Daily Temperature Range Research Articles

Frequencies of house fly proto-Y chromosomes across populations are predicted by temperature heterogeneity within populations.

Sex chromosomes often differ between closely related species and can even be polymorphic within populations. Species with multifactorial sex determination segregate for multiple different sex determining loci within populations, making them uniquely informative of the selection pressures that drive the evolution of sex chromosomes. The house fly (Musca domestica) is a model species for studying multifactorial sex determination because male determining genes have been identified on all six of the chromosomes, which means that any chromosome can be a "proto-Y". Natural populations of house fly also segregate for a recently derived female-determining locus, meaning house flies also have a proto-W chromosome. The different proto-Y chromosomes are distributed along latitudinal clines on multiple continents, their distributions can be explained by seasonality in temperature, and they have temperature-dependent effects on physiological and behavioral traits. It is not clear, however, how the clinal distributions interact with the effect of seasonality on the frequencies of house fly proto-Y and proto-W chromosomes across populations. To address this question, we measured the frequencies of house fly proto-Y and proto-W chromosomes across nine populations in the United States of America. We confirmed the clinal distribution along the eastern coast of North America, but it is limited to the eastern coast. In contrast, annual mean daily temperature range predicts proto-Y chromosome frequencies across the entire continent. Our results therefore suggest that temperature heterogeneity can explain the distributions of house fly proto-Y chromosomes in a way that does not depend on the cline.

Daily diurnal temperature range associated with emergency ambulance calls: a nine-year time-series study.

Diurnal temperature range (DTR) is associated with the increased risk of morbidity and mortality. However, the relationship between DTR and emergency ambulance calls (EACs), which more accurately and immediately reflect the health impacts of temperature changes, remains underexplored in China. We collected daily data on EACs and meteorological factors from 2009 to 2017 in Guangzhou, China. DTR, representing the temperature range within a day, was calculated by subtracting the minimum temperature from the maximum temperature for each day. Generalized additive models were used to estimate the association between DTR and EACs for all-cause, cardiovascular diseases, and respiratory diseases. Additionally, subgroup and sensitivity analyses were conducted in our study. We found significant associations between daily DTR and EACs. The excess risks (ERs) were 0.47% (95% CI: 0.14, 0.81%) for all-cause EACs, 0.94% (95% CI: 0.46, 1.43%) for cardiovascular-related EACs, and 1.31% (95% CI: 0.76, 1.86%) for respiratory -related EACs at lag01, respectively. Subgroup analyses indicated that these associations were notably stronger among the older, males, and during the warm season. Specifically, there was an increase of 1.16% (95% CI: 0.59, 1.74%) in cardiovascular-related EACs among the older adult, compared to 0.45% (95% CI: -0.21, 1.12%) among those younger than 65 years. Among males, the increase was 1.39% (95% CI: 0.79, 1.99%), compared to 0.13% (95% CI: -0.53, 0.79%) among females. During the warm season, the increase was 1.53% (95% CI: 0.74, 2.34%), compared to 0.75% (95% CI: 0.14, 1.37%) during the cold season. DTR might increase the risk of daily all-cause, cardiovascular-related, and respiratory-related EACs in Guangzhou, China. The associations were particularly strong among older adults, males, and during the warm season. Implementing public health policies is essential to mitigate the adverse health effects of DTR.

The Cooling Effect of Oasis Reservoir‐Riparian Forest Systems in Arid Regions

AbstractIn arid regions with limited water resources, numerous reservoirs have been built to support economic and social development. However, how the construction of reservoirs interacts with the surrounding ecosystem to affect temperature remains unclear. Spanning 2018 to 2022 in the Shiyang River Basin, we collected surface water and precipitation, as well as stem and soil samples. Using isotopic methods, we quantified how evaporation in the oasis reservoir‐riparian forest system affects the local climate. Our findings show that the latent heat released by evapotranspiration from the reservoir and riparian forest system reduces the daily maximum temperature and daily temperature range by 7°C and 6°C respectively, compared to downstream areas with sparse vegetation around artificial lakes. Additionally, it enhances local moisture recycling, increasing precipitation. This study reveals regional cooling effect due to interactions between water bodies, the atmosphere, and vegetation. We propose that establishing reservoir‐riparian forest systems can positively impact local climate regulation and serve as an effective strategy for adapting to global climate warming.

