Search Results (7,011)

Seed dormancy is a key ecological attribute influencing germination timing and the ability of species to establish in variable environments. This study investigated whether inter-population variability in seed dormancy expression exists in Lonicera etrusca, a Mediterranean shrub known for producing seeds with underdeveloped embryos and multiple dormancy types. Seeds were collected from four geographically and ecologically distinct populations in central Iberia and subjected to a series of germination experiments simulating natural seasonal temperature regimes, stratification treatments, and gibberellic acid application. Across all populations, seeds exhibited morphological dormancy (MD) and varying degrees of morphophysiological dormancy (MPD), including non-deep simple and deep complex types. Despite high intra-specific variability in dormancy expression, no significant differences were found among populations for germination patterns or embryo growth responses. This indicates that dormancy variability is an intrinsic, conserved feature of the species rather than a locally adaptive trait. The homogenization of germination strategies across populations may be facilitated by bird-mediated seed dispersal, promoting gene flow and limiting local selection. These findings support the hypothesis that dormancy polymorphism in L. etrusca reflects a flexible germination strategy that enhances colonization potential across heterogeneous Mediterranean environments, rather than an environmentally induced plastic response. Full article

Ceramide kinase (CerK) catalyzes the phosphorylation of ceramide to ceramide-1-phosphate (C1P), a bioactive sphingolipid with diverse signaling roles. While CerK has been identified in several cellular compartments, its presence and functional significance in kidney proximal tubules remain unexplored. Herein, we report the first characterization of CerK activity in basolateral membranes (BLMs) from porcine proximal tubule cells. We demonstrate that BLM fractions contain neutral and acidic sphingomyelinases, providing local substrate for CerK, which efficiently generates C1P under physiological pH (6.5–7.2) and temperature (30–37 °C) conditions. Enzyme activity was stimulated by cAMP in a protein kinase A-dependent manner but was not affected by angiotensin II. Lipidomic analysis confirmed the presence of C1P in human proximal tubule (HK-2) cells under basal conditions and revealed changes during ischemic stress. Transcriptomic analysis of kidney biopsies from patients with chronic kidney disease (CKD) further uncovered coordinated remodeling of sphingolipid metabolism genes, with increased expression of ceramidases (ASAH1 and NAAA) and downregulation of ceramide synthases (CERS4, CERS5), consistent with adaptive regulation of the Cer/CerK/C1P axis. Together, these findings identify for the very first time CerK activity in renal BLM, establish its biochemical requirements, and highlight its potential role in modulating transporter function and sphingolipid signaling in physiology and kidney disease. Full article

This paper presents a proposed LSTM-based vertical-gradient prediction combined with three-dimensional kriging that enables reconstruction of greenhouse 3D temperature fields under sparse-sensor deployments while capturing temporal dynamics and spatial correlations. In northern China, winter solar greenhouses rely on standardized structures and passive climate-control strategies, which often lead to non-uniform thermal conditions that complicate precise regulation. To address this challenge, 24 sensors were deployed, and their time-series data were used to train a long short-term memory (LSTM) model for vertical temperature-gradient prediction. The predicted values at multiple heights were fused with in situ observations, and three-dimensional ordinary kriging (3D-OK) was applied to reconstruct the spatiotemporal temperature field. Compared with conventional 2D monitoring and computationally intensive CFD, the proposed approach balances accuracy, efficiency, and deployability. LSTM–Kriging validation showed Trend + Residual Kriging had the lowest RMSE (0.45558 °C) and bias (−0.03148 °C) (p < 0.01), outperforming Trend-only RMSE (3.59 °C) and Kriging-only RMSE (0.48 °C); the 3D model effectively distinguished sunny and rainy dynamics. This cost-effective framework balances accuracy, efficiency, and deployability, overcoming limitations of 2D monitoring and CFD. It provides critical support for adaptive greenhouse climate regulation and digital-twin development, directly advancing precision management and yield stability in CEA. Full article

In the context of intensifying climate change, it is particularly important to assess the transformation of spring floods as a key phase of the hydrological regime of rivers. This study provides a comprehensive analysis of the characteristics of maximum runoff in the Zhaiyk–Caspian basin for the modern period and projected changes for 2030, 2040, and 2050 based on CMIP6 climate scenarios (SSP3-7.0 and SSP5-8.5). Analysis of observations at 34 hydrological stations showed a reduction in spring runoff by up to 35%, a decrease in the duration of high water and a reduction in maximum water discharge on some rivers by up to 45%. It has been established that those rising temperatures, more frequent thaws, and reduced autumn moisture lead to lower maximum water discharge and a redistribution of the seasonal flow regime. Scenario projections revealed significant spatial heterogeneity: some rivers are expected to experience an increase in maximum discharge of up to 72%, while others will see a steady decline in maximum discharge of up to 35%. The results obtained indicate the need to transition to an adaptive water management system focused on the regional characteristics of river basins and the sensitivity of small- and medium-sized watercourses to climate change. Full article

