Rising frequency of ozone-favorable synoptic weather patterns contributes to 2015-2022 ozone increase in Guangzhou.

Objective weather classification methods have been extensively applied to identify dominant ozone-favorable synoptic weather patterns (SWPs), however, the consistency of different classification methods is rarely examined. In this study, we apply two widely-used objective methods, the self-organizing map (SOM) and K-means clustering analysis, to derive ozone-favorable SWPs at four Chinese megacities in 2015-2022. We find that the two algorithms are largely consistent in recognizing dominant ozone-favorable SWPs for four Chinese megacities. In the case of classifying six SWPs, the derived circulation fields are highly similar with a spatial correlation of 0.99 between the two methods, and the difference in the mean frequency of each SWP is less than 7%. The six dominant ozone-favorable SWPs in Guangzhou are all characterized by anomaly higher radiation and temperature, lower cloud cover, relative humidity, and wind speed, and stronger subsidence compared to climatology mean. We find that during 2015-2022, the occurrence of ozone-favorable SWPs days increases significantly at a rate of 3.2 day/year, faster than the increases in the ozone exceedance days (3.0 day/year). The interannual variability between the occurrence of ozone-favorable SWPs and ozone exceedance days are generally consistent with a temporal correlation coefficient of 0.6. In particular, the significant increase in ozone-favorable SWPs in 2022, especially the Subtropical High type which typically occurs in September, is consistent with a long-lasting ozone pollution episode in Guangzhou during September 2022. Our results thus reveal that enhanced frequency of ozone-favorable SWPs plays an important role in the observed 2015-2022 ozone increase in Guangzhou.

Adverse health effects of climate change and air pollution in people with disabilities: a systematic review.

Global warming and air pollution adversely affect the health of the entire human population, particularly older adults, people with disabilities (PWDs), and children. In this systematic review, we investigated the adverse health effects of climate change and air pollution in PWDs. We conducted a comprehensive literature search of the PubMed database using the terms "disab*," "air pollution," and "climate change" on July 4, 2023, and August 8, 2023 and searched the Web of Science (WOS) database on December 28, 2023. We identified 425 and 1169 studies on climate change cited in PubMed and WOS, respectively, as well as 333 studies on air pollution in PubMed and 495 studies on air pollution in WOS. The studies were classified by type of exposure, and full-text screening was conducted to confirm that the population, intervention or exposure, comparator, outcome statement, and inclusion and exclusion criteria were met. The Newcastle-Ottawa Scale was used to assess the quality of the included cohort and case-control studies and for data analysis. In extreme temperatures, PWDs experienced higher rates of injury, heat-related illness, functional impairment, heart disease, mental disorders, and mortality than people who were nondisabled (ND). Exposure to air pollution resulted in higher rates of obesity, cardiovascular disease, poststroke neurological and functional disability, and mortality in PWDs than in people who were ND. Therefore, because PWDs were more affected by climate change and air pollution than people who were ND, sensitive policies and preparedness measures should be developed for PWDs.

Integrating user- and data-driven weather forecasts to develop legitimate, credible, and salient information services for smallholders in the Global South.

Climate-related risks and variability pose significant challenges to the livelihoods and food security of smallholder farmers practicing rainfed agriculture. Many smallholders have limited access to weather information from climate services, and this information is often not tailored to their specific context and needs. Therefore, they rely on local ecological knowledge. This study utilizes the second generation of climate services, which provide demand-driven forecast information systems through mobile apps. We present three cases from agricultural communities in Guatemala, Bangladesh, and Ghana where we collaborated with farmers to develop local weather forecasts (LF) and combined them with scientific weather forecasts (SF) to create hybrid weather forecasts (HF). The integration of user-driven forecasts (LF) and data-driven forecasts (SF) enhances the legitimacy of the service, thereby increasing farmers' trust and credibility by providing skilful forecasts. Furthermore, our results demonstrate that the hybrid weather forecast approach facilitates climate-smart, adaptive agricultural decision-making, enhancing the resilience and capacity of smallholder farmers in the Global South to adapt to a changing climate.

Does the Change of Weather Influence Disease Activity in Rheumatoid Arthritis Patients: Patients' Self-Assessment via WebApp.

