Anoxia begets anoxia: A positive feedback to the deoxygenation of temperate lakes.

Declining oxygen concentrations in the deep waters of lakes worldwide pose a pressing environmental and societal challenge. Existing theory suggests that low deep-water dissolved oxygen (DO) concentrations could trigger a positive feedback through which anoxia (i.e., very low DO) during a given summer begets increasingly severe occurrences of anoxia in following summers. Specifically, anoxic conditions can promote nutrient release from sediments, thereby stimulating phytoplankton growth, and subsequent phytoplankton decomposition can fuel heterotrophic respiration, resulting in increased spatial extent and duration of anoxia. However, while the individual relationships in this feedback are well established, to our knowledge, there has not been a systematic analysis within or across lakes that simultaneously demonstrates all of the mechanisms necessary to produce a positive feedback that reinforces anoxia. Here, we compiled data from 656 widespread temperate lakes and reservoirs to analyze the proposed anoxia begets anoxia feedback. Lakes in the dataset span a broad range of surface area (1-126,909 ha), maximum depth (6-370 m), and morphometry, with a median time-series duration of 30 years at each lake. Using linear mixed models, we found support for each of the positive feedback relationships between anoxia, phosphorus concentrations, chlorophyll a concentrations, and oxygen demand across the 656-lake dataset. Likewise, we found further support for these relationships by analyzing time-series data from individual lakes. Our results indicate that the strength of these feedback relationships may vary with lake-specific characteristics: For example, we found that surface phosphorus concentrations were more positively associated with chlorophyll a in high-phosphorus lakes, and oxygen demand had a stronger influence on the extent of anoxia in deep lakes. Taken together, these results support the existence of a positive feedback that could magnify the effects of climate change and other anthropogenic pressures driving the development of anoxia in lakes around the world.

Modification of heat-related effects on mortality by air pollution concentration, at small-area level, in the Attica prefecture, Greece.

BACKGROUND: The independent effects of short-term exposure to increased air temperature and air pollution on mortality are well-documented. There is some evidence indicating that elevated concentrations of air pollutants may lead to increased heat-related mortality, but this evidence is not consistent. Most of these effects have been documented through time-series studies using city-wide data, rather than at a finer spatial level. In our study, we examined the possible modification of the heat effects on total and cause-specific mortality by air pollution at municipality level in the Attica region, Greece, during the warm period of the years 2000 to 2016. METHODS: A municipality-specific over-dispersed Poisson regression model during the warm season (May-September) was used to investigate the heat effects on mortality and their modification by air pollution. We used the two-day average of the daily mean temperature and daily mean PM10, NO2 and 8 hour-max ozone (O3), derived from models, in each municipality as exposures. A bivariate tensor smoother was applied for temperature and each pollutant alternatively, by municipality. Α random-effects meta-analysis was used to obtain pooled estimates of the heat effects at different pollution levels. Heterogeneity of the between-levels differences of the heat effects was evaluated with a Q-test. RESULTS: A rise in mean temperature from the 75th to the 99th percentile of the municipality-specific temperature distribution resulted in an increase in total mortality of 12.4% (95% Confidence Interval (CI):7.76-17.24) on low PM10 days, and 21.25% (95% CI: 17.83-24.76) on high PM10 days. The increase on mortality was 10.09% (95% CI: - 5.62- 28.41) on low ozone days, and 14.95% (95% CI: 10.79-19.27) on high ozone days. For cause-specific mortality an increasing trend of the heat effects with increasing PM10 and ozone levels was also observed. An inconsistent pattern was observed for the modification of the heat effects by NO2, with higher heat effects estimated in the lower level of the pollutant. CONCLUSIONS: Our results support the evidence of elevated heat effects on mortality at higher levels of PM10 and 8 h max O3. Under climate change, any policy targeted at lowering air pollution levels will yield significant public health benefits.

