Impact Of Climate Change Research Articles

Climate change and human health: Last call to arms for us

Climate change, now the foremost global health hazard, poses multifaceted challenges to human health. This editorial elucidates the extensive impact of climate change on health, emphasising the increasing burden of diseases and the exacerbation of health disparities. It highlights the critical role of the healthcare sector, particularly anaesthesia, in both contributing to and mitigating climate change. It is a call to action for the medical community to recognise and respond to the health challenges posed by climate change.

The Impact of Climate Change on the Development of Circular Economy in China: A Perspective on Green Total Factor Productivity

<p>In the process of China's transition to high-quality development, the circular economy, as a key strategy for achieving green growth, is of significant importance in addressing climate change and promoting sustainable development. This study employs the SBM-GML model to analyze the Green Total Factor Productivity (GTFP) of 30 provinces in China from 2005 to 2019, exploring the influence of climate change on the development of the circular economy. The research finds that although China's GTFP shows an overall upward trend, indicating some achievements in the circular economy, the performance in the eastern region significantly outperforms other regions, with technological progress being the primary driver of growth. The impact of climate change on GTFP varies with temperature changes and exhibits differentiated characteristics in different regions. Based on these findings, this paper puts forward a series of policy recommendations aimed at strengthening the practice of the circular economy, enhancing resource utilization efficiency, reducing greenhouse gas emissions, and addressing the challenges of climate change through promoting green low-carbon development, optimizing industrial structure, and formulating adaptive environmental regulations.</p>

Impact of Climate Change on Extreme Rainfall Events and Pluvial Flooding Risk in the Vojvodina Region (North Serbia)

Extreme precipitation events, which are common natural hazards, are expected to increase in frequency due to global warming, leading to various types of floods, including pluvial floods. In this study, we investigated the probabilities of maximum 3-day precipitation amount (Rx3day) occurrences during spring in the Vojvodina region, covering both past (1971–2019) and future (2020–2100) periods. We utilized an ensemble of eight downscaled, bias-corrected regional climate models from the EURO-CORDEX project database, selecting the RCP8.5 scenario to examine future Rx3day amounts. The probabilities of occurrences of Rx3day were modeled using the GEV distribution, while the number of events where Rx3day in spring exceeds specific thresholds was modeled using the Poisson distribution. The results indicate that Rx3day with a ten-year return period during the spring months is expected to increase by 19% to 33%. Additionally, the probabilities of having more than one event where Rx3day exceeds thresholds are projected to rise by 105.6% to 200.0% in the future compared to the historical period. The analysis comparing the design values of Rx3day with future projections for the period 2020–2100 revealed that 51 drainage systems are likely to function without difficulties under future climate conditions. However, for the remaining 235 drainage systems, an increased risk of pluvial flooding was identified, as their design precipitation amounts are lower than the future projections. This study reveals that analyzing extreme rainfall events in the context of climate change yields crucial information that facilitates effective planning and policy making in water management, particularly flood protection.

Investigating the Adoption of Blockchain Technology in Agri-Food Supply Chains: Analysis of an Extended UTAUT Model

Against a backdrop of globalization, dynamic shifts in consumer demand, and climate change impact, the intricacies of agri-food supply chains have become increasingly convoluted, necessitating innovative measures to guarantee agri-food security and authenticity. Blockchain technology emerges as a promising solution, offering transparency, immutability, traceability, and efficiency in the overall supply chain. This study aims to investigate determinants impacting both the intention to use and the actual usage of blockchain-driven agri-food supply chain platforms. To achieve this, an expanded and adapted conceptual model rooted in the Unified Theory of Acceptance and Use of Technology (UTAUT) was formulated and empirically examined through Partial Least Squares Structural Equation Modeling using data from 175 respondents from agri-food companies across eight European countries. Agri-Food Supply Chain Partner Preparedness (FSCPP) emerged as the pivotal factor with the highest degree of influence on the intention to use blockchain-driven supply chain platforms. Additionally, the results from this study offer support for the significant influence of Performance Expectancy (PE), Effort Expectancy (EE), and Perceived Trust (PT) on usage intention, while also revealing the positive impact of Organizational Blockchain Readiness (OBR) on expected Usage Behavior (UB). This study provides significant insights into blockchain adoption within agri-food supply chains, contributing to the existing literature through an extended UTAUT framework.

