Climatic Events Research Articles

The Quantile Effects of Climate and Global Economic Policy Uncertainties on Renewable Energy Demands in the BRICS Nations: The Role of Green Ecological Policies

Renewable energy has an important role in attaining environmental quality. Numerous studies have determined the factors driving the diminishment or promotion of renewable energy consumption (REC) globally. Despite the findings of prior studies, the specific effects of climate policy uncertainty (CPU) and global economic policy uncertainty (GEPU) on REC have not been probed in the case of BRICS economies. Furthermore, fewer considerations have been taken into account to explore whether green environmental policies (EPs) have a moderating role. Therefore, the present work contributes to filling the gap by providing an empirical model and assessing the panel quantile data and fixed-effect methods used between 2010 and 2020. The findings reveal that the expansion of the financial market, inflowing FDI, rising international remittances, developing environmental innovation, and increasing CPU are significant factors promoting REC while unfavorably increasing CO2, economic activity, and GEPU impact. Notably, the results underscore that EPs have a significant positive effect, and stricter ecological strategies lead to a rise in REC. In addition, the findings highlight that by implementing stricter EPs, the effect of CPU on REC becomes more positive, and the negative effect of GEPU on REC is more controlled. In particular, the significant interaction effects highlight that the beneficial role of EPs is more pronounced in nations with strong EPs relative to low EPs. Overall, EPs have a substantial beneficial role in promoting REC when CPU and GEPU arise. These findings are reliable after using numerous measurements and methods, and several policy recommendations are suggested to governments, policymakers, and regulatory bodies.

Scoping review of the societal impacts of compound climate events

Abstract Climatic extremes have historically been seen as univariate; however, recent international reports have highlighted the potential for an increase in compound climate events (e.g., hot and dry events, recurrent flooding). Despite the projected increase in the frequency of compound climate events and the adoption of compound event terminology, few studies identify climate extremes as compound climate events and little evidence exists on the societal impacts of these compound climate events. This scoping review summarizes key findings and knowledge gaps in the current state of empirical studies that focus on the societal impacts of compound climate events. We identified 28 eligible studies published in four databases reporting on the societal impacts of compound climate events in four sectors: agriculture, public health, the built environment, and land use. Overall, we found the need for more research explicitly linking compound climate events to societal impacts, particularly across multiple compound climate events, rather than single case study events. We also noted several key findings, including changes in agricultural productivity, loss of habitat, increased fire risk, poor mental health outcomes, decreased health care access, and destruction of homes and infrastructure from these events. Additional research is needed both globally and locally to understand the implications of compound climate events across different geographic regions and populations to ensure responsive adaptation policies in a compound climate event framework.

Climatological Study on Cyclone Genesis and Tracks in Southern Brazil from 1979 to 2019

This study investigates cyclone dynamics and impacts in the Southwestern Atlantic, with a focus on their effects on southern Brazil. As climate change intensifies coastal vulnerability, understanding cyclone behavior has become essential. Using the TRACK and cycloTRACK algorithms, we examined cyclone trajectories and cyclogenesis densities from 1979 to 2019 to analyze seasonal and spatial patterns shaped by large-scale atmospheric circulations, including the Antarctic Oscillation (AAO). The analysis explores trends in cyclone activity across various temporal and spatial scales, identifying key regions of cyclogenesis and trajectory density. Results indicate that the cycloTRACK algorithm is more effective at tracking more intense and consistent cyclones, excluding weaker systems. Seasonal patterns suggest variability in cyclone formation, likely associated with atmospheric instability and ocean–atmosphere interactions. While trends reveal an increase in cyclone passages in southern Brazil, these systems are strongly associated with extreme climatic events in the region, including coastal storms, intense precipitation, strong winds, and high waves. By clarifying cyclone dynamics and seasonal patterns, this study enhances our understanding of cyclone behavior and contributes to improved assessments of regional climate resilience in southern Brazil.