Residue Addition Can Mitigate Soil Health Challenges with Climate Change in Drylands: Insights from a Field Warming Experiment in Semi-Arid Texas

Texas cotton production is facing challenges from increased temperatures and extended droughts. We sought to determine whether applying a multi-species grass mulch on the surface of cotton fields in a semiarid region would mitigate some of the negative effects of climate change. We used open-top chambers (OTCs) to mimic climate warming and compared whether the effects of residue addition were similar between dryland and irrigated cotton fields located in the High Plains region of Texas during the summer of 2021. The OTCs raised the average air temperature by 2 °C. Under experimental warming, residue addition increased moisture content in non-irrigated (i.e., dryland) soils (+9.2%) and reduced the daily temperature range (by −1.4 °C) relative to uncovered soils. Furthermore, when pooled across irrigation and warming treatments, the addition of residue increased microbial biomass, soil respiration (+78.2%), and cotton yield (+15.2%) relative to uncovered soils. OTCs further enhanced the residue effects on microbial biomass by 34.9%. We also observed higher soil organic matter, microbial biomass, cotton biomass, and yield in irrigated fields compared to dryland, irrespective of residue addition. Our findings suggest that residue addition in dryland agriculture can mitigate the adverse effects of warming by stabilizing soil microclimates and promoting microbial growth and biomass by providing a more labile source of carbon, which, in turn, could boost the yield of cotton plants.

Runoff concentration decline for Tarim river due to a dramatic increasing of runoff in cold season and hydro-junction regulation: Past and future

Study regionThe three headwaters of Tarim river, south of the Xinjiang Province, China. Study focusTemporal runoff concentration variations are crucial for water resources utilization and management, particularly in arid regions. In this study, the runoff concentration in the Tarim River Basin is studied based on analysis of the trend, abrupt changes, and periodicity, identifying key extreme climate indices influencing the Gini-runoff coefficient and predicting its future changes under three Shared Socioeconomic Pathways (SSPs). New hydrological insights for the regionFrom 1962–2020, the Gini-runoff coefficient decreased by 8.3 %, while annual runoff increased by 14.2 %. This is attributed to temperature changes, escalating hydrological risk uncertainty. The anomaly of low geopotential high fields and Central Asian anticyclones have caused an increase in total cloud cover (TCC) and precipitation, and a decrease in the Daily Temperature Range (DTR). Increasing of Warm nights (TN90), Maximum Tmax (TXx), and Hot nights (TR) have enhanced the warm-season runoff. However, the climatic impact on warm-season runoff is less pronounced than that in the cold season, which led to the runoff concentration decline. Changes in hydro-junction regulation led to decrease of Gini-runoff coefficient by 12.11 % from 2001 to 2020 along the Hotan river. Under the three SSP scenarios, the average Gini-runoff coefficient for the Aksu and Hotan rivers are expected to decrease by 3.3 % and 2.6 %, respectively.

Appendage pigmentation and temperature acclimation correlate with survival during acute heat stress in the upside-down jellyfish, Cassiopea xamachana

IntroductionUpside-down jellyfish (Cassiopea sp.) are highly tolerant to multiple abiotic stressors, including fluctuating temperatures associated with shallow marine habitats. This resilience may underlie the ability of Cassiopea sp. to inhabit a wide variety of tropical habitats across the globe. Additionally, Cassiopea sp. are marked by a conspicuous array of appendage coloration; individual medusae vary in the hue and number of oral appendages, which are often strikingly blue. The function of this coloration is not understood. We aimed to understand how extrinsic (temperature, location) and intrinsic (host color) factors may shape thermal tolerance.MethodsAdult Cassiopea xamachana were collected from two sites that vary in daily temperature range within the Florida Keys and were subjected to acute lethal heat stress. To quantify a whole-organism response to heat, we measured changes in bell pulsation, which likely plays a role in feeding, oxygen exchange, and symbiont uptake. Finally, color morphs were acclimated at either ambient (26°C) or elevated (33°C) temperatures.ResultsC. xamachana from two locations that vary in thermal range do not exhibit different responses to heat, suggesting that temperature fluctuations do not prime individuals for higher thermal tolerance. Additionally, C. xamachana with blue appendages survived significantly higher temperatures and exhibited less change in bell pulsation rates compared to non-blue individuals. We found that acclimation at 33°C, as well as appendage color in each treatment, led to higher survival under acute heat stress.DiscussionThese findings highlight the importance of temperature and coloration in Cassiopea xamachana resilience during heat stress.

