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608 results for “Heat stress”
Data from: Heat stress conditions affect the social network structure of free‐ranging sheep
<p>Extreme weather conditions, like heatwave events, are becoming more frequent with climate change. Animals often modify their behaviour to cope with environmental changes and extremes. During heat stress conditions, individuals change their spatial behaviour and increase the use of shaded areas to assist with thermoregulation. Here, we suggest that for social species, these behavioural changes and ambient conditions have the potential to influence an individual's position in its social network, and the social network structure as a whole. We investigated whether heat stress conditions (quantified through the temperature humidity index) and the resulting use of shaded areas, influence the social network structure and an individual's connectivity in it. We studied this in free‐ranging sheep in the arid zone of Australia, GPS‐tracking all 48 individuals in a flock. When heat stress conditions worsened, individuals spent more time in the shade and the network was more connected (higher density) and less structured (lower modularity). Furthermore, we then identified the behavioural change that drove the altered network structure and showed that an individual's shade use behaviour affected its social connectivity. Interestingly, individuals with intermediate shade use were most strongly connected (degree, strength, betweenness), indicating their importance for the connectivity of the social network during heat stress conditions. Heat stress conditions, which are predicted to increase in severity and frequency due to climate change, influence resource use within the ecological environment. Importantly, our study shows that these heat stress conditions also affect the animal's social environment through the changed social network structure. Ultimately, this could have further flow on effects for social foraging and individual health since social structure drives information and disease transmission.</p>
Beyond a single temperature threshold: applying a cumulative thermal stress framework to plant heat tolerance
<p>Most plant thermal tolerance studies focus on single critical thresholds, which limit the capacity to generalise across studies and predict heat stress under natural conditions. In animals and microbes, thermal tolerance landscapes describe the more realistic, cumulative effects of temperature. We tested this in plants by measuring the decline in leaf photosynthetic efficiency (F<sub>V</sub>/F<sub>M</sub>) following a combination of temperatures and exposure times, then modelled these physiological indices alongside recorded environmental temperatures. We demonstrate that a general relationship between stressful temperatures and exposure durations can be effectively employed to quantify and compare heat tolerance within and across plant species and over time. Importantly, we show how F<sub>V</sub>/F<sub>M</sub> curves translate to plants under natural conditions, suggesting that environmental temperatures often impair photosynthetic function. Our findings provide more robust descriptors of heat tolerance in plants and suggest that heat tolerance in disparate groups of organisms can be studied with a single predictive framework.</p>
Data from : Limited influence of irrigation on pre-monsoon heat stress in the Indo-Gangetic Plain
<p>The dataset contains WRF-CLM4 simulation post-processed output for three experiments named CTL, AGR, and MOD for pre-monsoon (April-May) from 2004-2016. Here, CTL represents WRF-CLM4 simulation with no irrigation, AGR represents WRF-CLM4 simulation with agricultural census-based irrigation data and MOD represents WRF-CLM4 simulation with model-estimated irrigation data. Here, C1, C2, and C3 represent different parameterization scheme combinations.</p> <ul> <li>C1:Mellor-Yamada Nakanishi and Niino Level 3 - WRF Double-Moment 6-class scheme - Tiedtke scheme (MYNN3-WDM6-Tiedtke)</li> <li>C2:Mellor-Yamada Nakanishi and Niino Level 3 - WRF Single-Moment 6-classscheme - KF scheme (MYNN3-WSM6-KF)</li> <li>C3:Mellor-Yamada Nakanishi and Niino Level 3 - WRF Single-Moment 6-class scheme - Grell3D (MYNN3-WSM6 Grell3D)</li> </ul> <p>The post-processed output contains the following variables:</p> <ol> <li>Land Surface Temperature</li> <li>Mean Air Temperature</li> <li>Maximum Air Temperature</li> <li>Wet-bulb Temperature</li> <li>Specific Humidity</li> <li>Latent Heat Flux</li> <li>Sensible Heat Flux</li> <li>Planet Boundary Layer Height</li> <li>Surface Pressure</li> <li>Relative Humidity</li> </ol> <p>The dataset also contains a spreadsheet that contains the FAO monthly calendar of the percentage of crop irrigation and pre-monsoon season crop calendar based on crop production data and annual reports “Agricultural Statistics At a Glance” from the Government of India. In addition, the file contains raw pre-monsoon data (area under the crop and crop irrigated area) from 2004 to 2016 for five crops (rice, maize, gram, sugarcane, and sunflower) over Indo-Gangetic Plain (Bihar, Uttar Pradesh, Haryana, Punjab, and Rajasthan). The pre-monsoon irrigation files for WRF contain irrigation data input for the WRF-CLM4 model.</p>
