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Seaweeds represent a vast resource that remains underutilized as an ingredient in aquafeeds. Here we probed the effect of addition of AquaArom, a seaweed meal derived from brown seaweeds (Laminaria sp., kelp), to fish feed on growth performance, antioxidant capacity and temperature responsiveness of mitochondrial respiration. A commercial salmonid feed was mixed with 0 (control), 3, 6 and 10% seaweed and fed to Atlantic salmon (Salmo salar) smolts for 30 days. The smolts consumed more of the seaweed-supplemented food relative to the control and there were no mortalities. Compared with the control, the final fish weight, standard length, weight gain and SGR were higher in fish fed diets supplemented with the 3 and 10% seaweed, while growth performance for fish maintained on 6% seaweed remained neutral. Importantly, seaweed supplementation increased protein efficiency ratio (PER) and tended to improve food conversion ratio (FCR). Although the hepatosomatic and visceral indices did not change, whole gut and intestinal weights and lengths were higher in fish maintained on seaweed-supplemented diets suggesting increased retention time and a larger surface area for food digestion and nutrient absorption. Measurement of antioxidant status revealed that seaweed supplementation dose-dependently increased plasma total antioxidant capacity as well as the level of glutathione, and activities of catalase and superoxide dismutase in liver mitochondria. Moreover, seaweed supplementation reduced the effect of acute temperature rise on mitochondrial respiration and proton leak. Overall, these data suggest that AquaArom can be mixed with fish food up to 10% to increase food consumption and enhance growth performance, as well as to improve antioxidant capacity and alleviate adverse effects of stressors such as temperature in fish.

The coast of Terra Nova Bay (TNB) is known as one of the intense katabatic wind confluence zones in Antarctica. Strong westerly winds with topography‐specific foehn effects (foehn‐like winds, FLWs) could have influenced surface temperatures in this area downwind of the Transantarctic Mountains, yet their impact remains unstudied. Jang Bogo Station (JBS) in TNB has weak winds year‐round, with occasional strong winds causing significant winter temperature increases. This study aims to investigate the FLWs and their recent variability in occurrence at JBS in terms of surface temperature variability. During the strong wind events, the surface warms due to foehn effects such as adiabatic heating and vertical mixing. FLWs occur approximately 16% (10%) of the time in winter (annually). FLWs are caused by cyclones in the eastern Ross Sea. Meteorological records for 2015–2022 revealed an increased FLW frequency, particularly in winter, which has increased temperatures in recent years. Plain Language Summary Foehn is mainly related to winds ascending along high mountains, and the resulting descending winds make the air warm and dry on the mountain's leeward side. They significantly contribute to rising surface temperature and melting ice shelf in Antarctica. Foehn‐like winds (FLWs), different from typical foehn but with the same effect, were speculated to occur on the coasts of Terra Nova Bay (TNB), Ross Sea, which are known to have intense katabatic winds (strong and cold air blowing along a slope inland to the coast) year‐round because most coastal areas are located downwind of the Transantarctic Mountains. This study investigated whether strong inland winds are foehn‐like and related to the recent temperature increase at Jang Bogo Station in TNB. We found that the downward strong westerly winds from inland are foehn‐like, and their increase in frequency has increased the surface temperature at Jang Bogo Station over the last 8 years. Large‐scale cyclones in the eastern Ross Sea are responsible for FLWs. The change in FLW frequency may imply atmospheric circulation changes over the Ross Sea. Key Points The study showed that the foehn effect is significant when strong inland winds blow from west, particularly in winter The recent rise in winter temperatures is related to an increase in the frequency of foehn‐like wind above Synoptic scale cyclones centered in the eastern Ross Sea cause foehn‐like winds at Jang Bogo Station

This study assessed the urban heat island (UHI) effect and its driver in five major cities of Pakistan from 2001 to 2022 using Moderate Resolution Imaging Spectroradiometer (MODIS) daily diurnal land surface temperature (LST) data. The study also used the City Clustering Algorithm (CCA) and yearly land cover data from MODIS to quantify the growth of urban areas and statistical data to estimate the changes in population density. The results showed a temperature difference of 4.1 − 5.0°C at night and 2.9 − 4.1°C during the day between the city area and outskirts. More regions showed a significant temperature rise during the nighttime, with an LST increase of more than 0.15°C/year. Major cities of Pakistan have expanded more, ranging from 1.5 to 5.87%, than the population growth (51.6 to 125.5%), which caused a rapid increase in urban population density. This study found a strong correlation between population density and LST, ranging from 0.68 to 0.84 for nighttime LST and from 0.60 to 0.78 for daytime LST. The analysis of changes in urban built-up areas revealed an increase in population density by nearly threefold in some cities. This suggests that dense urbanization is the main factor behind the rapid rise in the UHI effect. Global temperature rise coupled with increased population density would cause a continuous increase in UHI in mega cities of Pakistan. Unless effective mitigation measures are implemented, it will lead to a notable rise in public health risks, water and energy consumption, and damage to urban ecosystems.