Assessing Climate Change Projections through High-Resolution Modelling: A Comparative Study of Three European Cities

Climate change is expected to influence urban living conditions, challenging cities to adopt mitigation and adaptation measures. This paper assesses climate change projections for different urban areas in Europe –Eindhoven (The Netherlands), Genova (Italy) and Tampere (Finland)—and discusses how nature-based solutions (NBS) can help climate change adaptation in these cities. The Weather Research and Forecasting Model was used to simulate the climate of the recent past and the medium-term future, considering the RCP4.5 scenario, using nesting capabilities and high spatial resolution (1 km2). Climate indices focusing on temperature-related metrics are calculated for each city: Daily Temperature Range, Summer Days, Tropical Nights, Icing Days, and Frost Days. Despite the uncertainties of this modelling study, it was possible to identify some potential trends for the future. The strongest temperature increase was found during winter, whereas warming is less distinct in summer, except for Tampere, which could experience warmer summers and colder winters. The warming in Genova is predicted mainly outside of the main urban areas. Results indicate that on average the temperature in Eindhoven will increase more than in Genova, while in Tampere a small reduction in annual average temperature was estimated. NBS could help mitigate the increase in Summer Days and Tropical Nights projected for Genova and Eindhoven in the warmer months, and the increase in the number of Frost Days and Icing Days in Eindhoven (in winter) and Tampere (in autumn). To avoid undesirable impacts of NBS, proper planning concerning the location and type of NBS, vegetation characteristics and seasonality, is needed.

Implications of Ecological Drivers on Roan Antelope Populations in Mokala National Park, South Africa

Climate change has massive global impacts and affects a wide range of species. Threatened species such as the roan antelope (Hippotragus equinus) are particularly vulnerable to these changes because of their ecological requirements. Attempts to address concerns about the roan’s vulnerability have not been well documented in South African protected areas. This study identifies the landscape use and distribution of the roan as well as habitat and forage suitability changes to help inform management decisions for the conservation of roan. We used fine- and broad-scale data from Mokala National Park, South Africa that includes roan occurrence data, vegetation condition indices, vegetation (structure and plant species composition), elevation and temperature differences, and precipitation strata to construct a suitability framework using the Maximum Entropy (Maxent) and Random Forest statistical package. In Mokala National Park, roan occurred in the Schmidtia pappophoroides–Vachellia erioloba sparse woodland, Senegalia mellifera–Vachellia erioloba closed woodland, Senegalia mellifera–Vachellia tortilis open shrubland, Vachellia erioloba–V. tortilis closed woodland and Rhigozum obovatum–Senegalia mellifera open shrubland. The veld (vegetation) condition index (VCI) improved from 2019 (VCI < 50%) to 2021 (VCI > 60%), with the proportion of palatable grass species (Schmidtia pappophoroides and Eragrostis lehmanniana) also increasing. This study identified four key climatic conditions affecting roan distribution, namely annual mean daily temperature range, temperature seasonality, minimum temperatures of the coldest month, and precipitation of the wettest month. These results suggest that the conservation of roan antelope should consider these key variables that affect their survival in preferred habitats and foraging areas in anticipation of changing ecological conditions.

