Climate change is exposing subarctic ecosystems to higher temperatures, increased nutrient availability, and increasing cloud cover. In this study, we assessed how these factors affect the fluxes of greenhouse gases (GHGs) (i.e., methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2)), and biogenic volatile organic compounds (BVOCs) in a subarctic mesic heath subjected to 34 years of climate change related manipulations of temperature, nutrient availability, and light. GHGs were sampled from static chambers and gases analyzed with gas chromatograph. BVOCs were measured using the push-pull method and gases analyzed with chromatography-mass spectrometry. The soil temperature and moisture content in the warmed and shaded plots did not differ significantly from that in the controls during GHG and BVOC measurements. Also, the enclosure temperatures during BVOC measurements in the warmed and shaded plots did not differ significantly from temperatures in the controls. Hence, this allowed for assessment of long-term effects of the climate treatment manipulations without interference of temperature and moisture differences at the time of measurements. Warming enhanced CH4 uptake and the emissions of CO2, N2O, and isoprene. Increased nutrient availability increased the emissions of CO2 and N2O but caused no significant changes in the fluxes of CH4 and BVOCs. Shading (simulating increased cloudiness) enhanced CH4 uptake but caused no significant changes in the fluxes of other gases compared to the controls. The results show that climate warming and increased cloudiness will enhance CH4 sink strength of subarctic mesic heath ecosystems, providing negative climate feedback, while climate warming and enhanced nutrient availability will provide positive climate feedback through increased emissions of CO2 and N2O. Climate warming will also indirectly, through vegetation changes, increase the amount of carbon lost as isoprene from subarctic ecosystems.

Temperature extremes exert a significant influence on terrestrial ecosystems, but the precise levels at which these extremes trigger adverse shifts in vegetation productivity have remained elusive. In this study, we have derived two critical thresholds, using standard deviations (SDs) of growing-season temperature and satellite-based vegetation productivity as key indicators. Our findings reveal that, on average, vegetation productivity experiences rapid suppression when confronted with temperature anomalies exceeding 1.45 SD above the mean temperature during 2001-2018. Furthermore, at temperatures exceeding 2.98 SD above the mean, we observe the maximum level of suppression, particularly in response to the most extreme high-temperature events. When Earth System Models are driven by a future medium emission scenario, they project that mean temperatures will routinely surpass both of these critical thresholds by approximately the years 2050 and 2070, respectively. However, it is important to note that the timing of these threshold crossings exhibits spatial variation and will appear much earlier in tropical regions. Our finding highlights that restricting global warming to just 1.5°C can increase safe areas for vegetation growth by 13% compared to allowing warming to reach 2°C above preindustrial levels. This mitigation strategy helps avoid exposure to detrimental extreme temperatures that breach these thresholds. Our study underscores the pivotal role of climate mitigation policies in fostering the sustainable development of terrestrial ecosystems in a warming world.

Fruit traits mediate animal-plant interactions and have to a large degree evolved to match the sensory capacities and morphology of their respective dispersers. At the same time, fruit traits are affected by local environmental factors, which may affect frugivore-plant trait match. Temperature has been identified as a major factor with a strong effect on the development of fruits, which is of serious concern because of the rising threat of global warming. Nonetheless, this primarily originates from studies on domesticated cultivars in often controlled environments. Little is known on the effect of rising temperatures on fruit traits of wild species and the implications this could have to seed dispersal networks, including downstream consequences to biodiversity and ecosystem functioning. In a case study of five plant species from eastern Madagascar, we addressed this using the elevation-for-temperature approach and examined whether a temperature gradient is systematically associated with variation in fruit traits relevant for animal foraging and fruit selection. We sampled across a gradient representing a temperature gradient of 1.5-2.6 °C, corresponding to IPCC projections. The results showed that in most cases there was no significant effect of temperature on the traits evaluated, although some species showed different effects, particularly fruit chemical profiles. This suggests that in these species warming within this range alone is not likely to drive substantial changes in dispersal networks. While no systemic effects were found, the results also indicate that the effect of temperature on fruit traits differs across species and may lead to mismatches in specific animal-plant interactions.