Future Heat Stress Indicators for Johannesburg and Ekurhuleni
<p>This dataset is part of the scientific paper: Souverijns, N., De Ridder, K., Veldeman, N., Lefebre, F., Kusambiza-Kiingi, F., Memela, W., Jones, N.K.W., 2022. Urban heat in Johannesburg and Ekurhuleni, South Africa: A meter-scale assessment and vulnerability analysis. Urban Climate, 46, 101331. <a href="https://doi.org/10.1016/j.uclim.2022.101331">https://doi.org/10.1016/j.uclim.2022.101331</a></p> <p>Heat stress indicators for present and future climates for the cities of Johannesburg and Ekurhuleni (South Africa).at 30m spatial resolution calculated with UrbClim (De Ridder et al., 2015) for the following scenarios:</p> <p>- 2001-2020: present time (ERA5 input data)</p> <p>- 2021-2040 RCP4.5 (CMIP5 ensemble)</p> <p>- 2021-2040 RCP8.5 (CMIP5 ensemble)</p> <p>- 2041-2060 RCP4.5 (CMIP5 ensemble)</p> <p>- 2041-2060 RCP8.5 (CMIP5 ensemble)</p> <p>For each of the 23 indicators, an overview image is available at high resolution. Furthermore, georeferenced GeoTiffs are available to visualize & analyse the indicators on the users preferred system. The indicators are available in EPSG4326/WGS84. A description of each indicator is given:</p> <p>- Cooling degree hours: Annual number of hours during which the temperatures rises over 25°C, multiplied by the number of degrees the temperature rises above 25°C. This is an international standard to estimate the energy demand for air conditioning use.</p> <p>- CSDI: Cold spell duration index. Annual number of days with at least six consecutive days when the night temperature < 10th percentile</p> <p>- Heatwave days: Number of heatwave days per year calculated following the definition of the South African Weather Service. If the maximum temperature at a particular town is expected to meet or exceed 5 degrees C above the average maximum temperature of “the hottest month” for that particular place (this is 32°C for Johannesburg & Ekurhuleni), as well as persisting in that mode for 3 days or more (https://www.weathersa.co.za/home/weatherques)</p> <p>- T2M_daily_mean_max: Average daily maximum temperature</p> <p>- T2M_daily_mean_max_topography: Daytime Urban Heat Island corrected for topography</p> <p>- T2M_daily_mean_min: Average daily minimum temperature</p> <p>- T2M_daily_mean_min_topography: Nighttime Urban Heat Island corrected for topography</p> <p>- T2M_dayover25: Annual number of days attaining a maximum temperature > 25°C</p> <p>- T2M_dayover25_duetourban: Annual number of days attaining a maximum temperature > 25°C that are caused by urban canopy</p> <p>- T2M_dayover30: Annual number of days attaining a maximum temperature > 30°C</p> <p>- T2M_dayover30_duetourban: Annual number of days attaining a maximum temperature > 30°C that are caused by urban canopy</p> <p>- T2M_max: Absolute maximum temperature</p> <p>- T2M_mean: Absolute average temperature</p> <p>- T2M_min: Absolute minimum temperature</p> <p>- T2M_nightover20: Number of nights attaining a minimum temperature not dropping below 20°C</p> <p>- T2M_nightover25: Number of nights attaining a minimum temperature not dropping below 25°C</p> <p>- TN10P: Annual number of days when the night temperature < 10th percentile</p> <p>- TN90P: Annual number of days when the night temperature > 90th percentile</p> <p>- TN_max: Annual minimum nighttime warmest temperature</p> <p>- TX10P: Annual number of days when the day temperature < 10th percentile</p> <p>- TX90P: Annual number of days when the day temperature > 90th percentile</p> <p>- TX_min: Annual maximum daytime coolest temperature</p> <p>- WSDI: Warm Spell Duration Index. Annual number of days with at least six consecutive days when daytime temperatues > 90th percentile</p>
Data from: Breeding heat tolerant orchardgrass germplasm for summer persistence in high temperature stress environments of the southeastern United States