The interior climate and its microclimatic variation of temperate forests in Northern Patagonia, Argentina.

Knowledge on mesoclimatic zonation and microclimatic variations within mountain forest ecosystems is crucial for understanding regional species turnover and effects of climate change on these systems. The temperate mountain forests in the Andean region of South America are among the largest and contiguous natural deciduous forest areas in the world. Due to their pronounced disturbance regime and different successional stages, a climatic zonation combined with the characterisation of its microclimatic variation is important to identify thresholds of species occurrences.We used micro-loggers to measure air temperature and relative humidity for one year at 40 measurement locations along longitudinal and elevation gradients in mountain forests in Northern Patagonia, Argentina. Our results unveil mesoclimatic patterns within these forests characterised by variations in temperature and vapour pressure deficit along the elevational gradient in general, but also at different times of the year. For example, Austrocedrus chilensis and Nothofagus dombeyi forests differed mainly by temperature and its diurnal range in the warmest months of the year. Also, differences between forest stands and gaps were more pronounced in the warmest months of the year and at lower elevations, with up to 2.5 K higher temperatures in the second half of the day in gaps. We found clear indications that shrubland of Nothofagus antarctica representing a successional stage after disturbances alters the mesoclimatic pattern, favouring forest fire ignition. Such mesoclimatic variations have a major influence on tree species turnover and ecological processes within these forest ecosystems.The findings contribute to our understanding of the complex interplay between topography, climate, and vegetation in shaping the spatial patterns of species occurrences.

Decametric-scale buffering of climate extremes in forest understory within a riparian microrefugia: the key role of microtopography.

Riparian corridors often act as low-land climate refugia for temperate tree species in their southern distribution range. A plausible mechanism is the buffering of regional climate extremes by local physiographic and biotic factors. We tested this idea using a 3-year-long microclimate dataset collected along the Ciron river, a refugia for European beech (Fagus sylvatica) in southwestern France. Across the whole network, canopy gap fraction was the main predictor for spatial microclimatic variations, together with two other landscape features (elevation above the river and woodland fraction within a 300m radius). However, within the riparian forest only (canopy gap fraction < 25%, distance to the river < 150m), variations of up to -4°C and + 15% in summertime daily maximum air temperature and minimum relative humidity, respectively, were still found from the plateau to the cooler, moister river banks, only ~ 5-10m below. Elevation above the river was then identified as the main predictor, and explained the marked variations from the plateau to the banks much better than canopy gap fraction. The microclimate measured near the river is as cool but moister than the macroclimate encountered at 700-1000m asl further east in F. sylvatica's main distribution range. Indeed, at all locations, we found that air relative humidity was higher than expected from a temperature-only effect, suggesting that extra moisture is brought by the river. Our results explain well why beech trees in this climate refugium are restricted to the river gorges where microtopographic variations are the strongest and canopy gaps are rare.

Thermal characterization and ventilation assessment of a battery-caged laying hen housing in the humid tropic climate.

The indoor climate to which livestock are exposed is a critical factor influencing their performance and productivity. Elevated air temperature and relative humidity could result in heat stress for laying hens. This situation results in severe adverse effects such as weight loss and mortality. Egg fertility and hatchability are also impacted. Consequently, a study was carried out in a naturally ventilated battery-caged laying hen house to measure climatic variables (air temperature, relative humidity and air velocity). The degree of heat stress was assessed using the temperature-humidity index (THI), and the index of temperature and air velocity (ITV) was also evaluated. According to the results obtained, birds reared within the study building would spend most of their productive life under stressful thermal conditions, which could significantly hamper their performance. The air velocity was below 1.0 ms-1 for most of the internal part of the housing, meaning natural air movement at the location was insufficient to provide a suitable environment for the birds. A high THI was recorded for nearly the entire study period. This high THI could indicate high relative humidity about air temperature. The observed ITV values (ITV > 25) suggest that birds throughout the building could be perpetually uncomfortable. The thermal and velocity profile within the structure could further be assessed numerically using computational fluid dynamics. This would enable engineers to make modifications to improve living conditions within the building.