Objectives: The aim was to evaluate the influence of weather parameters on disease activity assessed by Routine Assessment of Patient Index Data (RAPID) scores via a Web-based smartphone application (WebApp). Methods: Correlation of changes of temperature (change of temperature, °C) and air pressure (change of air pressure, hPa) two days prior to and weekly self-assessment of disease activity by RAPID-3 scores over three months. To define background noise and quadrants of weather changes, we defined a central quadrant ± 2 hPa and ± 2° C, called E1. Based on this inner square, four quadrants were defined: A1 = sector left side above with increasing temperature and air pressure (improving weather); B1 = sector right side above; C1 = decreasing temperature and air pressure sector right side down (worsening weather); and D1 = sector left side down. Alterations of RAPID-3 scores analyzed changes in disease activity compared to RAPID-3 scores detected one week in advance. Results: Eighty patients were included in the analysis (median RA duration, 4.5 years; age, 57 years; 59% female). Median disease activity was 2.8 as assessed by DAS 28. In total, 210 time points were analyzed for quadrant A1, 164 for quadrant B1, 160 for quadrant C1, 196 for quadrant D1, and 145 for the inner square E1 were found during follow-up. The middle square E1 was balanced between increasing or decreasing values for RAPID scores. The odds for increasing RAPID scores were 1.33 (95% confidence interval CI: 1.0-1.78) for patients with ameliorating weather conditions which improve or alleviate unfavorable or adverse conditions (A1) compared to 0.98 (CI: 0.67-1.45) for worsening weather (C1) as defined by temperature and air pressure. Conclusions: On average, more patients developed a slight increase of disease activity if they were in the quadrant with increasing temperature and air pressure (improving weather). Thus, no correlation between the worsening of the weather and changing RAPID-3 scores was found.

LiDAR-Based Snowfall Level Classification for Safe Autonomous Driving in Terrestrial, Maritime, and Aerial Environments.

Studies on autonomous driving have started to focus on snowy environments, and studies to acquire data and remove noise and pixels caused by snowfall in such environments are in progress. However, research to determine the necessary weather information for the control of unmanned platforms by sensing the degree of snowfall in real time has not yet been conducted. Therefore, in this study, we attempted to determine snowfall information for autonomous driving control in snowy weather conditions. To this end, snowfall data were acquired by LiDAR sensors in various snowy areas in South Korea, Sweden, and Denmark. Snow, which was extracted using a snow removal filter (the LIOR filter that we previously developed), was newly classified and defined based on the extracted number of snow particles, the actual snowfall total, and the weather forecast at the time. Finally, we developed an algorithm that extracts only snow in real time and then provides snowfall information to an autonomous driving system. This algorithm is expected to have a similar effect to that of actual controllers in promoting driving safety in real-time weather conditions.

Changes in meteorological conditions as near-term risk factors for suicide attempts.

To evaluate the impact of acute meteorological changes (i.e., maximum temperature, humidity, wind speed, atmospheric pressure, cloud coverage, visibility, precipitation) as situational risk factors proximal (i.e., present in the hours directly preceding) to suicide attempts. Participants were 578 adult patients who were hospitalized within 24 h of a suicide attempt at the only Level 1 trauma hospital in the state of Mississippi. Participants completed a semi-structured interview to determine home address and exact timing of their suicide attempt. A within-person, case-crossover design was used with each patient serving as their own control. Meteorological variables were generated for the 6-hours preceding each patient's suicide attempt (case period) and corresponding hours the day prior (control period). Conditional logistic regression analyses were used to examine predictors of suicide attempts, and biological sex and season were evaluated as potential moderators. The presence of precipitation was associated with reduced odds of suicide attempts. Wind speed was marginally positively associated with suicide attempts among males, and visibility was positively associated with suicide attempts among females. Maximum temperature was positively associated with suicide attempts in the spring. Wind speed, visibility, maximum temperature, and precipitation (absence of) may represent situational risk factors for suicide attempts. Future studies should evaluate additional near-term situational risk factors and determine how to leverage this information to improve suicide risk management efforts to ultimately ameliorate the burden of suicide.