Snowfall Change Had Different Effects on Litter Decomposition for Two Typical Desert Species in Different Periods

In desert ecosystems, litter decomposition is the primary source of soil nutrients and is strongly affected by extreme climate events, which may influence desert plant survival and species diversity. To date, the effects of snowfall changes on litter decomposition in desert species remain poorly understood. Here, a snowfall manipulation experiment was conducted in Northwest China that included snowfall addition and removal treatments, as well as a natural snowfall control. Compared to the control, snowfall addition increased the amount of litter mass lost for Salsola passerina and Reaumuria soongarica during the snow-covered period by 21.54% and 21.8%, respectively. In contrast, snowfall addition effects differed between species during the snow-free period. More carbon was released from the S. passerina litter in the snowfall addition treatment during the snow-free period. Similarly, during the snow-covered period, more carbon and nitrogen were released from the R. soongorica litter in the snowfall addition treatment. Overall, the proportion of litter mass lost (from the annual total) increased with snowfall addition in the snow-covered period but was reduced with snowfall addition in the snow-free period. In the snow-covered period, the snowfall addition treatment affected litter mass loss to the same extent in both species but impacted S. passerina more strongly than R. soongorica in the snow-free period due to differences in soil urease activity. Changes in snowfall, therefore, significantly influenced litter decomposition in both desert species, but these effects differed between the snow-covered and snow-free period, particularly for litter with a higher C:N ratio.

Novel Machine-Learning Modeling of Facial Trauma Volume With Regional Event and Weather Data.

Facial trauma volume is difficult to predict accurately. We aim to understand the capacity of climate and regional events to predict daily facial trauma volume. This can provide epidemiologic understanding and subsequently tailor workforce distribution and scheduling. Retrospective cohort study. Single Tertiary Academic Medical Center. Facial trauma consults between 2017 and 2023 were extracted from a single Level I Trauma Center. Publicly accessible data on local concerts, National Hockey League games, National Football League games, and weather data from the National Oceanic and Atmospheric Administration data were merged with trauma data. Machine-learning random-forest (RF) plot feature identification was used to identify variables to model high-volume facial trauma days (greater than 75th percentile). For analysis, 2342 days were included. The median number of facial trauma consults was 3.0 (interquartile range: 2.0-5.0). The month of May exhibited the highest rate of high-volume trauma days (13% of days, P < .001). On RF feature identification, the strongest predictive factors included weekend day status, average temperature, precipitation, hail, high/damaging winds, and holidays. Regional events were not included in the final models. On stepwise logistic regression modeling with pertinent variables, weekend day (odds ratio [OR]: 2.20, 95% confidence interval [CI]: 1.80-2.69, P < .001), average temperature (OR: 1.02, 95% CI: 1.01-1.02, P < .001), and wind speed (0.97, 0.93-1.00, P = .049) were the only statistically significant variables. Climate data were the primary factor that had predictive capacity for high-volume facial trauma days, more so than regional events. Testing models prospectively will help validate such models and help inform staffing for facial trauma coverage.

Modeling the impact of extreme weather events and future climate on the radiologically contaminated sites of Enewetak Atoll

Enewetak Atoll underwent 43 historical nuclear tests from 1948 to 1958, including the first hydrogen bomb test, resulting in a substantial nuclear material fallout contaminating the Atoll and the lagoon waters. The radionuclide fallout material deposited in lagoon sediments and soil on the islands will remain for decades to come. With intensifying climate and extreme weather events, the possibility of redistribution of deposited radionuclide material has become a great concern. This study uses a numerical modeling approach to estimate the potential elevated radionuclide concentrations that can be distributed during storm events under current and future climates. We simulated three historical storm scenarios that are most likely to impact Atoll’s environment and remobilize the radionuclide-bound sediments. WRF-ARW was used to reconstruct these storm scenarios under current year (2015) and future year (2090) climates. Storm-induced ocean hydrodynamics conditions were generated using FVCOM. FVCOM-ICM was externally coupled to simulate the fate and transport of radionuclides. Given that the 239Pu is the largest fraction of the radionuclide inventory of the lagoon and Atoll islands, the model results show the highest average incremental 239Pu concentration that an island may be exposed to is 3.25E-4 Bq/m3 (becquerel per cubic meters), which is an increase of 84 times the average baseline/existing 239Pu concentration without the storm conditions. The overall increase in 239Pu average over all the islands of Atoll is about 20 folds relative to the baseline concentration. Despite the high relative increase ratios, a comprehensive exposure assessment is required to investigate the exposure risk. Further, due to the limitations of the study and uncertainties/biases in the historical data used, further research supported by field surveys to better characterize the current contamination level may be needed to make more accurate predictions.