High temporal resolution records of the velocity of Hansbreen, a tidewater glacier in Svalbard

Abstract. Monitoring changes in glacial dynamics is essential for understanding the environmental response to accelerated climate warming in the Arctic. However, geodetic surveys in polar regions continue to present considerable challenges because of the harsh environmental conditions and the polar night. This study records a 14-year-long time series (2006–2019) of global navigation satellite system (GNSS) surveys of the positions of 16 ablation stakes distributed across Hansbreen, a tidewater glacier in southern Svalbard. The measurements were conducted with an exceptionally high temporal resolution, from about 1 week to about 1 month, and covering altitudes ranging from 20 to 490 m a.s.l. The position of one stake was surveyed every day. The primary data products consist of the stake coordinates and velocities. Time series of annual and seasonal velocities are also provided. This dataset may be a subject of further studies of glacier dynamics in relation to the long-term and seasonal impact of climate change on ice flow in the region. It also offers unique material for tuning numerical models of glacier dynamics and for validating satellite-derived products such as velocity and digital elevation models. The dataset described here has been made publicly available through the Zenodo repository: https://doi.org/10.5281/zenodo.8289380 (Błaszczyk et al., 2023).

Navigating climate change complexity and deep uncertainty: approach for building socio-ecological resilience using qualitative dynamic simulation

The consequences of climate change on different sectors of society are interrelated. The threats posed by rising global temperatures, intensifying extreme weather events, and shifting climatic patterns are becoming increasingly evident all around the world. Policymakers face the daunting task of assessing climate change risks, encompassing impacts and response strategies, to guide sustainability transformations. In this study, we introduce a four-step qualitative Decision Making Under Deep Uncertainty (DMDU) approach in the context of Climate Change Impact Assessments (CCIA). Our goal is to enhance the integration of CCIA into spatial planning, particularly in the Global South, using qualitative system dynamics simulation. Emphasizing the value of qualitative DMDU, we explore vulnerability and resilience through a lens of multi-sectoral and multi-scalar socio-ecological processes. We exemplify our approach by applying CCIA to the coastal zone of Yucatán, Mexico, accounting for social and environmental heterogeneity across the four Regions in which it is administered. Results identify the optimal allocation of climate change mitigation and adaptation policies to address specified resilience in each Region, all of which are required to achieve the overall resilience of the coastal zone. We argue that our qualitative DMDU approach provides an analytical platform to address the trade-offs inherent in the ranking of multiple vulnerabilities related to achieving general resilience.

Modeling the Impact of Climate Change on Streamflow in the Meghna River Basin: An Analysis Using SWAT and CMIP6 Scenarios

This study assesses future climate change impacts on the hydrologic response of the Upper Meghna River Basin (UMRB), a major river system in Bangladesh. Separate SWAT (Soil and Water Assessment Tool) hydrologic models were developed for the three major sub-basins of the UMRB, i.e., Barak, Meghalaya, and Tripura, considering their unique geographical, hydrological, and land-use characteristics. To evaluate the efficiency of multi-site modeling in providing better model performance, the SWAT models were calibrated at both single and multiple locations. Those models were then simulated to estimate future flows using climate projection data from thirteen CMIP6 General Circulation Models (GCMs) under moderate and extreme emission scenarios, SSP2-4.5, and SSP5-8.5. The results revealed that the annual maximum flow will keep increasing gradually with time. The outlets of the Meghalaya sub-basin will experience a more significant rise in future flow in the upcoming decades compared to the Barak and Tripura sub-basins. Results showed that dry season flows with increases of up to 31–50% would be less affected compared to the wet periods, which could experience increases of up to 47–66%) across the sub-basins by the end of the 21st century under extreme emission projections. Besides an increasing trend in the mean flow, future flows at several outlets also exhibited an escalation in the intensity and frequency of extreme flood events.