<p>This is digital research data corresponding to a published manuscript, Breeding heat tolerant orchardgrass germplasm for summer persistence in high temperature stress environments of the southeastern United States, in Crop Science, Volume 61, p. 1915 - 1925. Orchardgrass (Dactylis glomerata L.) could serve as a cool-season perennial in southeastern production systems, but often does not behave as a true perennial under high temperature stress conditions of the region. This work sought to develop heat-tolerant orchardgrass germplasm through recurrent phenotypic selection (RPS) that would both reduce secondary seed dormancy caused by high soil temperatures and improve stand persistence over summer months. Selection was conducted in a growth chamber 40/30 °C (12/12 h, light/darkness), with germinated seedlings subjected to an additional 2–3 weeks of 40/30 °C conditions. The base germplasm (Cycle 0) and selected individuals (Cycles 1–3) were transplanted into the field, then harvested for seed. Forty-degree germination tests compared mean cumulative germination, velocity of germination within 8 days (VOG8), and realized heritability. Stand persistencewas assessed 1 year after transplanting.</p>
Still standing: the heat protection delivered by a facultative symbiont to its aphid host is resilient to repeated thermal stress
<p>This is the dataset for the article "<strong>Still standing: the heat protection delivered by a facultative symbiont to its aphid host is resilient to repeated thermal stress</strong>".</p> <p>This experimental study focused on the heat-protective mutualism between the pea aphid <strong><em>Acyrthosiphon pisum</em></strong> and the facultative bacterium <strong><em>Serratia symbiotica</em></strong>. We exposed two aphid lines (5A: deprived of <em><strong>S. symbiotica</strong></em>, 5AR: infected by <strong><em>S. symbiotica</em></strong>) to a varying number of heat shocks (35°C for 2 h) applied during insect immature development: none (control), one, two, or three. We recorded aphid immature survival rate, total longevity, immature development time, lifetime fecundity and hind tibia length (body size).</p> <p>. Individual = identification of the individual</p> <p>. Line = aphid clonal line, either deprived of (5A) or infected by <em><strong>S. symbiotica</strong> </em>(5AR)</p> <p>. Temp = thermal treatment, defined by the number of heat shocks applied during aphid juvenile life (0 = control, 1, 2 or 3)</p> <p>. Survival = whether (Y) or not (N) the individual survived until reproduction </p> <p>. Adulthood = time elapsed between birth and first reproduction (in days)</p> <p>. Longevity = time elapsed between birth and death (in days)</p> <p>. Fecundity = total number of larvae produced by each aphid throughout lifetime</p> <p>. Wing = whether (Y) or not (N) the individual developed wings following imaginal moult</p> <p>. Tibia = hind tibia length as a proxy of body size (in mm)</p>
Data for: Temperate and tropical lizards are vulnerable to climate warming due to increased water loss and heat stress
<p><span>Climate warming has imposed profound impacts on species globally. Understanding the vulnerabilities of species from different latitudinal regions to warming climates is critical for biological conservation. </span><span>Using five species of <em>Takydromus </em>lizards as a study system, we quantified physiological and life-history responses and geography range change across latitudes under climate warming. Using integrated biophysical models and hybrid species distribution models, w</span><span>e found: (1) thermal safety margin is larger at high latitudes, and is predicted to decrease under climate warming for lizards at all latitudes; (2) climate warming will speed up embryonic development and increase annual activity time of adult lizards, but will exacerbate water loss of adults across all latitudes; and (3) species across latitudes are predicted to experience habitat contraction under climate warming due to different limitations: tropical and subtropical species are vulnerable due to increased extremely high temperatures, whereas temperate species are vulnerable due to both extremely high temperatures and increased water loss. This study provides a comprehensive understanding of the vulnerability of species from different latitudinal regions to climate warming in ectotherms and also highlights the importance of integrating environmental factors, behavior, physiology, and life-history responses in predicting the risk of species to climate warming.</span></p>
Figure 9 in Incubation parameters, offspring growth, and behavioral adaptations to heat stress of Black Skimmers (Rynchops niger) in a Neotropical inland colony (Aves, Charadriiformes, Laridae)
Figure 9. Plumage development of a Black Skimmer (Rynchops niger) chick from Praia do Totelão, Pantanal, Mato Grosso, Brazil. (A) Camouflaged down plumage (Day 3); (B) appearance of dorsal pinfeathers and primaries (Day 7); (C) dorsal pinfeathers opened (Day 11); (D) primaries opened (Day 15); (E) completely developed immature plumage (Day 21). Photos: CO. BRA/INAU.