Climate model downscaling in central Asia: a dynamical and a neural network approach

Abstract. High-resolution climate projections are essential for estimating future climate change impacts. Statistical and dynamical downscaling methods, or a hybrid of both, are commonly employed to generate input datasets for impact modelling. In this study, we employ COSMO-CLM (CCLM) version 6.0, a regional climate model, to explore the benefits of dynamically downscaling a general circulation model (GCM) from the Coupled Model Intercomparison Project Phase 6 (CMIP6), focusing on climate change projections for central Asia (CA). The CCLM, at 0.22° horizontal resolution, is driven by the MPI-ESM1-2-HR GCM (at 1° spatial resolution) for the historical period of 1985–2014 and the projection period of 2019–2100 under three Shared Socioeconomic Pathways (SSPs), namely the SSP1-2.6, SSP3-7.0, and SSP5-8.5 scenarios. Using the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) gridded observation dataset as a reference, we evaluate the performance of CCLM driven by ERA-Interim reanalysis over the historical period. The added value of CCLM, compared to its driving GCM, is evident over mountainous areas in CA, which are at a higher risk of extreme precipitation events. The mean absolute error and bias of climatological precipitation (mm d−1) are reduced by 5 mm d−1 for summer and 3 mm d−1 for annual values. For winter, there was no error reduction achieved. However, the frequency of extreme precipitation values improved in the CCLM simulations. Additionally, we employ CCLM to refine future climate projections. We present high-resolution maps of heavy precipitation changes based on CCLM and compare them with the CMIP6 GCM ensemble. Our analysis indicates an increase in the intensity and frequency of heavy precipitation events over CA areas already at risk of extreme climatic events by the end of the century. The number of days with precipitation exceeding 20 mm increases by more than 90 by the end of the century, compared to the historical reference period, under the SSP3-7.0 and SSP5-8.5 scenarios. The annual 99th percentile of total precipitation increases by more than 9 mm d−1 over mountainous areas of central Asia by the end of the century, relative to the 1985–2014 reference period, under the SSP3-7.0 and SSP5-8.5 scenarios. Finally, we train a convolutional neural network (CNN) to map a GCM simulation to its dynamically downscaled CCLM counterpart. The CNN successfully emulates the GCM–CCLM model chain over large areas of CA but shows reduced skill when applied to a different GCM–CCLM model chain. The scientific community interested in downscaling CMIP6 models could use our downscaling data, and the CNN architecture offers an alternative to traditional dynamical and statistical methods.

A Review: Mechanisms of Ocean Acidification in the Context of Global Warming

Global warming stems mainly from the accumulation of greenhouse gases, which leads to higher atmospheric and ocean temperatures and has far-reaching impacts on marine systems. This paper focuses on the impact of global warming on the El Nio phenomenon and ocean acidification. There are significant changes in the frequency and intensity of El Nio events in the context of global warming, but the exact trends are uncertain. At the same time, the increase in carbon dioxide has led to ocean acidification, which poses a threat to the growth of marine organisms and the stability of ecosystems. An in-depth understanding of the role of El Nio and ocean acidification in climate change is therefore essential for the protection of marine ecosystems. For future marine ecological conservation, a comprehensive analysis of the climatic effects of El Nio and ocean acidification is essential. Only an in-depth study of these factors can lead to a more effective response to the ecological challenges posed by global warming.