Future projections of temperature-related indices in Prince Edward Island using ensemble average of three CMIP6 models

Prince Edward Island (PEI) is an agricultural province heavily relying on rainfed agriculture. The island has already experienced significant impacts from climate change. Accurate projections of PEI temperature extreme indices are required to mitigate and adapt to the changing climate conditions. This study aims to develop ensemble projections using Coupled Model Intercomparison Project Phase 6 (CMIP6) global circulation models (GCMs) to analyze temperature extremes on PEI. In this study, the ECMWF ERA5 reanalysis dataset was chosen for stepwise cluster analysis (SCA) due to its high accuracy. Three CMIP6 (NorESM2-MM, MPI-ESM1.2-HR, and CanESM5) GCMs, along with their ensemble average, were utilized in the SCA model to project future changes in daily maximum temperature (Tmax) and minimum temperature (Tmin) at four meteorological stations on PEI (East Point, Charlottetown, Summerside, and North Cape) under two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5). These GCMs were selected based on their low, medium, and high Equilibrium Climate Sensitivity. The bias-corrected results for the future period of Tmax and Tmin showed that the GCM-specific changes in the ECS also impact the regional scale. Additionally, several temperature extreme indices, including the daily temperature range (DTR), summer days (SU), growing degree days (GDD), growing season length (GSL), ice days (ID), and frost days (FD), were analyzed for two future periods: FP1(202–2050) and FP2 (2051–2075). The results indicate that DTR, SU, GDD, and GSL are expected to increase, while ID and FD are projected to decrease during FP1 and FP2 under both scenarios. The future projected mean monthly changes in Tmax, Tmin, and the selected temperature extreme indices highlight warmer future periods and an increase in agriculture-related indices such as GDD and GSL. Specifically, July, August, and September are expected to experience even higher temperatures in the future. As the climate becomes warmer, cold extreme events are projected to be shorter in duration but more intense in terms of their impact. The largest increments/decrements for Tmax, Tmin, and their relevant indices were observed during FP2 under SSP5-8.5. The outcomes of this study provide valuable insights for agricultural development, water resource management, and the formulation of effective mitigation strategies to address the impacts of climate change on PEI.

Daily temperature variability and mental health-related hospital visits in New York State

BackgroundDespite plausible behavioral and physiological pathways, limited evidence exists on how daily temperature variability is associated with acute mental health-related episodes. ObjectivesWe aimed to explore associations between daily temperature range (DTR) and mental health-related hospital visits using data of all hospital records in New York State during 1995–2014. We further examined factors that may modify these associations, including age, sex, hospital visit type and season. MethodsUsing a case-crossover design with distributed lag non-linear DTR terms (0–6 days), we estimated associations between ZIP Code-level DTR and hospital visits for mood (4.6 million hospital visits), anxiety (2.4 million), adjustment (∼368,000), and schizophrenia disorders (∼211,000), controlling for daily mean temperature, via conditional logistic regression models. We assessed potential heterogeneity by age, sex, hospital visit type (in-patient vs. out-patient), and season (summer, winter, and transition seasons). ResultsFor all included outcomes, we observed positive associations from period minimum DTR (0.1 °C) until 25th percentile (5.2 °C) and between mean DTR (7.7 °C) and 90th percentile (12.2 °C), beyond which we observed negative associations. For mood disorders, an increase in DTR from 0.1 °C to 12.2 °C was associated with a cumulative 16.0% increase (95% confidence interval [CI]: 12.8, 19.2%) in hospital visit rates. This increase was highest during transition seasons (32.5%; 95%CI: 26.4, 39.0%) compared with summer (10.7%; 95%CI: 4.8, 16.8%) and winter (−1.6%; 95%CI: −7.6, 4.7%). For adjustment and schizophrenia disorders, the strongest associations were seen among the youngest group (0–24 years) with almost no association in the oldest group (65+ years). We observed no evidence for modification by sex and hospital visit type. DiscussionDaily temperature variability was positively associated with mental health-related hospital visits within specific DTR ranges in New York State, after controlling for daily mean temperature. Given uncertainty on how climate change modifies temperature variability, additional research is crucial to comprehend the implications of these findings, particularly under different scenarios of future temperature variability.

Envirotype-based delineation of environmental effects and genotype × environment interactions in Indian soybean (Glycine max, L.)

