-level exposure to ambient RH, temperature, and PM2.5 were estimated. The associations between these factors and clinical outcomes were analyzed using linear regression models and generalized additive mixed models, adjusting for age, sex, smoking, and body mass index. In the total season, increases in RH difference were associated with increases in forced expiratory volume in 1 s (FEV1) / forced vital capacity (FVC), while increases in temperature difference were associated with decreases in FEV1 and FEV1/FVC. Increases in PM2.5 mean were associated with declines in FEV1. In the cold season, increases in temperature mean were associated with decreases in CAT and mMRC scores, while increases in PM2.5 mean were associated with declines in FEV1, FVC, and FEV1/FVC. In the warm season, increases in temperature difference were associated with decreases in FEV1 and FEV1/FVC, while increases in RH difference and PM2.5 mean were associated with decreases in CAT score. PM2.5 fully mediated the associations of temperature mean with FEV1/FVC in the cold season. In conclusion, PM2.5 mediates the effects of temperature and RH on clinical outcomes. Monitoring patients during low RH, extreme temperature, and high PM2.5 levels is crucial. Capsule of findings The significance of this study is that an increase in ambient RH and temperature, as well as PM2.5 exposure, were significantly associated with changes in lung function, and clinical symptoms in these patients. The novelty of this study is that PM2.5 plays a mediating role in the association of RH and temperature with COPD clinical outcomes in the short term.

Epigenetics of the far northern Yakutian population

BACKGROUND

Yakuts are one of the indigenous populations of the subarctic and arctic territories of Siberia characterized by a continental subarctic climate with severe winters, with the regular January average temperature in the regional capital city of Yakutsk dipping below - 40 °C. The epigenetic mechanisms of adaptation to such ecologies and environments and, in particular, epigenetic age acceleration in the local population have not been studied before.

RESULTS

This work reports the first epigenetic study of the Yakutian population using whole-blood DNA methylation data, supplemented with the comparison to the residents of Central Russia. Gene set enrichment analysis revealed, among others, geographic region-specific differentially methylated regions associated with adaptation to climatic conditions (water consumption, digestive system regulation), aging processes (actin filament activity, cell fate), and both of them (channel activity, regulation of steroid and corticosteroid hormone secretion). Further, it is demonstrated that the epigenetic age acceleration of the Yakutian representatives is significantly higher than that of Central Russia counterparts. For both geographic regions, we showed that epigenetically males age faster than females, whereas no significant sex differences were found between the regions.

CONCLUSIONS

We performed the first study of the epigenetic data of the Yakutia cohort, paying special attention to region-specific features, aging processes, age acceleration, and sex specificity.

Associations between season, climate, and pediatric alopecia areata flares in Providence, Rhode Island

Patients with alopecia areata (AA) may experience episodic hair loss that follows seasonal patterns. To assess associations between seasonal variation, climate factors, and AA flare frequency in pediatric AA patients, we performed a retrospective chart review of 123 pediatric AA patients at Brown Dermatology (Providence, Rhode Island) who experienced hair loss between January 2017 and December 2019. We assessed association of seasonal variation with monthly occurrence of AA flares. We then assessed association between climate variables and monthly AA hair loss frequency using Spearman rank correlation analyses. We conducted stratified analyses in patients with and without history of atopy. The greatest proportion of hair loss episodes occurred in winter (28.1%), followed by autumn (26.3%), spring (23.8%), and summer (21.7%). We found significant correlations between AA hair loss frequency and air pressure (R = 0.61) and hours of sunlight (R = - 0.60). These correlations remained significant among patients with no history of atopic disease but were not significant among those with history of atopy. Limitations include small sample size. This regional analysis supports the role of climate in AA hair loss episodes through assessment of seasonal occurrences and identification of correlations between climate characteristics and AA flare frequency.

Determining the effect of climate and profession on dry eye disease: A prevalence study among young males in north, north-west and central India

Background

Ocular tear film and the ocular surface together represent a dynamic playground of various protective factors against environmental influencers. Surrounding environment and geoclimatic milieu are the pertinent and continuous influencing factors. Prevalence study of Dry eye disease (DED) in various climatic conditions and professions provides an insight into this peculiar aspect of DED and human geography.