The rural population in semi-arid areas of Mexico suffers from poverty levels that hinder a dignified life, leading to migration and abandonment of their resources. This is exacerbated by climate change (droughts and high temperatures), which negatively impacts crops. While farmers attempt to adapt, their strategies are insufficient. A low-cost Complementary Agriculture (AgriCom) model was designed, using local resources to produce prickly pear (Opuntia ficus-indica Mill.) and corn (Zea mays L.), while simultaneously conserving regional germplasm of Opuntia spp. A randomized block design with three replications was used. Each block included seven varieties, with 125 plants per variety. Corn was grown as a monocrop in the same experimental site. Graphical analysis, analysis of variance with mean comparison test in RStudio, a profitability analysis, and a Land Equivalent (ELU) analysis were performed. The varieties Verdura, Atlixco, and Rojo Liso showed higher yield, internal rate of return, and net present value; their benefit–cost ratios were 7.97, 6.35, and 6.82, respectively. The ELU was greater than 1.0 when combining the prickly pear varieties. Agroclimatic conditions did not allow the corn to complete its phenological cycle, and its ELU was zero. Seventy prickly pear genotypes, with three replicates each, representing eight Opuntia species, were collected and integrated into the periphery of the production unit. This model was accepted by the Climate Action Platform for Agriculture in Latin America and the Caribbean (PLACA) for implementation in other communities. Full article

Climate change poses significant challenges to viticulture worldwide, with Eastern European vineyards experiencing increased water stress due to rising temperatures, irregular precipitation patterns, and prolonged drought periods. These climatic shifts hurt vine phenology, grape quality, and overall productivity. In response, adaptive irrigation strategies such as Regulated Deficit Irrigation (RDI) have gained attention for optimizing water use while preserving grape quality. Concurrently, the adoption of smart agriculture technologies—including soil moisture sensors, automated weather stations, remote sensing, and data-driven decision support systems—enables precise monitoring and real-time management of vineyard water status. This review synthesizes recent studies from Eastern Europe, emphasizing the necessity of integrating climate adaptation measures with intelligent irrigation management to enhance vineyard resilience and sustainability under increasing climate variability. Full article

The study focuses on the experimental investigation of the impact of using coconut oil (CO) as a phase-change material (PCM) for heat storage on the root-zone temperature within a greenhouse in Adana, Türkiye. The study examines the efficacy of PCM as latent heat-storage material and predicts root-zone temperature using three machine learning algorithms. The dataset used in the analysis consists of 2658 data at hourly resolution with six variables from February to April in 2022. A greenhouse with PCM shows a remarkable increase in both ambient (0.9–4.1 °C) and root-zone temperatures (1.1–1.6 °C) especially during the periods without sunlight compared to a conventional greenhouse. Machine learning algorithms used in this study include Multivariate Adaptive Regression Splines (MARS), Support Vector Regression (SVR), and Extreme Gradient Boosting (XGBoost). Hyperparameter tuning was performed for all three models to control model complexity, flexibility, learning rate, and regularization level, thereby preventing overfitting and underfitting. Among these algorithms, R² values for testing data listed from largest to smallest are MARS (0.95), SVR (0.96), and XGBoost (0.97), respectively. The results emphasize the potential of machine learning approaches for applying thermal energy storage systems to agricultural greenhouses. In addition, it provides insight into a net-zero energy greenhouse approach by storing heat in a bio-based PCM, alongside its implementation and operational procedures. Full article

Climate change is fundamentally transforming global water systems, affecting the availability, quality, and ecological dynamics of water resources. This review synthesizes current scientific understanding of climate change impacts on hydrological systems, with a focus on freshwater ecosystems, and regional water availability. Rising global temperatures are disrupting thermal regimes in rivers, lakes, and ponds; intensifying the frequency and severity of extreme weather events; and altering precipitation and snowmelt patterns. These changes place mounting stress on aquatic ecosystems, threaten water security, and challenge conventional water management practices. The paper also identifies key vulnerabilities across diverse geographic regions and evaluates adaptation strategies such as integrated water resource management (IWRM), the water, energy and food (WEF) nexus, ecosystem-based approaches (EbA), the role of advanced technology and infrastructure enhancements. By adopting these strategies, stakeholders can strengthen the resilience of water systems and safeguard critical resources for both ecosystems and human well-being. Full article