Drought is one of the foremost outcomes of global warming and global climate change. It is a serious threat to humans and other living beings. To reduce the adverse impact of drought, mitigation strategies as well as sound projections of extreme events are essential. This research aims to strengthen the robustness of anticipated twenty-first century drought by combining different Global Climate Models (GCMs). In this article, we develop a new drought index, named Maximum Relevant Prior Feature Ensemble index that is based on the newly proposed weighting scheme, called weighted ensemble (WE). In the application, this study considers 32 randomly scattered grid points within the Tibetan Plateau region and 18 GCMs of Coupled Model Intercomparison Project Phase 6 (CMIP6) of precipitation. In this study, the comparative inferences of the WE scheme are made with the traditional simple model averaging (SMA). To investigate the trend and long-term probability of various classes, this research employs Markov chain steady states probability, Mann-Kendall trend test, and Sen\'s Slope estimator. The outcomes of this research are twofold. Firstly, the comparative inference shows that the proposed weighting scheme has greater efficiency than SMA to conflate GCMs. Secondly, the research indicates that the Tibetan Plateau is projected to experience \"moderate drought (MD)\" in the twenty-first century.

Global crop production is severely affected by environmental factors such as drought, salinity, cold, flood etc. Among these stresses, drought is one of the major abiotic stresses reducing crop productivity. It is expected that drought conditions will further increase because of the increasing global temperature. In general, viruses are seen as a pathogen affecting the crop productivity. However, several researches are showing that viruses can induce drought tolerance in plants. This review explores the mechanisms underlying the interplay between viral infections and the drought response mechanisms in plants. We tried to address the molecular pathways and physiological changes induced by viruses that confer drought tolerance, including alterations in hormone signaling, antioxidant defenses, scavenging the reactive oxygen species, role of RNA silencing and miRNA pathway, change in the expression of several genes including heat shock proteins, cellulose synthase etc. Furthermore, we discuss various viruses implicated in providing drought tolerance and examine the range of plant species exhibiting this phenomenon. By applying current knowledge and identifying gaps in understanding, this review aims to provide valuable insights into the complex dynamics of virus-induced drought tolerance in plants, paving the way for future research directions and practical applications in sustainable agriculture.

BACKGROUND: Previous research has delved into the attitudes and behaviors of diverse professions regarding environmental sustainability. However, there needs to be more research specifically targeting radiographers. This study aims to survey radiographers\' perceptions, practices, and barriers to change concerning environmental sustainability in radiology.
METHODS: Institutional ethical approval was obtained (IRB-COHS-FAC-110-2024) and data collection was conducted using Google Forms (Google Inc., Mountain View, CA). The survey targeted 104 practicing radiographers across several countries. Questions were structured around five domains to gather insights into demographics, training in global warming and climate change, perceptions of sustainability and climate change, sustainability barriers, and current radiology practices on sustainability. Data analysis utilized descriptive and d inferential statistics.
RESULTS: One hundred and four radiographers completed the study. Females had a significantly higher attendance rate in environmental protection campaigns (P = 0.01). The majority of respondents (68%) believe in climate change\'s knowledge and impact on the natural world. Our survey findings demonstrate that 74% of respondents believe there\'s a need to improve sustainability practices. The most commonly used strategies to decrease energy consumption and emissions were low-energy lighting (60%), real-time power monitoring tools (41%), and energy-efficient heating systems (32%). A significant concern regarding sustainability emerges among respondents: time (50%) and lack of leadership (48%) are prevalent concerns among the identified barriers.
CONCLUSIONS: Participants are recognising the importance of environmental sustainability in radiology, but lack of leadership, support, authority, and facility limitations hinder their adoption.
UNASSIGNED: Radiology must prioritize environmental sustainability by providing resources and training for radiographers and collaborating with healthcare professionals, policymakers, and environmental experts to develop comprehensive strategies for a sustainable healthcare system.

The cloud responses to global warming are captured in various global climate models with distinct inferences on changes in cloud vertical structure as function of surface warming. However, long term observational evidences are scarce to validate the model outputs. Here, we have studied the changes in radiosonde derived cloud macro-physical properties and their association with other atmospheric variables during the period 2000-2019 in response to warming climate over the Indian summer monsoon region. We have observed a statistically significant increase in the frequency of cloudy days (∼13 % decade-1), high-level clouds (HLCs ∼11 % decade-1) and simultaneous decrease in low-level clouds (LLCs ∼8 % decade-1) over the Indian region during the monsoon season. The multiple linear regression, principle component analyses and further correlation analyses suggest significant associations between cloud vertical structure variations and large-scale climate indicators, such as global warming and El Niño-Southern Oscillation. The vertical extension of the tropospheric column and the upward shift of clouds, attributed to global warming, explain the changes observed in both HLCs and LLCs. These results contribute to a deeper understanding of the dynamic interplay between global climate change and regional cloud dynamics, with implications for weather and climate modeling.