Soybean is a rainfed crop grown across a wide range of environments in India. Its grain yield is a complex trait governed by many minor genes and influenced by environmental effects and genotype × environment interactions. In the current investigation, grain yield data of different sets of 41, 30 and 48 soybean genotypes evaluated during 2019, 2020 and 2021, respectively across 19 locations and twenty years’ data on 19 different climatic parameters at these locations was used to study the environmental effects on grain yield, to understand the genotype × environment interactions and to identify the mega-environments. Through analysis of variance (ANOVA), it was found that predominant portion of the variation was explained by environmental effects (E) (53.89, 54.86 and 60.56% during 2019, 2020 and 2021, respectively), followed by genotype × environment interactions (GEI) (31.29, 33.72 and 28.82% during 2019, 2020 and 2021, respectively). Principal Component Analysis (PCA) revealed that grain yield was positively associated with RH (Relative humidity at 2 m height), FRUE (Effect of temperature on radiation use efficiency), WSM (Wind speed at 2 m height) and RTA (Global solar radiation based on latitude and Julian day) and negatively associated with VPD (Deficit of vapour pressure), Trange (Daily temperature range), ETP (Evapotranspiration), SW (Insolation incident on a horizontal surface), n (Actual duration of sunshine) and N (Daylight hours). Identification of mega-environments is critical in enhancing the selection gain, productivity and varietal recommendation. Through envirotyping and genotype main effect plus genotype by environment interaction (GGE) biplot methods, nineteen locations across India were grouped into four mega-environments (MEs). ME1 included five locations viz., Bengaluru, Pune, Dharwad, Kasbe Digraj and Umiam. Eight locations—Anand, Amreli, Lokbharti, Bidar, Parbhani, Ranchi, Bhawanipatna and Raipur were included in ME2. Kota and Morena constitutes ME3, while Palampur, Imphal, Mojhera and Almora were included in ME4. Locations Imphal, Bidar and Raipur were found to be both discriminative and representative; these test locations can be utilized in developing wider adaptable soybean cultivars. Pune and Amreli were found to be high-yielding locations and can be used in large scale breeder seed production.

The application of a high-density street-level air temperature observation network (HiSAN): Spatial and temporal variations of thermal and wind condition in different climatic condition types

Different patterns of urban development will result in different characteristics of the urban heat island effect (UHI). In order to explore the impacts of urban environment characteristics, wind conditions, and climatic condition types on UHI over different periods, this study adopted Tainan City as the study site, and utilized the surface roughness length and wind prediction, to evaluate the correlation between wind conditions and UHI, as well as the thermal environment affected by different environmental. The UHI characteristics were evaluated by using 100 measurement stations (HiSAN) located in different urban environments. The results revealed the expansion of the daily temperature range was associated with an increase in the eastwest UHI centroid point movement; wind conditions affected north-south shifts of UHI centroid point. The built environments was positively correlate with daytime (0.24) and nighttime (0.68) temperatures. Daytime water bodies notably cool surroundings (correlation -0.52), and green spaces enhance nighttime cooling (correlation -0.64). Wind speed negatively correlates with UHI deviation values during the daytime (-0.17) and nighttime (-0.58). The study highlights the impact of wind speeds and temperature ranges on UHI movement, emphasizing effective ventilation's role in urban cooling and quantifying the importance of water and green space in mitigating UHI.

Effect of strip tillage widths on soil moisture, soil temperature and soil structure in northeast China

Strip tillage is an effective tillage technique, which included the strip seedbed tilled area (ST-IR) and the straw-covered area between the seedbeds (ST-BR). However, soil hydrothermal conditions and soil disturbance varies with strip tillage widths, which might affect crop growth and yields. Therefore, this study explored the effect of strip tillage width on the soil hydrothermal conditions and soil structure of ST-IR and ST-BR, to determine the optimal strip tillage width. A field experiment with three replicates was conducted to analyze soil moisture and soil temperature variation and to clarify the difference of soil structure in the IR and BR. Three strip tillage widths, 20 cm (ST20), 30 cm (ST30), and 40 cm (ST40), were examined in this study. Soil temperature in both the ST-IR and ST-BR increased as the strip tillage width increased, and the average soil temperature of ST30-IR and ST40-IR in the seedling stage was 2.11°C and 2.62°C higher than that of ST20-IR, respectively. Moreover, the daily soil temperature range in both the IR and BR was greater for ST40 than for ST20 and ST30 in the seedling stage; soil temperature differences in other crop growth stages were small. No significant difference in soil temperature was observed between ST30-IR and ST40-IR. Conversely, soil moisture was greater in ST20-IR and ST30-IR than in ST40-IR; soil moisture was also greater in ST30-BR and ST40-BR than in ST20-BR during the monitoring period. Soil moisture in ST40-IR and ST20-BR increased and decreased more rapidly during rainfall events than in the other treatments. Moreover, soil temperature was higher in the ST-IR than in the ST-BR for all 3 strip tillage widths, and the opposite results were observed for soil moisture. In addition, strip tillage widths had no significant differences on soil structure. In conclusion, a 30 cm strip tillage width had higher soil temperature and remained more soil moisture than other strip tillage widths, so this strip tillage width is thus recommended for use by farmers in Northeast China.