The pomegranate cultivar Barski slatki, the most widely cultivated on the Eastern Adriatic coast, was evaluated over one growing season across four growing areas to assess its pomological and chemical properties and antioxidant activity. Results showed that location significantly influenced fruit weight, volume, number of arils per fruit, and both total and individual aril weight, with the Kaštela (CRO) site producing the largest fruits and highest aril yields. Climatic factors, such as precipitation during bud differentiation, flowering, and early fruit development, were found to impact fruit set, aril number, and fruit size. Aril and juice yields, however, remained relatively stable across sites. Notable differences were observed in total soluble solids, titratable acidity, pH, total phenolic content, and anthocyanin profiles. Location with higher rainfall occurring during fruit growth favored enhanced phenolic accumulation. Although total anthocyanin content remained consistent among locations, significant variation occurred in aril coloration and composition of individual anthocyanins. In conclusion, microclimatic factors, particularly rainfall distribution, temperature, and altitude, play a decisive role in shaping the physical, chemical, and visual attributes of ‘Barski slatki’. Despite being cultivated under similar Mediterranean conditions, the observed differences across sites highlight the strong adaptability of this cultivar to diverse agroecological environments, while maintaining stable quality. Full article

In recent years, global climate fluctuation has been obvious and has had a significant impact on the food industry system, which makes the impact of climate change on the resilience of the food industry supply chain of great concern. Based on this, this paper selects the panel data of 30 provinces in China from 2011 to 2022; it takes the relationship between climate change and the toughness of the food industry supply chain as the entry point, and probes deeply into the intrinsic mechanism of the impact of climate change on the toughness of the food industry supply chain. The study found the following: First, climate change has a significant negative impact on the food industry supply chain resilience, and in climate change, the impact of temperature on the food industry supply chain resilience is significantly higher than the impact of rainfall on the food industry supply chain resilience. Second, the mechanism of the effect of climate change on food industry supply chains exhibits substantial heterogeneity between major food-producing regions and non-major food-producing ones and varies across different levels of mechanization. Third, crop diversification within the study scope remarkably mitigates the negative effect of temperature fluctuations on the resilience of the food industry supply chain. Therefore, the food supply chain system must enhance its capacity to withstand climate change, and current and future resilience should be strengthened by advancing the implementation of adaptation policies, plans, and actions that drive transformation. Full article

Influenza viruses cause mild to severe lower respiratory infections, sometimes resulting in hospitalization and death. Vaccination remains the primary prophylactic strategy. Live attenuated influenza vaccines (LAIVs) efficiently induce antiviral immune responses and contain temperature-sensitive and cold-adapted mutations that render them safe. These mutations are principally located in the PB1 and PB2 subunits of the viral RNA polymerase, but the mechanism by which they attenuate the virus is unclear. We introduced the PB1 and PB2 mutations from two LAIV backbones, A/Ann Arbor/6/1960 H2N2 (AA) and A/Leningrad/134/17/1957 H2N2 (Len), into the model influenza strain A/Puerto Rico/8/1934 H1N1 (PR8). In contrast to the wild-type (WT) PR8 polymerase, the two “PR8-LAIV” polymerase complexes demonstrated maximal activity at cold temperatures (30–32 °C) and greatly reduced activity at elevated temperatures (>37 °C). To further understand the impact of the LAIV mutations, we infected MDCK cells with WT and mutated PR8 viruses that contain the Len and AA LAIV mutations in PB1 and PB2. The PR8-LAIV mutant viruses exhibited a selective, temperature-dependent defect in the replicase activity of the viral RNA polymerase relative to WT PR8, while also demonstrating a temperature-dependent enhancement in the transcriptional activity of the enzyme. In addition, the PR8-LAIV mutant viruses produced similar levels of viral proteins to WT PR8 at 37 °C, but greatly (2–3 log₁₀) reduced levels of infectious viral progeny. Collectively, these data show that LAIV mutations selectively alter influenza viral RNA polymerase function, favoring transcription over genome synthesis at 37 °C, thereby preserving viral antigen production while also contributing to viral attenuation. Full article

This study assessed the impact of 39 active and passive energy efficiency measures on the energy demand of a prototype dwelling, modeled through parametric simulations in DesignBuilder across nine climatic zones in Chile, classified according to the Köppen system. Each measure was evaluated individually (single-measure scenarios); three variation levels were evaluated to quantify their relative influence on energy demand. Results indicate that passive strategies are more effective in cold and humid climates, where increasing wall insulation thickness reduced energy demand by up to 45%, and improving airtightness achieved a 43% reduction. In contrast, in tundra climates or areas with high thermal variability, some measures, such as green façades or overhangs, increased energy demand by up to 49% due to the loss of useful solar gains. In desert climates, characterized by high diurnal temperature variation, thermal mass played a more significant role: high-inertia walls without additional insulation outperformed lightweight EPS-based solutions. The findings suggest that measure selection must be climate-adapted, prioritizing high-impact passive strategies and avoiding one-size-fits-all solutions. This work provides quantitative evidence to inform residential thermal design and support climate-sensitive energy efficiency policies. This study delivers a single-measure comparative atlas; future research should integrate multi-measure optimization together with comfort/cost metrics. Full article