Harnessing the diversity of a lettuce wild relative to identify anthocyanin-related genes transcriptionally responsive to drought stress

Lettuce is a crop particularly vulnerable to drought. A transcriptomic study in the variety ‘Romired’ and the wild relative Lactuca homblei was conducted to understand the increase in anthocyanins (only significant in L. homblei) in response to drought previously observed. RNA-seq revealed more differentially expressed genes (DEGs), especially upregulated, in the wild species, in which the most abundant and significant GO terms were involved in regulatory processes (including response to water). Anthocyanin synthesis was triggered in L. homblei in response to drought, with 17 genes activated out of the 36 mapped in the phenylpropanoid-flavonoid pathway compared to 7 in ‘Romired’. Nineteen candidate DEGs with the strongest change in expression and correlation with both anthocyanin content and drought were selected and validated by qPCR, all being differentially expressed only in the wild species with the two techniques. Their functions were related to anthocyanins and/or stress response and they harboured 404 and 11 polymorphisms in the wild and cultivated species, respectively. Some wild variants had high or moderate predicted impacts on the respective protein function: a transcription factor that responds to abiotic stresses, a heat shock protein involved in stomatal closure, and a phospholipase participating in anthocyanin accumulation under abiotic stress. These genetic variants could explain the differences in the gene expression patterns between the wild (significantly up/downregulated) and the cultivated (no significant changes) species. The diversity of this crop wild relative for anthocyanin-related genes involved in the response to drought could be exploited to improve lettuce resilience against some adverse climate effects.

Unveiling the dark side of virtual work climate: the mediating role of blurred work-nonwork boundaries

PurposeThis research investigates the dark sides of virtual work climate by examining how blurred work-nonwork boundaries serve as a turning point leading to amotivation at work.Design/methodology/approachThis quantitative study involved 487 employees from small and medium-sized enterprises in China who completed a self-administered questionnaire. Data were analyzed using the partial least squares structural equation modeling (PLS-SEM) method.FindingsThe study found that virtual work climate positively influences workplace flexibility. However, blurred work-nonwork boundaries mediate the relationship between workplace flexibility and psychological demands, transforming the positive effects of virtual work climate in terms of flexibility into negative outcomes. Psychological demands from both work and nonwork domains contribute to amotivation at work.Practical implicationsThe study provides practical insights for managers on satisfying employees’ needs for flexible working arrangements within a virtual work climate by advocating for clear policies that establish distinct work-nonwork boundaries, thereby ensuring employee motivation is not compromised.Originality/valueThis research unveils the dark sides of the virtual work climate, extending the self-determination through the lens of the “too-much-of-a-good-thing” theory. The findings suggest that blurred work-nonwork boundaries may be the turning point where the virtual work climate leads to amotivation at work.

How Do Changes in Grassland Phenology and Its Responses to Extreme Climatic Events in Central Asia?

Extreme climate events have become more frequent under global warming, significantly affecting vegetation phenology and carbon cycles in Central Asia. However, the mediating effects of intensity of compound drought and heat events (CDHEs) and compound moisture and heat events (CMHEs) on grassland phenology and their trends in the relative contributions to grassland phenology over time have remained unclear. Based on the calculation results of grassland phenology and compound events (CEs), this study used trend analysis, partial least squares regression structural equation modeling (PLS-SEM), and ridge regression analysis to investigate the mediating effect and the temporal trend in relative contribution of CEs to grassland phenology in Central Asia, and the magnitude of sensitivity of grassland phenology to CEs. This study revealed that the start of season (SOS) was advanced by 0.4 d·a−1, end of season (EOS) was delayed by 0.5 d·a−1, and length of season (LOS) extended by 0.8 d·a−1 in 1982–2022. The duration of the CDHEs (0−37 days) was greater than that of the CMHEs (0−9 days) in Central Asia. The direct effects of CDHEs and CMHEs on grassland phenology were generally negative, except for the direct positive effect of CDHEs on LOS. The indirect effects of temperature and precipitation on grassland phenology through CDHEs and CMHEs were greater than their direct effects on phenology. The relative contribution of CDHEs to grassland phenology was consistently greater than that of CMHEs, and both the relative contribution curves showed a significant upward trend. The sensitivity of grassland phenology to CDHEs was higher than its sensitivity to CMHEs at 0.79 (SOS), 1.18 (EOS), and 0.72 (LOS). Our results emphasize the mediating effects of CDHEs and CMHEs on grassland phenology. Under the influence of CDHEs and CMHEs, the LOS will further lengthen in the future.