Methods

This was a hospital based, cross-sectional, comparative, analytical observational study. 1840 young soldiers between 25 and 45 years of age were studied. Divided in five climate groups based on Köppen-Geiger climate classification system the subjects were sub-grouped into professions exposed to known aggravating environmental factors. The ocular surface was examined for signs and symptoms of DED and its prevalence and risk ratio for different climates and professions were calculated.

Results

Highest prevalence of DED was found in cold desert climate and among visual display unit (VDU) users. Least prevalence was seen in highland type of climate and among people involved in professional exposed to high temperature. Prevalence of DED based upon the signs and ocular surface disease index (OSDI) was calculated and stratified with risk ratio for climatic conditions and professions.

Conclusion

Different climatic conditions and professions had different prevalence of signs, symptoms of OSD and DED which indicated its influence on prevalence of the disease.

Do ticks exhibit repeatable individual behaviors?

Diseases caused by ticks are often addressed as a traditional epidemiological mathematical puzzle, i.e., how many identical infected vectors, how many uniform potential hosts, and a dependable rate of transmission, etc. Although often useful at the population level, at the individual level disease transmission occurs when one tick bites one person. Just as we assign agency to people in their outdoor behavior and use of prophylactics against arthropods, perhaps we should also see ticks as individual actors? Are all ticks automatons that just quest and attach, or do they exhibit repeatable individual behaviors that affect transmission? We wanted to determine whether Dermacentor andersoni and D. variabilis adult ticks exhibited repeatable behaviors in four experiments. The experiments focused on left/right movement, attraction to CO2, photophilic tendencies, and avoidance of a repellant. We hypothesized that over two seasons we would find repeatable behavior patterns. In 2021, but not 2022, we found that within an experiment, individuals exhibited repeatable behaviors between trials and between experiments, i.e., if an animal showed repeatable 'adventurous' behavior in one experiment, this predicted adventurous behavior in a separate experiment. This strong evidence of predictable trait-like behavior was present in 2021 but was absent when we repeated the same experiments, with the same collection site, in 2022. This illustrates the importance of multiyear experimentation when testing for repeatable individual behaviors. Incidental to the study, we also observed that a major heat wave in 2021 altered the tick species composition (toward a more dry-adapted population) at our study site.

Developing an efficient climate forecasting model for the spatiotemporal climate dynamics estimation and the prediction that fits the variable topography feature of the upper Blue Nile basin, Ethiopia

The spatiotemporal climate estimation and prediction are challenging and demanding for variable topography feature areas. Spatially, the upper Blue Nile basin (UBNB) is unsatisfactory owing to complex topographical features and the lack of accurate climate prediction and estimation models. Yet accurate information and reliable seasonal climate dynamics estimation and forecasting are essential in the region for controlling reservoir operation and flooding prevention. However, there is a lack of reports regarding the accuracy and predictability of the climate in the UBNB region. Therefore, this article aims to improve the Artificial Neural Network (ANN) model by adopting the Impulse Response Function (IRF) and comparing it to the Regional Climate Model (RCM) and European Centre of Medium-range Weather Forecast (ECMWF) models for spatiotemporal climate dynamics estimation and forecasting, which are reliant on the UBNB topography features. Different atmospheric parameter data are investigated from reanalysis models. A fast Fourier transform is applied to remove the redundancy of the data and avoid the computational cost. The RCM and ECMWF models are used to test the performance of ANN model prediction skills. The IRF model was applied to enhance the ANN model's climate prediction performance. A 12-month spatial variation of precipitation is analyzed. The ANN model showed a satisfactory prediction performance, better than the RCM and ECMWF models by 20 %. After increasing the ANN model performance by IRF, the prediction errors are reduced by 10.2 % for precipitation and by 7.9 % for temperature. Based on the model results, the temperature has increased over the past 40 years and is expected to continue for the coming three decades (30 years). In contrast, precipitation over the past 40 years has decreased, and a slight increment will be expected in the next eight years, from 2024 to 2029. Therefore, this model should be practiced across Ethiopia and the Globe for accurate prediction of climate patterns. Hence, clear awareness should be created for the local community by providing a scientific remedy for future climate conditions to reduce production risk.