Figure 8 in Incubation parameters, offspring growth, and behavioral adaptations to heat stress of Black Skimmers (Rynchops niger) in a Neotropical inland colony (Aves, Charadriiformes, Laridae)
Figure 8. Mensural data of the single Black Skimmer (Rynchops niger) chick surveyed in August-September 2015 that reached the fledging phase at Praia do Totelão, Pantanal, Mato Grosso, Brazil (n = 1; accuracy = ± 0.01 cm). (A) Development of bill length (BL), bill width (BW), and tarsus length (TS) as a function of age (days). (B) Development of total body length (TL) and wing length (WL) as a function of age (days).
Figure 5 in Incubation parameters, offspring growth, and behavioral adaptations to heat stress of Black Skimmers (Rynchops niger) in a Neotropical inland colony (Aves, Charadriiformes, Laridae)
Figure 5. Developmental stages of a Black Skimmer (Rynchops niger) clutch (nest 4S) at Praia doTotelão, Pantanal, Mato Grosso, Brazil, from July to September 2015, with three fertilized eggs revealed by thermal imaging (right); with maximum (Max), minimum (Min), and mean temperature (Ds) inside the nest (white outline). Stages: (A) Day 8, (B) Day 14, and (C) Day 18 (two days before hatching). Note the well-camouflaged eggs inside the nest depression exhibiting some variation in shell pattern (left), with narrow corrugations caused by adults' bills when relocating the eggs. Photos by CO. BRA/INAU.
Figure 4 in Incubation parameters, offspring growth, and behavioral adaptations to heat stress of Black Skimmers (Rynchops niger) in a Neotropical inland colony (Aves, Charadriiformes, Laridae)
Figure 4. Mean surface temperatures (Te) of 25 eggs (n = 7 nests) of the Black Skimmer (Rynchops niger) at Praia do Totelão, Pantanal, Mato Grosso, Brazil, during incubation from July to September 2015; not all eggs reached hatching. Confidence intervals are indicated by bars; the regression line (dotted) represents a significant increase between Day 1 and hatching (R² = 0.098, p <0.01, LME).
Figure 3 in Incubation parameters, offspring growth, and behavioral adaptations to heat stress of Black Skimmers (Rynchops niger) in a Neotropical inland colony (Aves, Charadriiformes, Laridae)
Figure 3. Thermal images of a Black Skimmer (Rynchops niger) nest (12N, white rectangles) at Praia do Totelão, Pantanal, Mato Grosso, Brazil, taken on the same day (6 September 2015) in the early (05:59 h, A) and late morning (11.45 h, B), showing the mean (Ds), minimum, and maximum nest temperature, surface ground temperature (crosses), and egg surface temperature (within rectangles). Scale on right: color scale associated with the respective temperatures. With a special optical filter water drops were visualized (Blue and red circles outside the nest and next to the three clutch contours) which were taken to the nest by both adults. Note in Fig. B the sand surface temperature of 53.7℃. Photos by CO.BRA/INAU.
Figure 2 in Incubation parameters, offspring growth, and behavioral adaptations to heat stress of Black Skimmers (Rynchops niger) in a Neotropical inland colony (Aves, Charadriiformes, Laridae)
Figure 2. Egg mass development in three surveyed Black Skimmer (Rynchops niger) nests (n = 7 eggs, 84 measurements) until hatching at Praia do Totelão, Pantanal, Mato Grosso, Brazil, throughout the incubation period in July- September 2015. Note that the number of eggs decreased to three toward the end of incubation due to predation. The regression line indicates a negative trend (R² = 0.043, p <0.05, LME) of egg mass over incubation time.