Responses of phenology to preseason drought and soil temperature for different land cover types on the Mongolian Plateau

Drought and heat caused major disturbance in nature by interfering with plant phenology, and can also alter the vulnerability and resilience of terrestrial ecosystems. Existing research on the Mongolian Plateau has primarily focused on studying the response of the start (SOS) and end (EOS) of the growing season to drought and heat variations. However, there is still a lack of comprehensive understanding regarding the coupled effects of drought and heat on phenology across different land cover types. In this study, we retrieved SOS and EOS based on 34-year (1982–2015) normalized difference vegetation index (NDVI) dataset from Global Inventory Modeling and Mapping Studies (GIMMS). Results showed that grasslands and the Gobi-Desert show rapid advancement in SOS, and forests presented the slowest advancement in SOS, but SOS in croplands were delayed. EOS across four land cover types advanced, with the Gobi-Desert showed the highest rate of advancement and forests the lowest. Using the Palmer Drought Severity Index (PDSI) and soil temperature as the indicators of drought and thermal conditions, the responses of SOS and EOS to these two climate variables were evaluated. The advanced SOS driven by lower drought severity was detected in forests, grasslands, croplands and the Gobi-Desert. The dominant response of EOS to drought severity was positive in croplands, grasslands and forests, except for the Gobi-Desert, where drought severity had negative effects on EOS. Compared with the daily average soil temperature (STmean), the daily maximum soil temperature (STmax, daytime), and the daily minimum soil temperature (STmin, nighttime), the daily diurnal soil temperature range (DSTR, where DSTR = STmax − STmin) between night and day were the most suitable indicators for assessing the response of SOS and EOS to soil temperature. Strong negative correlation between SOS and the preseason DSTR was pronounced in all land cover types on the Mongolian Plateau. However, EOS was negatively correlated with the preseason DSTR only in the Gobi-Desert. Last but not least, normalized sensitivity assessments reveal that the negative impacts of DSTR on SOS and EOS were the main controlling factors on the Mongolian Plateau phenology, followed by the couple negative effects of drought severity and DSTR.

Impact of climate change on temperature variations and extrinsic incubation period of malaria parasites in Chennai, India: implications for its disease transmission potential

BackgroundThe global temperature has significantly risen in the past century. Studies have indicated that higher temperature intensifies malaria transmission in tropical and temperate countries. Temperature fluctuations will have a potential impact on parasite development in the vector Anopheles mosquito.MethodsYear-long microclimate temperatures were recorded from a malaria-endemic area, Chennai, India, from September 2021 to August 2022. HOBO data loggers were placed in different vector resting sites including indoor and outdoor roof types. Downloaded temperatures were categorised by season, and the mean temperature was compared with data from the same study area recorded from November 2012 to October 2013. The extrinsic incubation period for Plasmodium falciparum and P. vivax was calculated from longitudinal temperatures recorded during both periods. Vector surveillance was also carried out in the area during the summer season.ResultsIn general, temperature and daily temperature range (DTR) have increased significantly compared to the 2012–2013 data, especially the DTR of indoor asbestos structures, from 4.30 ℃ to 12.62 ℃ in 2021–2022, unlike the marginal increase observed in thatched and concrete structures. Likewise, the average DTR of outdoor asbestos structures increased from 5.02 ℃ (2012–2013) to 8.76 ℃ (2021–2022) although the increase was marginal in thatched structures and, surprisingly, showed no such changes in concrete structures. The key finding of the extrinsic incubation period (EIP) is that a decreasing trend was observed in 2021–2022 compared to 2012–2013, mainly in indoor asbestos structures from 7.01 to 6.35 days, which negatively correlated with the current observation of an increase in temperature. Vector surveillance undertaken in the summer season revealed the presence of Anopheles breeding in various habitats. Anopheles stephensi could be collected using CDC light traps along with other mosquito species.ConclusionThe microclimate temperature has increased significantly over the years, and mosquitoes are gradually adapting to this rising temperature. Temperature negatively correlates with the extrinsic incubation period of the parasite. As the temperature increases, the development of the parasite in An. stephensi will be faster because of a decrease in EIP, thus requiring relatively fewer days, posing a risk for disease transmission and a hindrance to malaria elimination efforts.Graphical