Land conversions not climate effects are the dominant indirect consequenceof sun-driven CO2 capture, conversion, and sequestration

Abstract Removing carbon dioxide (CO2) from the atmosphere is required for mitigating climate change. Large-scale direct air capture combined with injecting CO2 into geological formations could retain carbon long-term, but demands a substantial amount of energy, pipeline infrastructure, and suitable sites for gaseous storage. Here, we study Earth system impacts of modular, sun-powered process chains, which combine direct air capture with (electro)chemical conversion of the captured CO2 into liquid or solid sink products and subsequent product storage (sDACCCS). Drawing on a novel explicit representation of CO2 removal in a state-of-the-art Earth system model, we find that these process chains can be renewably powered and have minimal implications for the climate and carbon cycle. However, to stabilize the planetary temperature two degrees above pre-industrial levels, CO2 capturing, conversion, and associated energy harvest demand up to 0.46% of the global land area in a high-efficiency scenario. This global land footprint increases to 2.82% when assuming present-day technology and pushing to the bounds of removal. Mitigating historical emission burdens within individual countries in this high-removal scenario requires converting an area equivalent to 40% of the European Union's agricultural land. Scenarios assuming successful technological development could halve this environmental burden, but it is uncertain to what degree they could materialize. Therefore, ambitious decarbonization is vital to reduce the risk of land use conflicts if efficiencies remain lower than expected.

Relationship between motivational climate, anxiety and average mark in pre-service physical education teachers: a cross-sectional study based on structural equation modelling approach

BackgroundMotivation is a variable that directly influences task orientation. Within the motivational sphere, the motivational climate determines whether a task is performed with an intrinsic or extrinsic.PurposeIt has been observed that depending on motivational orientations, anxiety levels and task performance can be increased. Likewise, there are differences in interests depending on the gender of individuals.MethodsThis research aims (a) To elaborate and adjust a theoretical model of the causal relationship of motivational climate on anxiety and academic performance and (b) To analyse the causal relationship between the motivational climate on anxiety and the average mark of the participants. Regarding the design, a comparative, cross-sectional and descriptive study was carried out on a sample of 558 trainee physical education teachers. The sample for this study is from southern Spain. Likewise, the branch of study of the sample is related to university degrees in education sciences and physical activity and sport sciences. The Beck Anxiety Inventory (BAI), Perceived Motivational Climate in Sport-2 and an ad hoc socio-demographic questionnaire were used to collect the data.ResultsIt is observed that the male sex presents a greater causal relationship of task climate (β=−0.259; p ≤ 0.05) and ego climate (β = 0.324; p ≤ 0.001) on anxiety. A stronger causal relationship of task climate (β = 0.340; p ≤ 0.001) and ego climate (β = 0.241; p ≤ 0.05) on mean score is also observed for the male population. The sample presents a negative causal relationship of anxiety on the average mark. This is higher for the male population (β=−0.126).ConclusionsMale students show a greater causal effect of motivational climate on anxiety and grade point average. Likewise, the causal relationship of task climate on the development of anxiety is negative for the study sample. In contrast, the ego climate exerts a positive causal relationship on the development of anxiety.