Bivalves under extreme weather events: A comparative study of five economically important species in the South China sea during marine heatwaves.

Marine heatwaves (MHWs) are increasing in frequency and intensity, threatening marine organisms and ecosystems they support. Yet, little is known about impacts of intensifying MHWs on ecologically and economically important bivalves cultured in the South China Sea. Here, we compared survival and physiological responses of five bivalve species, Pinctada fucata, Crassostrea angulata, Perna viridis, Argopecten irradians and Paphia undulata, to two consecutive MHWs events (3 days of thermal exposure to + 4 °C or + 8 °C, following 3 days of recovery under ambient conditions). While P. fucata, P. viridis, and P. undulata are native to the South China Sea region, C. angulata and A. irradians are not. Individuals of P. fucata, C. angulata and P. viridis had higher stress tolerance to MHWs than A. irradians and P. undulata, the latter already experiencing 100% mortality under +8 °C conditions during the first event. With increasing intensity of MHWs, standard metabolic rates of all five species increased significantly, in line with significant depressions of function-related energy-metabolizing enzymes (CMA, NKA, and T-ATP). Likewise, activities of antioxidant enzymes (SOD, CAT, and MDA) and shell mineralization-related enzymes (AKP and ACP) responded significantly to MHWs, despite species-specific performances observed. These findings demonstrate that some bivalve species can likely fail to accommodate intensifying MHWs events in the South China Sea, but some may persist. If this is the case, then one would expect substantial loss of fitness in bivalve aquaculture in the South China Sea under intensifying MHWs conditions.

Progression of Gummy Stem Blight Epidemics on Watermelon with and without Fungicide Inputs.

Gummy stem blight (GSB), caused primarily by the fungus Stagonosporopsis citrulli in the southeastern United States, affects cucurbits and is particularly destructive on watermelon. Previous epidemiological models of GSB constructed for greenhouse cucumber showed leaf wetness and temperature were the primary and secondary environmental factors, respectively, that explained epidemic progress. The objective of this study was to construct a model that predicted GSB severity on field-grown watermelon based on environmental factors. Disease and weather data from six fungicide experiments in Charleston, South Carolina, in spring and fall 1997 and fall 2017, 2018, 2019, and 2022 were used as inputs. Fungicide treatments were grouped into nonsprayed, protectant (chlorothalonil and mancozeb) and GSB-specific (cyprodinil, difenoconazole and fludioxonil) applications. Cumulative hours of leaf wetness was the primary explanatory variable that modeled the increase in proportion GSB severity ≥2% across all epidemics. Incorporation of temperature or other environmental variables did not improve the model. Fit of the overall model was evaluated with k-fold cross validation, where individual experiments were each excluded from the model fitting process. Slopes of predicted disease progress curves were lowered significantly compared to the nonsprayed treatments by applications of protectant fungicides. Applying GSB-specific fungicides alternated with chlorothalonil further reduced slope values. The model successfully predicted progress of GSB epidemics under different weather patterns and fungicide applications.

Association between detection rate of norovirus GII and climatic factors in the Northwest Amazon region.

Worldwide, approximately one fifth of all cases of diarrhea are associated with norovirus, mainly in children, with a defined seasonality in temperate climates, but seasonal dynamics are less known in tropical climates. The objective was to investigate the impact of external clinical, epidemiological, and climatic factors on norovirus detection rates in samples from children under 5 years of age from Roraima, the Amazon region of Brazil. A total of 941 samples were included. According to climatic factors, we observed correlations between external climatic factors and weekly positivity rates, where temperature (P = 0.002), relative humidity (P = 0.0005), absolute humidity (P < 0.0001) and wind speed had the strongest effect (P = 0.0006). The Brazilian Amazon region presents a typical and favorable scenario for the persistence, expansion, and distribution of viral gastroenteritis. Importance: This study is important as it will serve as a basis for studies carried out in Brazil and Latin American countries on the epidemiological importance, seasonality, climate change, antigenic diversity, among other factors in the circulation of gastroenteric virus.

[Four cases of occupational heatstroke among sanitation workers working in high temperature weather].