Preliminary study suggests possible link between long-term heat exposure and molecular markers of ageing. Preliminary study suggests possible link between long-term heat exposure and molecular markers of ageing.

Prolonged and repeated drought, as seen in India and other parts of South Asia, is a symptom of climate change, which is partially the result of human interventions. The performance of the widely used drought metrics Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) are evaluated for 18 stations in Uttar Pradesh state for the period 1971 to 2018 in this study. Drought characteristics such as intensity, duration, and frequency of different categories are estimated and compared based on SPI and SPEI. In addition, station proportion is estimated at a different timescales, providing a better insight into temporal variability drought of a specific category. Spatiotemporal trend variability of SPEI and SPI was investigated at a significance level of 0.05 using the non-parametric Mann–Kendall (MK) test. SPEI adds the effect of temperature rise and deficit change on the drought occurrences of different classes. SPEI provides a better estimation of drought characteristics due to its consideration of temperature change in the drought severity. The more significant number of drying events accounted for a timescale of 3 months and 6 months, reflecting the higher variability of the seasonal fluctuation of water balance over the state. At 9-month and 12-month timescales, SPI and SPEI fluctuate gradually with considerable differences between the duration and severity of the drought event. This study reveals that there have been a substantial number of drought events over the state during the last two decades (2000 to 2018). The results conclude that the study area is at risk of erratic meteorological drought conditions where the western part of the study is worst affected compared to the eastern part of Uttar Pradesh (India).

Rising global temperatures caused by human-mediated change has already triggered significant responses in organismal physiology, distribution and ecosystem functioning. Although the effects of rising temperature on the physiology of individual organisms are well understood, the effect on community-wide processes has remained elusive. The fixation of carbon via primary productivity is an essential ecosystem function and any shifts in the balance of primary productivity and respiration could alter the carbon balance of ecosystems. Here we show through a series of tests that respiration of naturally structured algal assemblages in southern New Zealand greatly increases with rising temperature, with implications for net primary productivity (NPP). The NPP of in situ macroalgal assemblages was minimally affected by natural temperature variation, possibly through photo-acclimation or temperature acclimation responses, but respiration rates and compensating irradiance were negatively affected. However, laboratory experiments testing the impacts of rising temperature on several photosynthetic parameters showed a decline in NPP, increasing respiration rates and increasing compensating irradiance. The respiration Q10 of laboratory assemblages (the difference in metabolic rates over 10°C) averaged 2.9 compared to a Q10 of 2 often seen in other autotrophs. However, gross primary productivity (GPP) Q10 averaged 2, indicating that respiration was more severely affected by rising temperature. Furthermore, combined high irradiance and high temperature caused photoinhibition in the laboratory, and resulted in 50% lower NPP at high irradiance. Our study shows that communities may be more severely affected by rising global temperatures than would be expected by responses of individual species. In particular, enhanced respiration rates and rising compensation points have the potential to greatly affect the carbon balance of macroalgal assemblages through declines in sub-canopy NPP, the impacts of which may be exacerbated over longer time-scales and could result in declines in sub-canopy species richness and abundance.

The temperature rise during the growing season on the Tibetan Plateau (TP) is crucial for the local vegetation phenology and atmospheric circulation. In this study, we investigated the possible effects of soil moisture (SM) anomalies associated with the freeze–thaw process on the surface air temperature (SAT) rise during the growing season using observations and reanalysis data from 1979 to 2014. Results demonstrate that winter SM anomalies associated with the freeze–thaw process can persist until July, significantly modulating SAT rise intensity from May to July on the TP. Positive winter SM anomalies can lead to decreased in SAT in May but increased in SAT in July, thus strengthening the SAT rise from May to July. Further analysis of physical mechanisms suggest the positive winter SM anomaly leads to the increase of surface latent heat flux but the decrease of surface sensible heat flux in May, thus cooling the SAT. As July approaches, significantly increased atmospheric water vapor caused by the positive winter SM anomaly leads to the enhancement of surface downward longwave radiation, which exceeds the cooling effect of decreased sensible heat, resulting in a warmer SAT. Previous studies mainly revealed the “drier SM—higher SAT” feedback. Here we highlight that the thermal variations caused by SM anomalies related with the freeze–thaw process are complicated in the TP, with completely opposite climatic effects during different months.