Cycling temperature treatments affect estimates of digestive performance in prairie lizards (Sceloporus consobrinus).

In nature, many organisms experience a daily range of body temperatures. Thermal performance at stable temperatures is often extrapolated to predict function in cyclical environments. However, temperature order and cyclicity may influence physiological processes. The current study compared energy intake, digestive passage time and energy budgets at a stable temperature (33°C) and two temperature cycles in lizards (Sceloporus consobrinus), to determine (1) whether stable treatments adequately project performance in a cycling environment and (2) whether temperature order influences performance. Cycles had a mean temperature of 33°C, and rotated through 30°C, 33°C and 36°C daily, with equal durations of time at each temperature but differing temperature order, with warm days and cool nights in cycle 1 and cool days and warm nights in cycle 2. For analyses, performance in the stable treatment was compared with that during cycles. If temperature is the primary factor regulating performance, then performance from the stable treatment and cycles should compare favorably. However, physiological performance varied based on temperature treatment. Energy intake and budgets were similar between the stable trial and cycle 1 but not cycle 2. However, passage time did not differ. Notably, the two cycling regimes consistently varied in performance, indicating that temperature order plays a primary role in regulating performance. Physiological data collection requires careful consideration of effects of cycling versus stable temperature treatments. Stable temperatures do not consistently represent performance in cycling regimes and consideration should be paid not only to which temperatures animals experience but also to how temperature is experienced in nature.

GPEP v1.0: the Geospatial Probabilistic Estimation Package to support Earth science applications

Abstract. Ensemble geophysical datasets are foundational for research to understand the Earth system in an uncertainty-aware context and to drive applications that require quantification of uncertainties, such as probabilistic hydro-meteorological estimation or prediction. Yet ensemble estimation is more challenging than single-value spatial interpolation, and open-access routines and tools are limited in this area, hindering the generation and application of ensemble geophysical datasets. A notable exception in the last decade has been the Gridded Meteorological Ensemble Tool (GMET), which is implemented in FORTRAN and has typically been configured for ensemble estimation of precipitation, mean air temperature, and daily temperature range, based on station observations. GMET has been used to generate a variety of local, regional, national, and global meteorological datasets, which in turn have driven multiple retrospective and real-time hydrological applications. Motivated by an interest in expanding GMET flexibility, application scope, and range of methods, we have developed the Python-based Geospatial Probabilistic Estimation Package (GPEP) that offers GMET functionality along with additional methodological and usability improvements, including variable independence and flexibility, an efficient alternative cross-validation strategy, internal parallelization, and the availability of the scikit-learn machine learning library for both local and global regression. This paper describes GPEP and illustrates some of its capabilities using several demonstration experiments, including the estimation of precipitation, temperature, and snow water equivalent ensemble analyses on various scales.

Rapid weather changes are associated with daily hospital visitors for atrial fibrillation accompanied by abnormal ECG repolarization: a case-crossover study