Measurement Errors When Measuring Temperature in the Sun.

In the validation of microclimate simulation software, the comparison of simulation results with on-site measurements is a common practice. To ensure reliable validation, it is crucial to utilize high-quality temperature sensors with a deviation smaller than the average absolute error of the simulation software. However, previous validation campaigns have identified significant absolute errors, particularly during periods of high solar radiation, possibly attributed to the use of non-ventilated radiation shields. This study addresses the issue by introducing a ventilated radiation shield created through 3D printing, aiming to enhance the accuracy of measurements on cloudless summer days with intense solar radiation. The investigation employs two pairs of sensors, each comprising one sensor with a ventilated and one with a non-ventilated radiation shield, placed on a south-oriented facade with two distinct albedos. Results from the measurement campaign indicate that the air temperature measured by the non-ventilated sensor is elevated by up to 2.8 °C at high albedo and up to 1.9 °C at a low albedo facade, compared to measurements with the ventilated radiation shield. An in-depth analysis of means, standard deviations, and 95% fractiles highlights the strong dependency of the non-ventilated sensor error on wind velocity. This research underscores the importance of employing ventilated radiation shields for accurate microclimate measurements, particularly in scenarios involving high solar radiation, contributing valuable insights for researchers and practitioners engaged in microclimate simulation validation processes.

Reproductive biology of Lepidocephalichthys guntea: a key conservation approach considering environmental factors in Payra River, Bangladesh.

The guntea loach, Lepidocephalichthys guntea, is categorically common freshwater fish in Southeast Asia. Current study is the first elucidation on the reproductive feature of L. guntea including population structure, sex ratio (SR), size at first maturity (Lm), breeding period, and condition factor, emphasizing on the effect of environmental factors on reproduction of this fish in the Payra River (Southern Bangladesh) during July 2021 to June 2022. Using various conventional gears, 1128 individuals (534 males and 594 females) have been collected. Total length (TL), standard length (SL), and body weight (BW) of each fish were measured. Ovaries were cautiously dissected, removed, and precisely weighed. TL ranges from 4.6 to 9.7 cm (BW = 0.7-9.27 g) for male and 4.6-10.3 cm (BW = 0.8-10.75 g) for female. Both male (47.34%) and female (52.66%) populations were the leading group in 7.00-7.99 cm TL. Overall SR was not notably altered from anticipated value of 1:1 (male:female = 1:1.11). Nonetheless, monthly variations of SR specified females were considerably outnumbered males in each month excluding March-May. Lm range was 6.4-7.0 cm, so larger than Lm is recommended to exploit. Monthly changes in GSI indicated that the main spawning season was from March to June. The spawning season was substantially correlated with rainfall, nonetheless with temperature. Additionally, relative weight indicated that habitat was imbalanced with higher predators. A fishing ban is recommended during peak spawning to protect L. guntea in the Payra River and its surroundings based on current research.

Delineating the impacts of air temperature and humidity for endurance exercise.