Co-occurring climate events and environmental justice in California, 2018-2019

Abstract Climate change will increase the frequency of extreme weather events. This means climate-driven events like wildfires and power outages will likely co-occur more often, potentially magnifying their health risks. We characterized three types of climate-driven events—anomalously warm temperatures, wildfire burn zone disasters, and long power outages—in 58 California counties during 2018–2019. We defined county-day anomalously warm temperatures when daily average temperatures exceeded 24°C and the 85th percentile of the long-term county average. We defined county-day wildfire burn zone disasters when an active wildfire burn zone intersected a county, burned 1+ structures, killed a civilian, or received a FEMA Fire Management Declaration, and overlapped with a community. For a subset of the 38 counties (66%), long power outage county days were identified using PowerOutage.us data when an outage affected &gt; 0.5% of county customers for 8+ hours. Co-occurring events were when 2+ of these events occurred on the same county day. Using the CDC/ATSDR Social Vulnerability Index (SVI), we determined whether co-occurring events disproportionately affected vulnerable populations. Nearly every county (97%) experienced at least one day of anomalously warm temperatures, 57% had at least one wildfire burn zone disaster day, and 63% (24/38 counties with available data) had at least one long power outage day. The most common co-occurring events (anomalously warm temperatures and wildfire burn zone disasters) impacted 24 (41%) counties for 144 total county-days. We did not find a clear connection between co-occurring events and social vulnerability. We observed an inverse correlation between co-occurring wildfire burn zone disasters and long power outage days with SVI, and a positive correlation between co-occurring anomalously warm and long power outage days with SVI. This analysis can inform regional resource allocation and other state-wide planning and policy objectives to reduce the adverse effects of climate-driven events.

From division to 'divergence': to understand wood growth across timescales, we need to (learn to) manipulate it.

Wood formation is the Rosetta stone of tree physiology: a traceable, integrated record of physiological and morphological status. It also produces a large and persistent annual sink for terrestrial carbon, motivating predictive understanding. Xylogenesis studies have greatly expanded our knowledge of the intra-annual controls on wood formation, while dendroecology has quantified the environmental drivers of multi-annual variability. But these fields operate on different timescales, making it challenging to predict how short (e.g. turgor) and long timescale processes (e.g. disturbance) interactively influence wood formation. Toward this challenge, wood growth responses to natural climate events provide useful but incomplete explanations of tree growth variability. By contrast, direct manipulations of the tree vascular system have yielded unexpected insights, particularly outside of model species like boreal conifers, but they remain underutilized. To improve prediction of global wood formation, we argue for a new generation of experimental manipulations of wood growth across seasons, species, and ecosystems. Such manipulations should expand inference to diverse forests and capture inter- and intra-specific differences in wood growth. We summarize the endogenous and exogenous factors influencing wood formation to guide future experimental design and hypotheses. We highlight key opportunities for manipulative studies integrating measurements from xylogenesis, dendroanatomy, dendroecology, and ecophysiology.

A common future for coastal peoples and seabirds facing extreme climatic events

A common future for coastal peoples and seabirds facing extreme climatic events

Cropland expansion links climate extremes and diets in Nigeria.

Climate change threatens smallholder agriculture and food security in the Global South. While cropland expansion is often used to counter adverse climate effects despite ecological trade-offs, the benefits for diets and nutrition remain unclear. This study quantitatively examines relationships between climate anomalies, forest loss from cropland expansion, and dietary outcomes in Nigeria, Africa's most populous country. Combining high-resolution data on forest cover and climate variables within random forest and panel regression models, we find that 25 to 31% of annual forest loss is linked to climate variability. Using georeferenced household survey data, we then find that changes in forest cover have a significant positive association with changes in child diet diversity-a key proxy of nutritional adequacy-while cropland expansion does not, suggesting that such forest conversions may be an ineffective climate adaptation strategy for improving nutrition. Our findings highlight the potential of nutrition-sensitive climate adaptation to enhance yields, promote nutritious cropping choices, and protect remaining forests.