Through the report of 4 cases of occupational heatstroke among sanitation workers working in high-temperature weather, this study analyzes the risk of occupational heatstroke among workers in the environmental sanitation industry working in high-temperature weather, and provides scientific suggestions for standardizing occupational health management, safeguarding the health rights and interests of workers, and preventing the occurrence of occupational heatstroke in summer. Through case analysis, we aim to raise high awareness of the occupational health of sanitation workers in the whole society, in order to provide a scientific and healthy working environment for sanitation workers and promote their physical and mental health.

The Prognostic Effect of Air Pollution in Patients Presenting to the Emergency Department with Carbon Monoxide Poisoning.

OBJECTIVE: Weather conditions such as low air temperatures, low barometric pressure, and low wind speed have been linked to more cases of carbon monoxide (CO) poisoning. However, limited literature exists regarding the impact of air pollution. This study aims to investigate the relationship between outdoor air pollution and CO poisoning in 2 distinct cities in Turkey. METHODS: A prospective study was conducted at 2 tertiary hospitals, recording demographic data, presenting complaints, vital signs, blood gas and laboratory parameters, carboxyhemoglobin (COHb) levels, meteorological parameters, and pollutant parameters. Complications and outcomes were also documented. RESULTS: The study included 83 patients (Group 1 = 44, Group 2 = 39). The air quality index (AQI) in Group 2 (61.7 ± 27.7) (moderate AQI) was statistically significantly higher (dirtier AQI) than that in Group 1 (47.3 ± 26.4) (good AQI) (P = 0.018). The AQI was identified as an independent predictor for forecasting the need for hospitalization (OR = 1.192, 95% CI: 1.036 - 1.372, P = 0.014) and predicting the risk of developing cardiac complications (OR: 1.060, 95% CI: 1.017 - 1.104, P = 0.005). CONCLUSIONS: The AQI, derived from the calculation of 6 primary air pollutants, can effectively predict the likelihood of hospitalization and cardiac involvement in patients presenting to the emergency department with CO poisoning.

Understanding Barriers and Facilitators to Disaster Preparedness in Federally Qualified Health Centers in the United States: A Mixed Methods Study.

OBJECTIVE: Severe weather events exacerbate existing health disparities due to poorly managed non-communicable diseases (NCDs). Our objective is to understand the experiences of staff, providers, and administrators (employees) of Federally Qualified Health Centers (FQHCs) in Puerto Rico and the US Virgin Islands (USVI) in providing care to patients living with NCDs in the setting of recent climate-related extreme events. METHODS: We used a convergent mixed-methods study design. A quantitative survey was distributed to employees at 2 FQHCs in Puerto Rico and the USVI, assessing experience with disasters, knowledge of disaster preparedness, the relevance of NCDs, and perceived gaps. Qualitative in-depth interviews explored their experience providing care for NCDs during recent disasters. Quantitative and qualitative data were merged using a narrative approach. RESULTS: Through the integration of quantitative and qualitative data, we recognize: (1) significant gaps in confidence and preparedness of employees with a need for more training; (2) challenges faced by persons with multiple NCDs, especially cardiovascular and mental health disorders; and (3) most clinicians do not discuss disaster preparedness with patients but recognize their important role in community resilience. CONCLUSION: With these results, we recommend strengthening the capacity of FQHCs to address the needs of their patients with NCDs in disasters.

Prioritizing social vulnerability in urban heat mitigation.

We utilized city-scale simulations to quantitatively compare the diverse urban overheating mitigation strategies, specifically tied to social vulnerability and their cooling efficacies during heatwaves. We enhanced the Weather Research and Forecasting model to encompass the urban tree effect and calculate the Universal Thermal Climate Index for assessing thermal comfort. Taking Houston, Texas, and United States as an example, the study reveals that equitably mitigating urban overheat is achievable by considering the city's demographic composition and physical structure. The study results show that while urban trees may yield less cooling impact (0.27 K of Universal Thermal Climate Index in daytime) relative to cool roofs (0.30 K), the urban trees strategy can emerge as an effective approach for enhancing community resilience in heat stress-related outcomes. Social vulnerability-based heat mitigation was reviewed as vulnerability-weighted daily cumulative heat stress change. The results underscore: (i) importance of considering the community resilience when evaluating heat mitigation impact and (ii) the need to assess planting spaces for urban trees, rooftop areas, and neighborhood vulnerability when designing community-oriented urban overheating mitigation strategies.