Sexual selection moderates heat stress response in males and females
<p><span>1. </span><span>A widespread effect of climate change is the displacement of organisms from their thermal optima. The associated thermal stress imposed by climate change has been argued to have a particularly strong impact on male reproduction but evidence for this postulated sex-specific stress response is equivocal. </span></p> <p><span>2. </span><span>One important factor that may explain intra- and interspecific variation in stress responses is sexual selection, which is predicted to magnify negative effects of stress. Nevertheless, empirical studies exploring the </span><span>interplay of sexual selection and heat stress </span><span>are still scarce. </span></p> <p><span>3. </span><span>We tested experimentally for an interaction between sexual selection and thermal stress in the red flour beetle Tribolium castaneum by contrasting heat responses in male and female reproductive success between setups of enforced monogamy versus polygamy. </span></p> <p><span>4. </span><span>We found that polygamy magnifies detrimental effects of heat stress in males but relaxes the observed negative effects in females. Our results suggest that sexual selection can reverse sex differences in thermal sensitivity, and may therefore alter sex-specific selection on alleles associated with heat tolerance. </span></p> <p><span>5. </span><span>Assuming that sexual selection and natural selection are aligned to favour the same genetic variants under environmental stress, our findings support the idea that sexual selection on males may promote the adaptation to current global warming.</span></p>
Dataset for: Identification of genomic regions of wheat associated with grain Fe and Zn content under drought and heat stress using genome-wide association study
<p>The study material in the GWAS panel with 282 advanced breeding lines of bread wheat genotypes from IARI stress breeding program was selected to map the genomic regions responsible for grain iron and Zinc content under drought and heat stress treatments.</p> <p>Phenotypic data:</p> <p>The GWAS panel was evaluated at IARI, New Delhi - DL (28.6550° N, 77.1888° E, MSL 228.61 m) under Irrigated (IR), Restricted Irrigated (RI) and Late sown (LS) treatment conditions with augmented RCBD design. Data was collected on Grain Iron and Grain zinc content along with thousand-grain weight. Around 20 g of grain sample from each of 282 genotypes from the GWAS panel under all three conditions were used for phenotyping GFeC and GZnC through high-throughput Energy Dispersive X-ray Fluorescence (ED-XRF) machine (model X-Supreme 8000; Oxford Instruments plc, Abingdon, United Kingdom) calibrated with glass beads-based values. To record TGW, manual counting of grains was followed and the weight of the grains was recorded in grams with an electronic balance.</p> <p>Genotypic data:</p> <p>Genomic DNA of the GWAS panel was extracted from the leaves of seedlings by Cetyl Trimethyl Ammonium Bromide (CTAB) method. The panel was genotyped using Axiom Wheat Breeder's Genotyping Array (Affymetrix, Santa Clara, CA, United States) having 35,143 genome-wide SNPs. The monomorphic, markers with minor allele frequency (MAF) of <5%, missing data of >20%, and heterozygote frequency >25% were removed from the analysis. The remaining set of 10546 high-quality SNPs was used in GWAS analysis.</p>
Heat Stress and Microbial Stress Induced Defensive Phenol Accumulation in Medicinal Plant Sparganium stoloniferum
Open the record for dataset details and reuse information.
Data for irrigation impacts on urban heat stress in North America
<p>Includes all model simulation results, summaries by urban clusters, and evaluation results of the study. <br><br>The netcdf files are for various model variables and simulations (noURB for no urban simulation, IRR for irrigation simulation, and CTRL for the urban with no irrigation simulation, which is treated as the baseline), the csv files are the summaries for various cases (by urban cluster, and by world and climate zone for model evaluations), and the geotiff files are the raster images for key variables shown in the manuscript.<br><br>The python notebook has all the scripts to estimate the heat stress metrics from the netcdf files.</p>
Analysis files for MSC Marc finite element software, Article: The analysis of shrink-fit connection – the methods of heating and the factors influencing the distribution of residual stresses
<p>This archive contains model files for Finite Element Analysis of the shrink-fit connection in crankshaft and the files for charts in GNUPlot.</p>
Bivariate GWA mapping reveals associations between aliphatic glucosinolates and plant responses to thrips and heat stress
<p>Supplemental data on bivariate GWA mapping of stress phenotypes and metabolomes of Arabidopsis.</p>
Datasets and codes for 'Heat stress effects on offspring compound across parental care'
<p>This repository contains the datasets and code associated with the manuscript, 'Heat Stress Effects on Offspring Compound Across Parental Care.' For inquiries regarding this repository, please contact the corresponding author, Syuan-Jyun Sun (<a rel="noopener">sjs243@ntu.edu.tw</a>).</p>
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