NEW FINDINGS: What is the central question of this study? What are the independent effects of air temperature and humidity on performance, physiological and perceptual responses during endurance exercise? What is the main finding and its importance? When examined independently, elevated air temperature increased heat strain and impaired aerobic exercise performance, but to a lesser extent than has been reported previously. These findings highlight the importance of absolute humidity relative to temperature when exercising or working under severe heat stress. ABSTRACT: Many studies have reported that ambient heat stress increases physiological and perceptual strain and impairs endurance exercise, but effects of air temperature per se remain almost unexamined. Most studies have used matched relative humidity, thereby exponentially increasing absolute humidity (water content in air) concurrently with temperature. Absolute (not relative) humidity governs evaporative rate and is more important at higher work rates and air temperatures. Therefore, we examined the independent effects of air temperature and humidity on performance, thermal, cardiovascular and perceptual measures during endurance exercise. Utilizing a crossover design, 14 trained participants (7 females) completed 45 min fixed-intensity cycling (70% V ̇ O 2 peak ${\dot V_{{{\rm{O}}_{\rm{2}}}{\rm{peak}}}}$ ) followed by a 20-km time trial in each of four environments: three air temperatures at matched absolute humidity (Cool, 18°C; Moderate, 27°C; and Hot, 36°C; at 1.96 kPa, air velocity ∼4.5 m/s), and one at elevated humidity (Hot Humid, 36°C at 3.92 kPa). Warmer air caused warmer skin (0.5°C/°C; P < 0.001), higher heart rate (1 bpm/°C; P < 0.001), sweat rate (0.04 l/h/°C; P < 0.001) and thermal perceptions during fixed-intensity exercise, but minimally affected core temperature (<0.01°C/°C; P = 0.053). Time-trial performance was comparable between Cool and Moderate (95% CI: -1.4, 5.9%; P = 0.263), but 3.6-6% slower in Hot (95% CI: ±2.4%; P ≤ 0.006). Elevated humidity increased core temperature (P < 0.001), perceived temperature and discomfort but not skin temperature or heart rate, and reduced mean blood pressure (P = 0.046) during fixed-intensity exercise. Elevated humidity impaired time-trial performance by 3.4% (95% CI: ±2.2%; P = 0.006). In conclusion, these findings quantify the importance of absolute humidity alongside air temperature when exercising under severe heat stress.

Descriptive analysis of occupational accidents in Spain and their relationship with heatwaves.

OBJECTIVE: The purpose of this work is to carry out a descriptive analysis of occupational accidents and to evaluate the relationship between heatwaves and work accidents in Spain's three most populated provinces: Madrid, Barcelona and Valencia. METHODS: Daily data of work accidents (including for each case: gender, age, date, length of time in the position, type of work, place of accident and duration of medical leave) was collected. A heatwave was defined when daily mean temperatures above the threshold (95th percentile) of the climatological period (1990-2021) were recorded for at least three consecutive days. To estimate the association between daily workplace accidents and heatwave events, we applied a Generalized Additive Model combined with a Distributed Lag Non-linear Model with a quasi-Poisson distribution. RESULTS: The average annual accident rate was 33.2 work accidents/100,000 employees in Madrid, 35.8 work accidents/100,000 employees in Barcelona and 31.8 work accidents/100,000 employees in Valencia. The total accident rates followed a downward trend between 2005 and 2021. The difference in work accident rates between sex decreased over the studied period (p < 0.005). In the first month of work, the highest casualty rate occurs among construction workers in Madrid and Barcelona, and in primary sector workers in Valencia. Work accidents tend to increase during heatwaves. The highest risk was recorded when considering a cumulative lagged effect of 3 days in Madrid and Barcelona and 5 days in Valencia. CONCLUSIONS: Since work accidents increase during heatwaves, risk prevention services and public administrations must take special measures to prevent them.

Study of the influence of meteorological factors on HFMD and prediction based on the LSTM algorithm in Fuzhou, China.