Possible changes and occurrences of future wave power in an enclosed sea using a high-resolution regional climate model

The present study evaluates future wave power resources and detects a possible impact of climate change on wave power in an enclosed sea (Black Sea) for the 21st century. The wave data are obtained from a third-generation spectral wave model using a validated RCM (Regional Climate Model). The wave power projection and projected occurrences are analyzed for near and middle future (NF, MF) periods based on two RCP (Representative Concentration Pathway) scenarios (4.5 and 8.5). Possible changes in wave power for the NF 2021–2060 and MF 2061−2100 periods are evaluated by comparing the historical (1970–2005) period. According to two RCP scenarios, the wave power potential for the NF is expected to increase markedly over the entire basin, while, for the MF, the changes are projected by decreases, especially in the northeastern and western parts of the basin. Furthermore, projected occurrences are examined using Energy Level Occurrences known as available, moderate, and rich level occurrences. The 15 reference points over the basin are chosen to detect the most suitable location(s) for future wave power developments. All spatial and local analyses indicate that the western basin, especially the southwest, will continue having high wave power potential and occurrences in future periods.

Predicting the impact of climate change on the area of wetlands using remote sensing

Predicting the impact of climate change on the area of wetlands using remote sensing

Assessing Climate Change Impacts on Streamflow and Baseflow in the Karnali River Basin, Nepal: A CMIP6 Multi-Model Ensemble Approach Using SWAT and Web-Based Hydrograph Analysis Tool

Our study aims to understand how the hydrological cycle is affected by climate change in river basins. This study focused on the Karnali River Basin (KRB) to examine the impact of extreme weather events like floods and heat waves on water security and sustainable environmental management. Our research incorporates precipitation and temperature projections from ten Global Circulation Models (GCMs) under the Coupled Model Intercomparison Project Phase 6 (CMIP6). We applied thirteen statistical bias correction methods for precipitation and nine for temperatures to make future precipitation and temperature trend projections. The research study also utilized the Soil and Water Assessment Tool (SWAT) model at multi-sites to estimate future streamflow under the Shared Socioeconomic Pathway (SSP) scenarios of SSP245 and SSP585. Additionally, the Web-based Hydrograph Analysis Tool (WHAT) was used to distinguish between baseflow and streamflow. Our findings, based on the Multi-Model Ensemble (MME), indicate that precipitation will increase by 7.79–16.25% under SSP245 (9.43–27.47% under SSP585) and maximum temperatures will rise at rates of 0.018, 0.048, and 0.064 °C/yr under SSP245 (0.022, 0.066, and 0.119 °C/yr under SSP585). We also anticipate that minimum temperatures will increase at rates of 0.049, 0.08, and 0.97 °C/yr under SSP245 (0.057, 0.115, and 0.187 °C/yr under SSP585) for near, mid, and far future periods, respectively. Our research predicts an increase in river discharge in the KRB by 27.12% to 54.88% under SSP245 and 45.4% to 93.3% under SSP585 in different future periods. Our finding also showed that the expected minimum monthly baseflow in future periods will occur earlier than in the historical period. Our study emphasizes the need for sustainable and adaptive management strategies to address the effects of climate change on water security in the KRB. By providing detailed insights into future hydrological conditions, this research serves as a critical resource for policymakers and stakeholders, facilitating informed decision-making for the sustainable management of water resources in the face of climate change.

Arbuscular Mycorrhizal Fungi-Mediated Modulation of Physiological, Biochemical, and Secondary Metabolite Responses in Hemp (Cannabis sativa L.) under Salt and Drought Stress