Biophilic design has traditionally evolved from temperate-zone contexts, where access to nature is more readily available, and has rarely addressed the challenges of extreme climatic conditions. The potential of biophilic design to enhance health and well-being in cold environments, where exposure to nature must adapt to low temperatures, limited solar radiation, and pronounced photoperiod variation, remains underexplored. This study conducts a systematic meta-synthesis of biophilic architectural design strategies in Arctic and Sub-Arctic regions, adopting the SALSA (Search, Appraisal, Synthesis, and Analysis) framework in alignment with PRISMA guidelines to ensure methodological transparency and reproducibility. Nine peer-reviewed studies published between 2019 and 2024 were analyzed using qualitative coding and synthesis in NVivo. The findings identify thermal comfort, daylight, and circadian regulation as the most influential biophilic parameters, while greenery and water features, common in temperate frameworks, were limited due to environmental constraints. Key interventions include adaptive envelopes, optimized window design, intermediate buffer zones, and materials that balance insulation with sensory enrichment. The study proposes an “Interventions–Parameters–Outcomes” framework that illustrates the interrelationships among biophilic strategies, health-related outcomes, and climatic adaptation. While all studies originated from northern Canada, the conceptual framework provides a transferable foundation for future empirical validation and comparative research across diverse cold-climate regions, contributing to the advancement of climate-responsive, human-centered design in extreme environments. Full article

Training on deep sand is commonly employed in endurance horses, but its physiological adaptation remains poorly characterized. This study aimed to characterize locomotor adaptations during a 7 km controlled-speed canter on deep sand in eighteen endurance horses, to identify heart rate variability (HRV) components, and to investigate changes in hematological variables before and after exercise. Stride frequency (SF) and stride length (SL), HRV, and hematological profiles were recorded during exercise and recovery with a fitness tracker. Associations between maximum speed and locomotor parameters were assessed by linear regression, while Pearson’s correlation assessed HRV relationships, also with physiological parameters. Hematological parameters were assessed with paired t-test before and after training. SL percentage change was the strongest predictor of speed (β = 0.677). HRV analysis revealed delayed parasympathetic reactivation; the parasympathetic recovery index (PNS REC) was correlated with mean RR interval on the ECG (r = 0.968) and heart rate (r = −0.964) during recovery. Post-exercise rectal temperature showed correlations with HRV recovery indices. Hematological evaluation revealed post-exercise increases in red blood cell count, hematocrit, hemoglobin, and corpuscular indices. SL plays a predominant role in achieving higher speeds on deep sand, while PNS REC emerges as a practical and accessible marker of autonomic recovery and fatigue. Horses with enhanced thermoregulation recover better. Hematological results confirm a physiological stress response that may optimize oxygen delivery. Integrating locomotor, cardiovascular, and hematological monitoring may improve management and welfare in endurance training. Full article

Drought is one of the main climate-induced risks threatening agricultural sustainability in semi-arid regions. Northern Kazakhstan, a key grain-producing region in Central Asia, exhibits increasing vulnerability to droughts due to climatic variability and reliance on rainfed agriculture. This study evaluates the informativeness of drought indices based on the response of agricultural vegetation to dry conditions using remote sensing-based vegetation indices across Northern Kazakhstan from 1990 to 2024. Ground-based meteorological indices—the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), the Hydrothermal Coefficient (HTC), and the Modified China-Z Index (MCZI)—and vegetation indices—the Vegetation Condition Index (VCI), the Temperature Condition Index (TCI), and the Vegetation Health Index (VHI)—were analyzed using data from 11 representative meteorological stations. For the first time in Kazakhstan, the MCZI was calculated, demonstrating high sensitivity to local climate variability and strong agreement with the VHI. The SPI, MCZI, and HTC showed strong seasonal correlations with vegetation indices, whereas the SPEI had a weak correlation, limiting its applicability. The highest correlations (r ≥ 0.82) between meteorological and vegetation indices were recorded in summer, while spring and autumn were influenced by phenological and temperature factors. Persistent drying trends in the southern and southwestern areas contrasted with moderate wetting in the north. The combined use of the SPI, MCZI, HTC, and VHI proved effective for monitoring droughts. The results provide a reproducible foundation for local drought assessment and early warning systems, supporting climate-resilient agricultural planning and sustainable land and water resource management. The results also offer actionable insights to enhance adaptation strategies and support long-term agricultural and environmental sustainability in Central Asia and similar continental agroecosystems. Full article