BACKGROUND: This study adopted complete meteorological indicators, including eight items, to explore their impact on hand, foot, and mouth disease (HFMD) in Fuzhou, and predict the incidence of HFMD through the long short-term memory (LSTM) neural network algorithm of artificial intelligence. METHOD: A distributed lag nonlinear model (DLNM) was used to analyse the influence of meteorological factors on HFMD in Fuzhou from 2010 to 2021. Then, the numbers of HFMD cases in 2019, 2020 and 2021 were predicted using the LSTM model through multifactor single-step and multistep rolling methods. The root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and symmetric mean absolute percentage error (SMAPE) were used to evaluate the accuracy of the model predictions. RESULTS: Overall, the effect of daily precipitation on HFMD was not significant. Low (4 hPa) and high (≥ 21 hPa) daily air pressure difference (PRSD) and low (< 7 °C) and high (> 12 °C) daily air temperature difference (TEMD) were risk factors for HFMD. The RMSE, MAE, MAPE and SMAPE of using the weekly multifactor data to predict the cases of HFMD on the following day, from 2019 to 2021, were lower than those of using the daily multifactor data to predict the cases of HFMD on the following day. In particular, the RMSE, MAE, MAPE and SMAPE of using weekly multifactor data to predict the following week's daily average cases of HFMD were much lower, and similar results were also found in urban and rural areas, which indicating that this approach was more accurate. CONCLUSION: This study's LSTM models combined with meteorological factors (excluding PRE) can be used to accurately predict HFMD in Fuzhou, especially the method of predicting the daily average cases of HFMD in the following week using weekly multifactor data.

Effects of Short- And Medium-Term Exposures to Lower Air Temperature on 71 Novel Biomarkers of Subclinical Inflammation: Results from the KORA F4 Study.

Increasing evidence has revealed that exposure to low temperatures is linked to a higher risk of chronic diseases and death; however, the mechanisms underlying the observed associations are still poorly understood. We performed a cross-sectional analysis with 1115 participants from the population-based KORA F4 study, which was conducted in Augsburg, Germany, from 2006 to 2008. Seventy-one inflammation-related protein biomarkers were analyzed in serum using proximity extension assay technology. We employed generalized additive models to explore short- and medium-term effects of air temperature on biomarkers of subclinical inflammation at cumulative lags of 0-1 days, 2-6 days, 0-13 days, 0-27 days, and 0-55 days. We found that short- and medium-term exposures to lower air temperature were associated with higher levels in 64 biomarkers of subclinical inflammation, such as Protein S100-A12 (EN-RAGE), Interleukin-6 (IL-6), Interleukin-10 (IL-10), C-C motif chemokine 28 (CCL28), and Neurotrophin-3 (NT-3). More pronounced associations between lower air temperature and higher biomarker of subclinical inflammation were observed among older participants, people with cardiovascular disease or prediabetes/diabetes, and people exposed to higher levels of air pollution (PM2.5, NO2, and O3). Our findings provide intriguing insight into how low air temperature may cause adverse health effects by activating inflammatory pathways.

Temperature Changes Induced by Biogeochemical and Biophysical Effects of Bioenergy Crop Cultivation.

The production of bioenergy with carbon capture and storage (BECCS) is a pivotal negative emission technology. The cultivation of dedicated crops for BECCS impacts the temperature through two processes: net CO2 removal (CDR) from the atmosphere (biogeochemical cooling) and changes in the local energy balance (biophysical warming or cooling). Here, we compare the magnitude of these two processes for key grass and tree species envisioned for large-scale bioenergy crop cultivation, following economically plausible scenarios using Earth System Models. By the end of this century, the cumulative CDR from the cultivation of eucalypt (72-112 Pg C) is larger than that of switchgrass (34-83 Pg C) because of contrasting contributions of land use change carbon emissions. The combined biogeochemical and biophysical effects are cooling (-0.26 to -0.04 °C) at the global scale, but 13-28% of land areas still have net warming signals, mainly due to the spatial heterogeneity of the biophysical effects. Our study shows that the deployment of bioenergy crop cultivation should not only be guided by the principles of maximizing yield and CDR but should also take an integrated perspective that includes all relevant Earth system feedbacks.

Impact of the COVID-19 outbreak on urban air, Land surface temperature and air pollution in cold climate zones.