The increasing impact of global climate change has resulted in adversity stresses, like salt and drought, gradually becoming the main factors that limit crop growth. Hemp, which contains numerous medicinal active components and multiple bioactive functions, is widely used in the agricultural, industrial, and medical fields, hence promoting the rapid development of related industries. Arbuscular mycorrhizal fungi (AMF) can establish a symbiotic relationship with 80% of vascular plants. This symbiosis promotes host plant growth, regulates plant physiology and biochemistry, facilitates secondary metabolite synthesis, and enhances resistance to abiotic stresses. However, the effects of salt stress, drought stress, and AMF interaction in hemp are not well understood. In this study, to investigate this, we performed a study where we cultured hemp that was either inoculated or uninoculated with Funneliformis mosseae and determined changes in effective colonization rate, growth, soluble substances, photosynthesis, fluorescence, ions, and secondary metabolites by cultivating hemp under different concentrations of NaCl (0 mM, 100 mM, and 200 mM) and different soil moisture content (45%, 25%, and 15%). The results showed that salt, drought stress, or salt–drought interaction stress all inhibited colonization rate after stress, plant growth, mainly due to ion toxicity and oxidative damage. Inoculation with F. mosseae effectively alleviated plant growth inhibition under 100 mM NaCl salt stress, drought stress, and salt–drought interaction stress conditions. It also improved osmoregulation, photosynthetic properties, fluorescence properties, and ion homeostasis, and promoted the accumulation of secondary metabolites. However, under 200 mM NaCl salt stress conditions, inoculation with F. mosseae negatively affected plant physiology, biochemistry, and secondary metabolite synthesis, although it did alleviate growth inhibition. The results demonstrate that there are different effects of salt–drought interaction stress versus single stress (salt or drought stress) on plant growth physiology. In addition, we provide new insights about the positive effects of AMF on host plants under such stress conditions and the effects of AMF on plants under high salt stress.

Impacts of climate change on the natural distribution of species of lowland high and low in the Amazon

The areas of Amazonian floodplains have added ecological value to their multiple ecosystem services, including water supply, local climate regulation, biodiversity with a marked number of endemic species, and diversity of micro-habitat. Considering the importance of conserving these environments, this study aimed to analyze the behavior and delimit the areas of the natural distribution of forest species Alchornea castaneifolia (Willd.) A. Juss and Laetia corymbulosa(lowland low), Maquira coriacea (H.Karst.) C.C. Berg (Moraceae), and Ocotea cymbarumKunth (high floodplain), besides evaluating the potential impacts of climate change on the future distribution inferring on its conservation. The potential species distribution was modeled using Environmental Modelling & Software, by employing algorithms such as Bioclim, Domain, Maximum Entropy, Random Forests, and Support Vector Machine (SVM). The projections indicate that climate change threatens the occurrence of floodplain species. Under the SSP 585 scenario for both periods, the four species studied will lose areas of climatic adequacy until the end of the 21st century, especially in the Brazilian Amazon. The study shows the need to increase socio-environmental responsibility through conserving current protected areas in freshwater ecosystems and implementing new priority areas for conserving wetlands (Ramsar Sites) in the Amazon. Such measures are essential to ensure in situ conservation and protect them from habitat loss.

Climate change and crop production nexus: assessing the role of technological development for sustainable agriculture in Vietnam

Purpose This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018. Design/methodology/approach Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis. Findings The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam. Research limitations/implications This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production. Originality/value To the best of the authors’ knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation.

Carbon Monitor Power-Simulators (CMP-SIM v1.0) across countries: a data-driven approach to simulate daily power generation

Abstract. The impact of climate change on power demand and power generation has become increasingly significant. Changes in temperature, relative humidity, and other climate variables affect cooling and heating demand for households and industries and, therefore, power generation. Accurately predicting power generation is crucial for energy system planning and management. It is also crucial to understand the evolution of power generation to estimate the amount of CO2 emissions released into the atmosphere, allowing stakeholders to make informed plans to reduce emissions and to adapt to the impacts of climate change. Artificial intelligence techniques have been used to investigate energy-demand-side responses to external factors at various scales in recent years. However, few have explored the impact of climate and weather variability on power demand. This study proposes a data-driven approach to model daily power demand provided by the Carbon Monitor Power project by combining climate variables and human activity indices as predictive features. Our investigation spans the years 2020 to 2022 and focuses on eight countries or groups of countries selected to represent different climates and economies, accounting for over 70 % of global power consumption. These countries include Australia, Brazil, China, the European Union (EU), India, Russia, South Africa, and the United States. We assessed various machine-learning regressors to simulate daily power demand at the national scale. For countries within the EU, we extended the analysis to one group of countries. We evaluated the models based on key evaluating metrics: coefficient of determination (R2), mean absolute error (MAE), root mean squared error (RMSE), and median absolute error (MedAE). We also used the models to identify the most influential variables that impact power demand and determine their relationship with it. Our findings provide insight into variations in important predictive features among countries, along with the role played by distinct climate variables and indicators of the level of economic activity, such as weekends and working days, vacations and holidays, and the influence of COVID-19.