What does infrared thermography tell us about the evolutionary potential of heat tolerance in endotherms?

Abstract Anthropogenic climate change affects wild animal populations through increasing average temperatures and more frequent extreme climatic events. Endotherms have evolved the capacity to regulate their body temperature but little is still known about how they can physiologically adapt to the pace of global warming. Adaptive responses would require that heat-tolerance mechanisms, such as the capacity to withstand high body temperatures and regulate evaporative water loss, exhibit sufficient heritable genetic variation for selection to act upon. Unfortunately, the quantitative genetics of these traits in endotherms remains poorly understood. In a recent study using infrared thermography (IRT) on semi-captive ostriches, Svensson et al., (Heritable variation in thermal profiles is associated with reproductive success in the world’s largest bird. Evolution Letters, 8(2), 200–211.) sought to address this knowledge gap by measuring relative heat exchange from the head and neck and assessing the link between among-individual variation in heat dissipation and reproductive fitness. We discuss how IRT serves as a valuable tool for non-invasive data collecting, highlighting its potential for field studies of the evolutionary potential of thermal tolerance. Nevertheless, interpreting IRT data is not as straightforward as it may seem and thus must be conducted carefully. For instance, body parts from which surface temperatures are measured need to be unequivocally identified as sources of dry heat exchange in order to inform on thermoregulation—something lacking in the mentioned study. Furthermore, there is still no conclusive evidence that surface temperatures reflect core body temperatures in endotherms. Critical underlying mechanisms of the heat response, such as evaporative cooling, must also be considered. Assumptions stemming from uncertain proxies of thermoregulation can obscure our understanding of the endothermic adaptation of heat-tolerance traits to rapid global warming. These considerations emphasize that, while IRT can be a valuable tool for developing quantitative genetic approaches to estimate the evolutionary potential of heat tolerance in endotherms—particularly for species most vulnerable to warming, its application warrants careful planning.

Response of Pedunculate Oak (Quercus robur L.) to Adverse Environmental Conditions in Genetic and Dendrochronological Studies.

Pedunculate oak (Quercus robur L.) is widely distributed across Europe and serves critical ecological, economic, and recreational functions. Investigating its responses to stressors such as drought, extreme temperatures, pests, and pathogens provides valuable insights into its capacity to adapt to climate change. Genetic and dendrochronological studies offer complementary perspectives on this adaptability. Tree-ring analysis (dendrochronology) reveals how Q. robur has historically responded to environmental stressors, linking growth patterns to specific conditions such as drought or temperature extremes. By examining tree-ring width, density, and dynamics, researchers can identify periods of growth suppression or enhancement and predict forest responses to future climatic events. Genetic studies further complement this by uncovering adaptive genetic diversity and inheritance patterns. Identifying genetic markers associated with stress tolerance enables forest managers to prioritize the conservation of populations with higher adaptive potential. These insights can guide reforestation efforts and support the development of climate-resilient oak populations. By integrating genetic and dendrochronological data, researchers gain a holistic understanding of Q. robur's mechanisms of resilience. This knowledge is vital for adaptive forest management and sustainable planning in the face of environmental challenges, ultimately helping to ensure the long-term viability of oak populations and their ecosystems. The topics covered in this review are very broad. We tried to include the most relevant, important, and significant studies, but focused mainly on the relatively recent Eastern European studies because they include the most of the species' area. However, although more than 270 published works have been cited in this review, we have, of course, missed some published studies. We apologize in advance to authors of those relevant works that have not been cited.

Effect of tropical climates on the quality of commonly used antibiotics: the protocol for a systematic review and meta-analysis

IntroductionMedicine quality can be influenced by environmental factors. In low- and middle-income countries (LMICs) with tropical climates, storage facilities of medicines in healthcare settings and homes may be suboptimal. However,...