The objective of this study was to analyze air pollution and thermal environment in Turkey's cold region before, during, and after COVID-19 in 2019, 2020 and 2021. The CO, NO2, O3, PM10 and SO2 data from the state air quality stations, as well as ground air temperature data from six weather stations, and land satellite images from the USGS website using ArcGIS 10.4.1 software were collected in January, March, April and August of 2019, 2020 an 2021. In order to evaluate the impact of COVID-19 measures and restrictions on cold region cities, air pollution indicators, land surface temperature and air temperature as well as statistical data were analyzed. The results indicated that the CO, NO2, PM10 and SO2 emissions decreased by 14.9%, 14.3%, 47.1% and 28.5%, but O3 increased by 16.9%, respectively, during the COVID-19 lockdown in 2020 as compared to these of the pre-COVID-19 levels in 2019. A positive correlation between air temperature and O3 in 2019 (r2 = 0.80), and in 2020 and 2021 (r2 = 0.64) was obtained. Air temperature in 2020 and 2021 decreased due to lockdowns and quarantine measures that led to lower O3 emissions as compared to 2019. Negative correlations were also found between air temperature and NO2 (r2 = 0.60) and SO2 (r2 = 0.5). There was no correlation between air temperature and PM10. During the COVID-19 lockdown and intense restrictions in April 2020, the average LST and air temperature values dropped by 14.7 °C and 1.6 °C respectively, compared to April 2019. These findings may be beneficial for future urban planning, particularly in cold regions.

The impact of daily mean air temperature on the proportion of time in hypoglycemia in 2,582 children and adolescents with type 1 diabetes - Is this association clinically relevant?

OBJECTIVES: To study the potential association between increases in daily mean air temperature and time below range (TBR <54 mg/dl) and time above range (TAR >250 mg/dl) in children and adolescents with type 1 diabetes. RESEARCH DESIGN AND METHODS: Individuals with type 1 diabetes <21 years with information on daily glucose profiles from the diabetes prospective follow-up study (DPV) were included (n = 2582). Further inclusion criteria were age at least 6 months at diabetes onset, diabetes duration for at least one year and treatment years 2020-2021. Mean daily air temperature and other meteorological parameters from 78 measurement stations in Germany were linked to the individual glucose sensor profile via the five-digit postcode areas of residency. We used multivariable repeated measures fractional logistic regression models with a compound symmetry covariance structure to study the association between a 1 °C increase in daily mean temperature and time in specific glucose ranges. RESULTS: A 1 °C increase in daily mean temperature was associated with an acute (Odds Ratio (OR) 1.009 (95%-CI 1.007, 1.011)) and up to 7 days delayed (OR 1.003 (1.001, 1.005)) increase in TBR <54 mg/dl. Moreover, an acute decrease in TAR >250 mg/dl (OR 0.997 (0.996, 0.997)) was found. CONCLUSIONS: Results of the DPV registry showed small, but statistically significant changes in TBR and TAR in association with a short-term temperature increase. Higher blood flow and faster insulin absorption might be one possible mechanism. In times of increasing temperature fluctuations meteorological impacts on time in range could become even more relevant.

High-resolution spatiotemporal modeling of daily near-surface air temperature in Germany over the period 2000-2020.