The impact of temperature on increased airborne pollen and earlier onset of the pollen season in Trentino, Northern Italy

The impact of climate change on ecosystems can be assessed through pollen dispersion data, which acts as a proxy for the plant flowering stage. The aim of this study is to verify if changes occurred in the season and concentration of airborne pollen in Trentino (Northern Italy), and to evaluate if temperature (T), precipitation (P), and/or land use influenced such changes in the period 1989–2018. Airborne pollen, sampled by a Hirst-type trap, was analyzed by light microscopy, and pollen concentrations were obtained. Twenty-four taxa, covering 95% of the local pollen spectrum, were considered for this study. A significant upward trend in annual pollen integral (APIn) is the main outcome over the study period. The increase in APIn is more evident when analyzing the data in three decadic blocks, both for all the considered taxa (+ 58%) and for Arboreal Pollen (AP; + 155%). Considering both the annual data and the decadic blocks, APIn shows a significant positive trend for Cupressaceae/Taxaceae, Ulmus, Populus, Salix, Ostrya, Quercus, Olea (AP), and Plantago, Cannabaceae, Ambrosia (non-arboreal pollen, NAP); a significantly earlier start of the Main Pollen Season (MPS) is proved for Rumex and Poaceae. APIn for 24 taxa shows a significant positive correlation with annual T min (< 0.005) and T mean (< 0.001), both of which showing a significant increase, and a negative correlation (< 0.025) with the number of frost days. From a human health perspective, higher temperatures, driven by climate changes, lead to higher concentrations of allergenic airborne pollen, turning into a higher risk for allergy sufferers.

Climate Change Impact on Insect Population in Vegetable Crops: A Review

One of the world's largest nations, India is known for its distinctive landscape, which distinguishes it as a distinct geographical entity and a global center of mega diversity. Pest populations in vegetable crops may be significantly impacted by climate change. Additionally, warmer temperatures can lead to faster insect development and increased reproductive rates. Farmers and researchers need to monitor these changes and develop strategies to mitigate the potential negative effects on vegetable crops. In response to climate change, whiteflies may exhibit shifts in their distribution patterns, population sizes, and behavior. They may also evolve certain traits that help them better survive in warmer or more variable climates.

A review of the potential involvement of small RNAs in transgenerational abiotic stress memory in plants.

Crop production is increasingly threatened by the escalating weather events and rising temperatures associated with global climate change. Plants have evolved adaptive mechanisms, including stress memory, to cope with abiotic stresses such as heat, drought, and salinity. Stress memory involves priming, where plants remember prior stress exposures, providing enhanced responses to subsequent stress events. Stress memory can manifest as somatic, intergenerational, or transgenerational memory, persisting for different durations. The chromatin, a central regulator of gene expression, undergoes modifications like DNA acetylation, methylation, and histone variations in response to abiotic stress. Histone modifications, such as H3K4me3 and acetylation, play crucial roles in regulating gene expression. Abiotic stresses like drought and salinity are significant challenges to crop production, leading to yield reductions. Plant responses to stress involve strategies like escape, avoidance, and tolerance, each influencing growth stages differently. Soil salinity affects plant growth by disrupting water potential, causing ion toxicity, and inhibiting nutrient uptake. Understanding plant responses to these stresses requires insights into histone-mediated modifications, chromatin remodeling, and the role of small RNAs in stress memory. Histone-mediated modifications, including acetylation and methylation, contribute to epigenetic stress memory, influencing plant adaptation to environmental stressors. Chromatin remodeling play a crucial role in abiotic stress responses, affecting the expression of stress-related genes. Small RNAs; miRNAs and siRNAs, participate in stress memory pathways by guiding DNA methylation and histone modifications. The interplay of these epigenetic mechanisms helps plants adapt to recurring stress events and enhance their resilience. In conclusion, unraveling the epigenetic mechanisms in plant responses to abiotic stresses provides valuable insights for developing resilient agricultural techniques. Understanding how plants utilize stress memory, histone modifications, chromatin remodeling, and small RNAs is crucial for designing strategies to mitigate the impact of climate change on crop production and global food security.