In the context of global warming, the occurrence and severity of extreme events like atmospheric drought (AD) and warm spell duration index (WSDI) have increased, causing significant impacts on terrestrial ecosystems in Central Asia\'s arid regions. Previous research has focused on single extreme events such as AD and WSDI, but the effect of compound hot and dry events (CHWE) on grassland phenology in the arid regions of Central Asia remains unclear. This study utilized structural equation modeling (SEM) and the Pettitt breakpoint test to quantify the direct and indirect responses of grassland phenology (start of season - SOS, length of season - LOS, and end of season - EOS) to AD, WSDI, and CHWE. Furthermore, this research investigated the threshold of grassland phenology response to compound hot and dry events. The research findings indicate a significant increasing trend in AD, WSDI, and CHWE in the arid regions of Central Asia from 1982 to 2022 (0.51 day/year, P < 0.01; 0.25 day/year, P < 0.01; 0.26 day/year, P < 0.01). SOS in the arid regions of Central Asia showed a significant advancement trend, while EOS exhibited a significant advance. LOS demonstrated an increasing trend (-0.23 day/year, P < 0.01; -0.12 day/year, P < 0.01; 0.56 day/year). The temperature primarily governs the variation in SOS. While higher temperatures promote an earlier SOS, they also offset the delaying effect of CHWE on SOS. AD, temperature, and CHWE have negative impacts on EOS, whereas WSDI has a positive effect on EOS. AD exhibits the strongest negative effect on EOS, with an increase in AD leading to an earlier EOS. Temperature and WSDI are positively correlated with LOS, indicating that higher temperatures and increased WSDI contribute to a longer LOS. The threshold values for the response of SOS, EOS, and LOS to CHWE are 16.14, 18.49, and 16.61 days, respectively. When CHWE exceeds these critical thresholds, there are significant changes in the response of SOS, EOS, and LOS to CHWE. These findings deepen our understanding of the mechanisms by which extreme climate events influence grassland phenology dynamics in Central Asia. They can contribute to better protection and management of grassland ecosystems and help in addressing the impacts of global warming and climate change in practice.

Neotropical seasonal dry forest (NSDF) is one of the most threatened ecosystems according to global climate change predictions. Nonetheless, few studies have evaluated the global climate change impacts on diversity patterns of NSDF plants. The lack of whole biome-scale approaches restricts our understanding of global climate change consequences in the high beta-diverse NSDF. We analysed the impact of global climate change on species distribution ranges, species richness, and assemblage composition (beta diversity) for 1,178 NSDF species. We used five representative plant families (in terms of abundance, dominance, and endemism) within the NSDF: Cactaceae, Capparaceae, Fabaceae, Malvaceae, and Zygophyllaceae. We reconstructed potential species distributions in the present and future (2040-2080), considering an intermediate Shared Socioeconomic Pathway and two dispersal ability assumptions on the taxa. Using a resource use scores index, we related climate-induced range contractions with species\' water stress tolerance. Even under a favourable dispersal scenario, species distribution and richness showed future significant declines across those sites where mean temperature and precipitation seasonality are expected to increase. Further, changes in species range distribution in the future correlated positively with potential use of resources in Fabaceae. Results suggest that biotic heterogenization will likely be the short-term outcome at biome scale under dispersal limitations. Nonetheless, by 2080, the prevailing effect under both dispersal assumptions will be homogenization, even within floristic nuclei. This information is critical for further defining new areas worth protecting and future planning of mitigation actions for both species and the whole biome.

One of the most crucial steps in the practical conservation of endangered endemic mountain plants is to address their population size status and habitat requirements concurrently with understanding their response to future global warming. Three endangered Silene species-Silene leucophylla Boiss., S. schimperiana Boiss., and S. oreosinaica Chowdhuri-in Egypt were the focus of the current study. These species were examined for population status change, habitat quality variables (topography, soil features, and threats), and predictive current and future distributions. To find population size changes, recent field surveys and historical records were compared. Using Random Forest (RF) and Canonical Correspondence Analysis (CCA), habitat preferences were assessed. To forecast present-day distribution and climate change response, an ensemble model was used. The results reported a continuous decline in the population size of the three species. Both RF and CCA addressed that elevation, soil texture (silt, sand, and clay fractions), soil moisture, habitat-type, chlorides, electric conductivity, and slope were among the important variables associated with habitat quality. The central northern sector of the Saint Catherine area is the hotspot location for the predictive current distribution of three species with suitable areas of 291.40, 293.10, and 58.29 km2 for S. leucophylla, S. schimperiana, and S. oreosinaica, respectively. Precipitation-related variables and elevation were the key predictors for the current distribution of three Silene species. In response to climate change scenarios, the three Silene species exhibited a gradual contraction in the predictive suitable areas with upward shifts by 2050 and 2070. The protection of these species and reintroduction to the predicted current and future climatically suitable areas are urgent priorities. Ex-situ conservation and raised surveillance, as well as fenced enclosures may catapult as promising and effective approaches to conserving such threatened species.