The commonly used weather stations cannot fully capture the spatiotemporal variability of near-surface air temperature (Tair), leading to exposure misclassification and biased health effect estimates. We aimed to improve the spatiotemporal coverage of Tair data in Germany by using multi-stage modeling to estimate daily 1 × 1 km minimum (Tmin), mean (Tmean), maximum (Tmax) Tair and diurnal Tair range during 2000-2020. We used weather station Tair observations, satellite-based land surface temperature (LST), elevation, vegetation and various land use predictors. In the first stage, we built a linear mixed model with daily random intercepts and slopes for LST adjusted for several spatial predictors to estimate Tair from cells with both Tair and LST available. In the second stage, we used this model to predict Tair for cells with only LST available. In the third stage, we regressed the second stage predictions against interpolated Tair values to obtain Tair countrywide. All models achieved high accuracy (0.91 ≤ R2 ≤ 0.98) and low errors (1.03 °C ≤ Root Mean Square Error (RMSE) ≤ 2.02 °C). Validation with external data confirmed the good performance, locally, i.e., in Augsburg for all models (0.74 ≤ R2 ≤ 0.99, 0.87 °C ≤ RMSE ≤ 2.05 °C) and countrywide, for the Tmean model (0.71 ≤ R2 ≤ 0.99, 0.79 °C ≤ RMSE ≤ 1.19 °C). Annual Tmean averages ranged from 8.56 °C to 10.42 °C with the years beyond 2016 being constantly hotter than the 21-year average. The spatial variability within Germany exceeded 15 °C annually on average following patterns including mountains, rivers and urbanization. Using a case study, we showed that modeling leads to broader Tair variability representation for exposure assessment of participants in health cohorts. Our results indicate the proposed models as suitable for estimating nationwide Tair at high resolution. Our product is critical for temperature-based epidemiological studies and is also available for other research purposes.

Hospital admission tendencies caused by day-to-day temperature changes during summer: a case study for the city of Novi Sad (Serbia).

Increased temperature risk in cities threatens the health and well-being of urban population and is fueled by climate change and intensive urbanization. Consequently, further steps must be taken for assessing temperature conditions in cities and their association with public health, in order to improve public health prevention at local or regional level. This study contributes to solving the problems by analyzing the connection between extreme temperatures and the tendencies of all-cause hospital admissions. The analyses used (a) 1-h air temperature data, and (b) daily data of all-cause hospital admissions. The datasets include the summer period (June, July, August) for the years 2016 and 2017. We tested the effects of two temperature indices, day-to-day change in maximum temperature - Tmax,c and daily temperature range - Tr, with all-cause hospital admission subgroups, such as all-cause cases - Ha, hospital admissions in the population below 65 - Ha<65, and hospital admissions in the population aged 65 and over - Ha≥65. The results show the highest values of Ha when Tmax,c is between 6 and 10 °C. Therefore, more intensive hospital admissions can be expected when Tmax increases from day-to-day (positive values of Tmax,c), and it is more visible for Ha and Ha<65 (1 °C = 1% increase in hospital admissions). Also, Tr values between 10 °C and 14 °C cause an increase in the number of hospital admissions, and it is more noticeable for Ha≥65.

The effects of summer ambient temperature on total mortality in Serbia.

In the context of recent climate change, temperature-attributable mortality has become an important public health threat worldwide. A large number of studies in Europe have identified a relationship between temperature and mortality, while only a limited number of scholars provided evidence for Serbia. In order to provide more evidence for better management of health resources at the regional and local level, this study aims to assess the impact of summer temperature on the population in Serbia, using daily average temperature (Ta) and mortality (CDR (crude death rate) per 100,000). The analysis was done for five areas (Belgrade, Novi Sad, Nis, Loznica, and Vranje), covering the summer (June-August) period of 2001-2015. In order to quantify the Ta-related CDR, a generalized additive model (GAM) assuming a quasi-Poisson distribution with log as the link function was used. Five regression models were constructed, for each area, revealing a statistically significant positive relationship between Ta and CDR in four areas. The effect of Ta on CDR was defined as the relative risk (RR), which was obtained as the exponential regression coefficient of the models. RR indicates that a 1 °C increase in Ta at lag0 was associated with an increase in CDR of 1.7% for Belgrade, Novi Sad, and Nis and 2% for Loznica. The model for Vranje did not quantify a statistically significant increase in CDR due to Ta (RR=1.006, 95% CI 0.991-1.020). Similar results were confirmed for gender, with a slightly higher risk for women. Analysis across lag structure showed different exposure, but the highest effect of Ta mainly occurs over the short term and persists for 3 days.

Common snowdrop as a climate change bioindicator in Czechia.