Investigating Vulnerability, Adaptation, and Resilience: A Comprehensive Review within the Context of Climate Change

This review seeks to enhance the understanding of the critical concepts of vulnerability, adaptation, and resilience within the context of global environmental challenges, with a particular focus on climate change. Climate change is characterized by rising global temperatures and an increase in extreme weather events, making the comprehension and addressing of these concepts crucial for effective adaptation strategies. Despite widespread recognition of the interconnectedness of vulnerability, adaptation, and resilience, there remains a gap in a comprehensive understanding of how these concepts interrelate. Through synthesizing existing literature, this review provides a detailed examination of their definitions and the interrelationships among vulnerability, adaptation, resilience, and climate-related disasters. Additionally, it explores the impact of climate change on future disaster risk reduction efforts by analyzing the nexus between climate change adaptation and disaster risk reduction. Key findings highlight the necessity of incorporating social, institutional, economic, and environmental factors into adaptation planning and call for innovative approaches to boost adaptive capacity and resilience. This review not only furthers the discourse in research, policy, and practice in this vital area but also offers strategic insights for developing more resilient and adaptive societies amidst the challenges posed by climate change.

Modelling the impact of climate change on cultural practices: the future of fen skating (1981–2079)

Cultural practices reliant on the formation of ice are likely to be affected by climate change across the world. Outdoor skating is a popular pastime in many regions of North America, Asia and northern Europe. Fen skating is a traditional sport practiced in the flat area of east England, when shallowly flooded fields and meadows freeze to form large stretches of ice. To assess the future of fen skating, climate metrics were constructed to capture the freezing conditions needed for fen skating to take place. A skating freeze was defined as requiring the daily minimum temperature to be either (i) four nights below -4 °C, (ii) three nights below -5 °C or (iii) two nights below -8 °C. The 12 km resolution UKCP18 dataset was used to assess the frequency and duration of skating freezes in the fens for the period 1981 to 2079. Results from the 12 UKCP18 model members showed notable variability and only four model members successfully captured past skating freezes. Outputs from these four model members showed a rapid decrease in the frequency and duration of skating freezes, raising concerns over the future of this sport.

Soil organic matter dynamics and stability: Climate vs. time

Climate and time are among the most important factors driving soil organic carbon (SOC) stability and accrual in mineral soils; however, their relative importance on SOC dynamics is still unclear. Therefore, understanding how these factors covary over a range of soil developmental stages is crucial to improve our knowledge of climate change impact on SOC accumulation and persistence. Two chronosequences located along a climate gradient were investigated to determine the main interactions among time (age) and climate (precipitation and temperature) on SOC stability and stock with depth. Considering a common depth (0–15 or 0–30 cm), in the drier chronosequence, the older soil showed the highest SOC stock, while the younger exhibited the lowest carbon accumulation. Considering the whole profile, the SOC stock increased with age. In the wetter chronosequence, the younger soil showed the highest SOC stock considering a common depth, whereas, when the entire profile is taken into account, the older one accumulated 2–3 times more SOC than the others. In both chronosequences, significant stocks of SOC (~42 %) were accumulated >30 cm. Soil organic matter stability, assessed by thermal analysis and heterotrophic respiration, increases with depth and age only in the drier chronosequence. Soils from the wetter chronosequence were instead characterized by a greater quantity of labile and/or not-stabilized SOC; here, the amorphous Fe/Al-rich secondary mineral weathering products showed an essential predictor function of SOC storage, although they do not seem to be involved in SOC stabilization mechanisms. Otherwise, the interaction of SOC with fine particles, short-range order minerals, and organo-metal complexes represent the significant stabilization mechanisms in soils from drier climate. The results highlighted how the age factor plays an unassuming role in geochemical processes influencing SOC dynamics; however, climate determines different trajectories of soil development and SOC dynamics for a given soil age. Thus, soil age shows a key role in SOC stabilization especially in drier climatic conditions, while wetter conditions determine an accumulation of a higher yet more labile amount of SOC.