Seasonal patterns of influenza incidence and the influence of meteorological and air pollution factors in Thailand during 2009-2019.

Influenza, an acute respiratory illness, remains a significant public health challenge, contributing substantially to morbidity and mortality worldwide. Its seasonal prevalence exhibits diversity across regions with distinct climates. This study aimed to explore the seasonal patterns of influenza and their correlation with meteorological and air pollution factors across six regions of Thailand. We conducted an analysis of monthly average temperature, relative humidity, precipitation, PM10, NO2, O3 concentrations, and influenza incidence data from 2009 to 2019 using wavelet analysis. Our findings reveal inconsistent biannual influenza prevalence patterns throughout the study period. The biannual pattern emerged during 2010-2012 across all regions but disappeared during 2013-2016. However, post-2016, the biannual cycles resurfaced, with peaks occurring during the rainy and winter seasons in most regions, except for the southern region. Wavelet coherence reveals that relative humidity can be the main influencing factor for influenza incidence over a one-year period in the northern, northeastern, central, Bangkok-metropolitan, and eastern regions, not in the southern region during 2010-2012 and 2016-2018. Similarly, precipitation can drive the influenza incidence at the same period for the northeastern, central, Bangkok-metropolitan, and eastern regions. PM10 concentration can influence influenza incidence over a half-year period in the northeastern, central, Bangkok-metropolitan, and eastern regions of Thailand during certain years. These results enhance our understanding of the temporal dynamics of influenza seasonality influenced by weather conditions and air pollution over the past 11 years. Such knowledge is invaluable for resource allocation in clinical settings and informing public health strategies, particularly in navigating Thailand's climatic complexities.

Existing evidence on the effects of climate variability and climate change on ungulates in North America: a systematic map.

BACKGROUND: Climate is an important driver of ungulate life-histories, population dynamics, and migratory behaviors. Climate conditions can directly impact ungulates via changes in the costs of thermoregulation and locomotion, or indirectly, via changes in habitat and forage availability, predation, and species interactions. Many studies have documented the effects of climate variability and climate change on North America's ungulates, recording impacts to population demographics, physiology, foraging behavior, migratory patterns, and more. However, ungulate responses are not uniform and vary by species and geography. Here, we present a systematic map describing the abundance and distribution of evidence on the effects of climate variability and climate change on native ungulates in North America. METHODS: We searched for all evidence documenting or projecting how climate variability and climate change affect the 15 ungulate species native to the U.S., Canada, Mexico, and Greenland. We searched Web of Science, Scopus, and the websites of 62 wildlife management agencies to identify relevant academic and grey literature. We screened English-language documents for inclusion at both the title and abstract and full-text levels. Data from all articles that passed full-text review were extracted and coded in a database. We identified knowledge clusters and gaps related to the species, locations, climate variables, and outcome variables measured in the literature. REVIEW FINDINGS: We identified a total of 674 relevant articles published from 1947 until September 2020. Caribou (Rangifer tarandus), elk (Cervus canadensis), and white-tailed deer (Odocoileus virginianus) were the most frequently studied species. Geographically, more research has been conducted in the western U.S. and western Canada, though a notable concentration of research is also located in the Great Lakes region. Nearly 75% more articles examined the effects of precipitation on ungulates compared to temperature, with variables related to snow being the most commonly measured climate variables. Most studies examined the effects of climate on ungulate population demographics, habitat and forage, and physiology and condition, with far fewer examining the effects on disturbances, migratory behavior, and seasonal range and corridor habitat. CONCLUSIONS: The effects of climate change, and its interactions with stressors such as land-use change, predation, and disease, is of increasing concern to wildlife managers. With its broad scope, this systematic map can help ungulate managers identify relevant climate impacts and prepare for future changes to the populations they manage. Decisions regarding population control measures, supplemental feeding, translocation, and the application of habitat treatments are just some of the management decisions that can be informed by an improved understanding of climate impacts. This systematic map also identified several gaps in the literature that would benefit from additional research, including climate effects on ungulate migratory patterns, on species that are relatively understudied yet known to be sensitive to changes in climate, such as pronghorn (Antilocapra americana) and mountain goats (Oreamnos americanus), and on ungulates in the eastern U.S. and Mexico.