BackgroundAtrial fibrillation (AF) is highly prevalent in the population, yet the factors contributing to AF events in susceptible individuals remain partially understood. The potential relationship between meteorological factors and AF, particularly with abnormal electrocardiograph (ECG) repolarization, has not been adequately studied. This case-crossover study aims to investigate the association between meteorological factors and daily hospital visits for AF with abnormal ECG repolarization in Shanghai, China.MethodsThe study cohort comprised 10,325 patients with ECG-confirmed AF who sought treatment at Shanghai Sixth People's Hospital between 2015 and 2018. Meteorological and air pollutant concentration data were matched with the patient records. Using a case-crossover design, we analyzed the association between meteorological factors and the daily count of hospital visitors for AF with abnormal ECG repolarization at our AF center. Lag analysis models were applied to examine the temporal relationship between meteorological factors and AF events.ResultsThe analysis revealed statistically significant associations between AF occurrence and specific meteorological factors. AF events were significantly associated with average atmospheric pressure (lag 0 day, OR 0.9901, 95% CI 0.9825–0.9977, P < 0.05), average temperature (lag 1 day, OR 0.9890, 95% CI 0.9789–0.9992, P < 0.05), daily pressure range (lag 7 days, OR 1.0195, 95% CI 1.0079–1.0312, P < 0.01), and daily temperature range (lag 5 days, OR 1.0208, 95% CI 1.0087–1.0331, P < 0.01). Moreover, a significant correlation was observed between daily pressure range and daily temperature range with AF patients, particularly those with abnormal ECG repolarization, as evident in the case-crossover analysis.ConclusionThis study highlights a significant correlation between meteorological factors and daily hospital visits for AF accompanied by abnormal ECG repolarization in Shanghai, China. In addition, AF patients with abnormal ECG repolarization were found to be more vulnerable to rapid daily changes in pressure and temperature compared to AF patients without such repolarization abnormalities.

Avian responses to climate extremes: insights into abundance curves and species sensitivity using the UK Breeding Bird Survey

Climate change remains one of the most urgent challenges for biodiversity conservation. Recent studies have highlighted that climate extremes (CLEXs) can lead to widespread and negative effects across all taxa and ecological levels, but most of these studies are based on short-term periods and small spatial scales and lack a multi-species approach. Here, using generalised additive models (GAMs) and the UK Breeding Bird Survey (BBS), we described response curves for the abundance of 100 resident bird species over large spatial and temporal scales and identified the species showing a greater sensitivity to CLEXs. We used five climatic indices computed at 1-km spatial resolution as proxies of CLEXs during the winter or breeding season and considered both 1- and 2-year lagged effects. The results demonstrated widespread and significant effects of CLEXs on bird abundances at both time lags and in both seasons. Winter frost days (FD0), summer days (SU25) during the breeding season and simple precipitation intensity index (SDII) during the breeding season mainly showed negative effects. Daily temperature range (DTR) in both winter and breeding season and dry days (DD) during the breeding season led to diversified responses across the species, with a prevalence of positive effects. A large proportion of species showed a high sensitivity to CLEXs, highlighting that these species may deserve attention in future studies aimed at biodiversity conservation. We demonstrated that CLEXs can represent a significant driver affecting population abundances over large spatial and temporal scales, emphasising the need for understanding mechanistic processes at the basis of the observed effects.

The ecological suitability area of Cirsium lineare (Thunb.) Sch.-Bip. under future climate change in China based on MaxEnt modeling.

Many kinds of medicinal ingredients occur in Cirsium lineare that have good clinical efficacy, conferring on this species its high medicinal development value. However, with a rapidly changing global climate, it is increasingly imperative to study the factors affecting the habitat distribution and survival of species. We predicted the current and future distribution areas of suitable habitats for C. lineare, analyzed the importance of environmental variables in influencing habitat shifts, and described the alterations to suitable habitats of C. lineare in different periods (modern, 2050s, and 2070s) and scenarios (RCP2.6, RCP4.5, and RCP8.5). The results show that, under the current climate, the total suitable area of C. lineare is about 2,220,900 km2, of which the highly suitable portion amounts to ca. 292,600 km2. The minimum temperature of the coldest month, annual precipitation, and mean daily temperature range are the chief environmental variables affecting the distribution of habitat for C. lineare. In the same period, with rising greenhouse gas emission concentrations, the total suitable area will increase. In general, under future climate change, the suitable habitat for C. lineare will gradually migrate to the west and north, and its total suitable area will also expand. The results of this experiment can be used for the conservation and management of the wild resources of C. lineare. We can choose suitable growth areas to protect the medicinal resources of C. lineare through insitu conservation and artificial breeding.