The phenological response to climate change differs among species. We examined the beginning of flowering of the common snowdrop (Galanthus nivalis) in connection with meteorological variables in Czechia in the period 1923-2021. The long-term series were analyzed from phenological and meteorological stations of the Czech Hydrometeorological Institute (CHMI). Temporal and spatial evaluation (using Geographic Information System) in timing of beginning of flowering (BBCH 61) of G. nivalis was investigated under urban and rural settings. Furthermore, the detailed analysis of selected meteorological variables to onset of G. nivalis flowering was performed. Moreover, the trends (using Mann-Kendall test) and Pearson's correlation coefficients between phenological phase and meteorological variable were calculated. The main finding of this study was that the trend of the beginning of flowering of the common snowdrop during the studied period (1923-2021) is negative, and it varies in urban and rural environments. The results showed most significant acceleration of the beginning of flowering of G. nivalis by - 0.20 day year-1 in urban area and by - 0.11 day year-1 in rural area. Above that, a major turning point occurred between 1987 and 1988 (both, in phenological observations and meteorological variables), and the variability of the beginning of flowering is significantly higher in the second period 1988-2021. On top of, the study proved that the beginning of flowering of G. nivalis closely correlated with number of days with snow cover above 1 cm (December-March) at both types of stations (urban and rural), and with mean air temperature in February, maximum air temperature in January, and minimum air temperature in March. The Mann-Kendall test showed a reduction in the number of days with snow cover above 1 cm (December-March) during 99 years period at Klatovy station (a long-term time series) by - 0.06 day year-1, i.e., by - 5.94 days per the whole period. Conversely, air temperatures increase (maximum and minimum air temperature by 0.03 °C year-1 (2.97 °C per the whole period) and average air temperature by 0.02 °C year-1 (1.98 °C per the whole period)). Thus, our results indicate significant changes in the beginning of flowering of G. nivalis in Czechia as a consequence of climate change.

Pollen production of downy birch (Betula pubescens Ehrh.) along an altitudinal gradient in the European Alps.

High-altitude environments are highly susceptible to the effects of climate change. Thus, it is crucial to examine and understand the behaviour of specific plant traits along altitudinal gradients, which offer a real-life laboratory for analysing future impacts of climate change. The available information on how pollen production varies at different altitudes in mountainous areas is limited. In this study, we investigated pollen production of 17 birch (Betula pubescens Ehrh.) individuals along an altitudinal gradient in the European Alps. We sampled catkins at nine locations in the years 2020-2021 and monitored air temperatures. We investigated how birch pollen, flowers and inflorescences are produced in relation to thermal factors at various elevations. We found that mean pollen production of Betula pubescens Ehrh. varied between 0.4 and 8.3 million pollen grains per catkin. We did not observe any significant relationships between the studied reproductive metrics and altitude. However, minimum temperature of the previous summer was found to be significantly correlated to pollen (rs = 0.504, p = 0.039), flower (rs = 0.613, p = 0.009) and catkin (rs = 0.642, p = 0.005) production per volume unit of crown. Therefore, we suggest that temperature variability even at such small scales is very important for studying the response related to pollen production.

Investigation the relationship between causes of death and thermal comfort conditions: the sample of Amasya Province.

Despite many advances in medicine, there is still a strong relationship between human health and atmospheric conditions. This study determines the effects of thermal comfort conditions on the causes of death in the province of Amasya, which is located in the Mediterranean basin. Meteorological data and monthly mortality data were used as material. As a method, thermal comfort conditions were determined by the Rayman model according to the PET index. Pearson correlation analysis and linear regression analysis methods were used to determine the effects of air temperature and thermal comfort conditions on the causes of death. In conclusion, it has been determined that thermal comfort conditions are effective on the total number of deaths, deaths due to external injuries and poisonings, deaths due to circulatory, and respiratory system diseases, but not for deaths due to other causes. These findings are important for early warning systems, preventive, and protective measures in health systems.