Effects of Weather on the Severity of Menstrual Symptoms Among College- and High School-Going Women in the Southern Regions of Saudi Arabia.

BACKGROUND: The effects of weather on the severity of menstrual symptoms have been a topic of interest and research for many years. While some studies have shown a correlation between weather conditions and increased severity of menstrual symptoms, others have found no significant relationship. OBJECTIVE: The current study aimed to assess the effects of weather on the severity of menstrual symptoms among women going to college and high school in the southern regions of Saudi Arabia. METHODS: A descriptive cross-sectional study was conducted targeting all women going to college and high school in southern regions of Saudi Arabia. An online questionnaire was used for data collection. The data were entered and analyzed in IBM SPSS Statistics for Windows, version 26 (IBM Corp., Armonk, NY), and stored with no attempts to identify the participants. RESULTS: The study included 484 participants; most of them were 20-30 years old; 64.5% had regular menstrual cycles. It was observed that mood fluctuations, bloating, difficulty concentrating, breast pain, irritability, anxiety, social isolation, feeling tired, headaches, and mood changes are all affected to some degree before and during menstruation. On the other hand, the amount of blood, duration of the course, physical activity during menstruation, nutritional habits, lower back pain, and sleep disorders showed varying percentages of impact. These findings provide valuable insights into the physiological and psychological changes that occur during the menstrual cycle. CONCLUSION: In conclusion, the relationship between weather and the severity of menstrual symptoms is a complex and multifaceted topic. While some women may perceive a correlation between certain weather conditions and an increase in symptom severity, the scientific evidence in support of this connection is still limited and inconclusive. Further research is needed to better understand the underlying mechanisms and to provide evidence-based recommendations for managing menstrual symptoms in relation to weather conditions.

Effects of Low-Pressure Systems on Temperature, Humidity, Egg Production, and Feed Utilization Efficiency in Large-Scale Poultry Houses during Summer.

Low-pressure systems (LPSs) are among the most critical weather systems, producing excessive precipitation that causes air temperatures to drop and rise considerably. Acute temperature changes directly affect poultry feed intake (FI) and laying performance. To explore the effects of LPSs on hens, the parameters of air temperature, relative humidity, egg production, and feed utilization efficiency were evaluated during different LPSs in three houses. Results indicated that about 2.8 ± 0.7 d, 2.4 ± 0.5 d, and 2.4 ± 0.5 d before the LPS landfall in houses 1, 2, and 3, respectively, the indoor air temperature started to decrease, with the average decreases being 1.7 °C ± 0.4 °C, 2.4 °C ± 0.6 °C, and 1.8 °C ± 0.4 °C, respectively. Significant differences were observed between different LPSs for reducing indoor air temperature (p < 0.05) in the three houses. In house 1, the egg production rates (EPRs) were decreased by 6.6% and 1.1% when LPSs 1 and 2 landed. The average egg weight (AEW) and FI during the LPS landfall were significantly higher than those before the LPS landfall (p < 0.01). Under successive LPSs landfall in the three houses, the EPRs initially reduced by 3.9%, 4.0%, and 0.5%, respectively, but the second LPS event increased the EPRs by 1.8%, 5.3%, and 1.0%, respectively. Furthermore, the LPS landfall increased the feed conversion ratio (FCRe) in the three houses, all above 2.00. In conclusion, LPSs can reduce heat stress, lower the EPRs, and lead to higher FI, FCRe, and AEW.

Climate Change Impacts on and Response Strategies for Kiwifruit Production: A Comprehensive Review.