The projection and identification of historical and future changes in climatic systems is crucial. This study aims to assess the performance of CMIP6 climate models and projections of precipitation and temperature variables over the Upper Blue Nile Basin (UBNB), Northwestern Ethiopia. The bias in the CMIP6 model data was adjusted using data from meteorological stations. Additionally, this study uses daily CMIP6 precipitation and temperature data under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios for the near (2015–2044), mid (2045–2074), and far (2075–2100) periods. Power transformation and distribution mapping bias correction techniques were used to adjust biases in precipitation and temperature data from seven CMIP6 models. To validate the model data against observed data, statistical evaluation techniques were employed. Mann–Kendall (MK) and Sen’s slope estimator were also performed to identify trends and magnitudes of variations in rainfall and temperature, respectively. The performance evaluation revealed that the INM-CM5-0 and INM-CM4-8 models performed best for precipitation and temperature, respectively. The precipitation projections in all agro-climatic zones under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios show a significant (p < 0.01) positive trend. The mean annual maximum temperature over UBNB is estimated to increase by 1.8 °C, 2.1 °C, and 2.8 °C under SSP1-2.6, SSP2-4.5, and SSP5-8.5 between 2015 and 2100, respectively. Similarly, the mean annually minimum temperature is estimated to increase by 1.5 °C, 2.1 °C, and 3.1 °C under SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. These significant changes in climate variables are anticipated to alter the incidence and severity of extremes. Hence, communities should adopt various adaptation practices to mitigate the effects of rising temperatures.

The current study on spatiotemporal variability of temperature presents a holistic approach for quantifying the joint space–time variability of extreme temperature indices over the physio-climatically heterogeneous Tapi River basin (TRB) using two unsupervised machine learning algorithms, i.e., principal component analysis (PCA) and cluster analysis. The long-term variability in extreme temperature indices, recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI), was evaluated for 1951–2016. The magnitude and statistical significance of the temporal trend in extreme temperature indices were estimated using non-parametric Sen’s slope estimator and modified Mann Kendall (MMK) tests, respectively. The multivariate assessment of temporal trends using PCA resulted in four principal components (PCs) encapsulating more than 90% variability. The cluster analysis of corresponding PCs resulted in two spatial clusters exhibiting homogeneous spatiotemporal variability. Cluster 1 is characterized by significantly increasing hottest, very hot, and extremely hot days with rising average maximum temperature and intraday temperature variability. On the other hand, cluster 2 showed significantly rising coldest nights, mean minimum, mean temperature, and Tx37 with significantly decreasing intraday and interannual temperature variability, very cold, and extremely cold nights with reducing cold spell durations. The summertime heat stress computation revealed that the Purna sub-catchment of the Tapi basin is more vulnerable to various health issues and decreased work performance (> 10%) for more than 45 days per year. The current study dealing with the associated effects of rising temperature variability on crop yield, human health, and work performance would help policymakers formulate better planning and management strategies to safeguard society and the environment.

Knowledge of the effects of climate change on agro-ecosystems is fundamental to identifying local actions aimed to maintain productivity and reduce environmental issues. This study investigates the effects of climate perturbation on the European crop and grassland production systems, combining the findings from two specific biogeochemical models. Accurate and high-resolution management and pedoclimatic data were employed. Results have been verified for the period 1978–2004 (historical period) and projected until 2099 with two divergent intensities: the Intergovernmental Panel on Climate Change (IPCC) climate projections, Representative Concentration Pathway (RCP) 4.5 and RCP8.5. We have provided a detailed overview of productivity and the impacts on management (sowing dates, water demand, nitrogen use efficiency). Biogenic greenhouse gas balance (N2O, CH4, CO2) was calculated, including an assessment of the gases' sensitivity to the leading drivers, and a net carbon budget on production systems was compiled. Results confirmed a rise in productivity in the first half of the century (+5 % for croplands at +0.2 t DM ha−1 yr−1, +1 % for grasslands at +0.1 t DM ha−1 yr−1; DM denotes dry matter), whereas a significant reduction in productivity is expected during the period 2050–2099, caused by the shortening of the length of the plant growing cycle associated with rising temperatures. This effect was more pronounced for the more pessimistic climate scenario (−6.1 % for croplands and −7.7 % for grasslands), for the Mediterranean regions and in central European latitudes, confirming a regionally distributed impact of climate change. Non-CO2 greenhouse gas emissions were triggered by rising air temperatures and increased exponentially over the century, often exceeding the CO2 accumulation of the explored agro-ecosystems, which acted as potential C sinks. The emission factor for N2O was 1.82 ± 0.07 % during the historical period and rose to up to 2.05 ± 0.11 % for both climate projections. The biomass removal (crop yield, residues exports, mowing and animal intake) converted croplands and grasslands into net C sources (236 ± 107 Tg CO2 eq. yr−1 in the historical period), increasing from 19 % to 26 % during the climate projections, especially for RCP4.5. Nonetheless, crop residue restitution might represent a potential management strategy to overturn the C balance. Although with a marked latitudinal gradient, water demand will double over the next few decades in the European croplands, whereas the benefit in terms of yield (+2 % to +10 % over the century) will not contribute substantially to balance the C losses due to climate perturbation.