Climate change, a pressing global concern, poses significant challenges to agricultural systems worldwide. Among the myriad impacts of climate change, the cultivation of kiwifruit trees (Actinidia spp.) faces multifaceted challenges. In this review, we delve into the intricate effects of climate change on kiwifruit production, which span phenological shifts, distributional changes, physiological responses, and ecological interactions. Understanding these complexities is crucial for devising effective adaptation and mitigation strategies to safeguard kiwifruit production amidst climate variability. This review scrutinizes the influence of rising global temperatures, altered precipitation patterns, and a heightened frequency of extreme weather events on the regions where kiwifruits are cultivated. Additionally, it delves into the ramifications of changing climatic conditions on kiwifruit tree physiology, phenology, and susceptibility to pests and diseases. The economic and social repercussions of climate change on kiwifruit production, including yield losses, livelihood impacts, and market dynamics, are thoroughly examined. In response to these challenges, this review proposes tailored adaptation and mitigation strategies for kiwifruit cultivation. This includes breeding climate-resilient kiwifruit cultivars of the Actinidia species that could withstand drought and high temperatures. Additional measures would involve implementing sustainable farming practices like irrigation, mulching, rain shelters, and shade management, as well as conserving soil and water resources. Through an examination of the literature, this review showcases the existing innovative approaches for climate change adaptation in kiwifruit farming. It concludes with recommendations for future research directions aimed at promoting the sustainability and resilience of fruit production, particularly in the context of kiwifruit cultivation, amid a changing climate.

Bacterial accumulation dynamics in runoff from extreme precipitation.

Extreme precipitation can significantly influence the water quality of surface waters. However, the total amount of bacteria carried by rainfall runoff is poorly understood. Here, thirty rainfall scenarios were simulated by artificial rainfall simulators, with designed rainfall intensity ranging from 19.3 to 250 mm/h. The instantaneous concentration ranges of R2A, nutrient agar (NA) culturable bacteria, and viable bacteria in runoff depended on the types of underlying surfaces. The instantaneous bacterial concentrations in runoff generated by forest lands, grasslands and bare soil were: R2A culturable bacteria = 104.5-6.3, 104.5-6.1, 104.0-5.3 colony-forming units (CFU)/mL, NA culturable bacteria = 104.0-6.0, 103.9-5.8, 103.2-4.9 CFU/mL, and viable bacteria = 106.4-8.0, 107.0-8.9, 106.4-7.6 cells/mL. Based on the measured bacterial instantaneous concentration in runoff, cumulative dynamic models were established, and the maximum amount of culturable bacteria and viable bacteria entering water sources were estimated to be 109.38-11.31 CFU/m2 and 1011.84-13.25 cells/m2, respectively. The model fitting and the bacterial accumulation dynamics were influenced by the rainfall types (p < 0.01). Surface runoff from the underlying surface of forest lands and grasslands had a high microbial risk that persisted even during the "Drought-to-Deluge Transition". Bacterial accumulation models provide valuable insight for predicting microbial risks in catchments during precipitation and can serve as theoretical support for further ensuring the safety of drinking water under the challenge of climate change.

Comparison of hunting site strategies of the common buzzard Buteo buteo in open landscapes and along expressways.

Background: The expansion of human activities in their many forms increases the frequency, diversity, and scale of human-wildlife interactions. One such negative form is the expansion of road infrastructure, causing road kill and traffic-related noise as well as habitat loss and fragmentation. Even so, habitats around road infrastructure are attractive foraging areas that attract certain bird species. We assessed the impact of road infrastructure on the foraging strategies of the common buzzard Buteo buteo. Methods: Birds were observed during two winter seasons in two land-use types, along an expressway and an open agricultural landscape. Individual birds were tracked for a 10-min sequence as a separate sample was analysed. The material, covering 1,220 min along the expressway, and 1,100 min in the agricultural landscape, was collected. Results: Time spent by buzzards on medium-height sites was higher along the expressway than in farmland. Buzzards changed their hunting sites following the mean wind speed. Also, they more often changed their sites along the expressway than in farmland. The land-use types, snow cover, and the mean wind speed mediated the number of attacks on prey. These results illustrate the high plasticity of the buzzards' behaviour, which can adapt their hunting strategies to both foraging locations (expressway and farmland) and weather conditions. Roadsides along expressways are attractive foraging areas for this diurnal raptor, so reducing the risk of vehicle collisions with this and other birds of prey may require targeted planning efforts.