Effects Of Climate Change Research Articles

Conservation value and carbon sequestration potential of urban green spaces in a growing city: Case of the city of Bouaflé

Faced with the effects of climate change, green spaces are very determining in the provision of ecosystem services, particularly in carbon sequestration. This is why, from a perspective of sustainable management of these high-value spaces, this study was carried out. Surface and itinerant survey methods were combined to collect floristic data. At the end of the inventories, 99 species distributed between 33 families and 75 genera including 24 species with special status were recorded in eight (08) types of development. The total biomass of all the species inventoried at Bouaflé is 4385.78 t, corresponding to a carbon rate of 2192.91 t for a CO2 equivalent of 8047.99 t. The economic value of the rate of CO2 sequestered by all types of development varies from 24143.97 Euros, or 15814274 FCFA according to the CDM carbon price to 112671.86 Euros, or 73800068 FCFA according to the REDD+ carbon price. Social and educational establishments recorded the highest biomass (1841.88 t) while the lowest biomass (5.53 t) was estimated in sports equipment. The average biomass estimated in all types of development is of the order of 232.02±185.64 t/ha, which corresponds to a carbon rate of 116.01±92.82 t/ha and an equivalent CO2 of 425.76±340.65 t/ha. Considering each type of development, the average value of biomass varies between 24.83 t/ha in sports facilities and 468.79 t/ha in cemeteries.

Morocco, at the Heart of the Harmonization of the African Union's Migration Policies: Context, Complexity, Diversity, Effects and Challenges

Since the mid-1980s, the European Union has adopted a cautious attitude to migratory flows. It has constantly stepped up initiatives to combat immigration, by tightening border controls and reducing the granting of visas, thereby forcing would-be emigrants to look for alternatives. At the same time, Africa is facing unique migration challenges. The consequences of colonization, the imposition of capitalist relations and the development of an extroverted economy, among others, continue to influence current migration dynamics. Persistent economic crises, exacerbated by inequitable global economic policies, are driving many people to seek better opportunities elsewhere. In addition, the effects of climate change, such as desertification, droughts and floods, are intensifying migratory pressures. African countries therefore need to develop effective migration policies to govern migratory flows and respond to geopolitical challenges. It is crucial to put in place regional and international cooperation mechanisms to manage migration in a coordinated and humane manner. This means thinking carefully about migration issues, considering the historical, economic and political realities that shape them. This issue must be at the heart of the concerns of States and the African Union. It is true that attempts are being made at continental level, such as the Kampala Convention and the establishment of the African Continental Free Trade Area (ACFTA), but these measures can only be truly appreciated if they are applied on the ground.

Effect of Climate Change on Alpine Flowers

Global warming results in climate change that increases the intensity of rainfall, drought, dry spell, heat waves. This condition have profound impact on alpine plant ecology and induce migration or range shifts of spe¬cies in search for their optimal growth conditions. These shifts subsequently lead to change in local species composition, often resulting in a relative increase of warm demanding species and a decreasing number of cold demanding species. The result of this change may cause habitat loss and disastrous extinction in those alpine environments. An alpine flower has been serving as source of genetic material for ornamental flower industry. Improvement of commercial cultivars through interspecific hybridization with wild relatives has also been the major way forward for transfer of important traits such as disease resistance. However, as a result of global warming, heat stress has become the major challenge for alpine ecosystem that is estimated to be 3% of terrestrial habitats. Here, I review literature regarding impacts of climate change on alpine flowers by using specific commercially important flowers as an example: <i>Dianthus</i>, <i>Primula</i> and <i>Rhododendron</i>. Then, I discuss ways to enhance <i>Rhododendron</i> breeding efficiency for heat stress using invitro growth conditions. Finally, I summarize with indicating future areas of research that should be undertaken.

Effects of Climate Change on the Distribution of Scomber japonicus and Konosirus punctatus in China’s Coastal and Adjacent Waters

Climate change has increasingly impacted the marine environment, with various marine environmental factors interacting to influence fish distribution. Assessing the impact of climate change on the future distribution of fish depends on understanding how biological responses interact with environmental conditions. Enhancing our understanding of the potential impacts of climate change is crucial for the sustainable development of marine fisheries. In this study, we analyzed the habitat suitability of Scomber japonicus and Konosirus punctatus in the coastal waters of China (17°–41° N, 107°–130° E) using marine environmental data, including, as follows: sea surface temperature (SST); sea surface salinity (SSS); pH; and biological occurrence data from 2000 to 2010. A maximum entropy (MaxEnt) model was employed to predict the future distribution of these two species based on the shared socioeconomic pathway (SSP) scenarios for 2040–2050 and 2090–2100. The results indicate that climate change will significantly affect the future habitat distribution of S. japonicus and K. punctatus, leading to a decrease in suitable habitat areas offshore China and a gradual shift northeastward in the center of these habitats. These findings are essential for understanding the impacts of climate change on the distribution of S. japonicus and K. punctatus, with significant implications for fisheries resource assessment and management.

Remote Sensing, Artificial Intelligence and Smart Agriculture Technology Trends of the Future

The efficient and sustainable operation of the agricultural sector has become increasingly important in light of the transformations brought about by the third and fourth industrial revolutions. Population growth, increasing food demand, rising input costs, and environmental pressures necessitate innovative approaches not only to ensure food security but also to mitigate the effects of climate change. The European Union (EU) emphasizes the role of digital technologies in supporting agricultural productivity and resilience by promoting a bio-based economy. Strategies such as Farm to Fork (F2F) initiative aim to reduce pesticide and nutrient inputs, thus preserving biodiversity and supporting ecosystem health. Artificial intelligence (AI) and predictive analytics, along with connected sensors, offer opportunities to optimize water and nutrient usage and increase crop yields. By utilizing AI, combining remote sensing technologies, and monitoring changes in land use, it is possible to reduce environmental risks associated with agricultural practices. Although there are challenges such as high investment costs and data control for the integration of digital technologies, ongoing research and development efforts promise to overcome these obstacles. In conclusion, the integration of digital technologies into agriculture presents unique opportunities to address urgent issues and achieve sustainability goals. This review discusses the applicability of fundamental technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), Precision Agriculture (PA), and Machine Learning (ML) in making agriculture more efficient and sustainable, by enabling the perception, monitoring, collection, analysis, and extraction of meaningful insights from agricultural data.

University students' perception of the effects of climate change on food security 2023

University students' perception of the effects of climate change on food security 2023

Digitalization and Decarbonization of Sri Lanka's Electric Power System: A Way Forward for Sustainability

The global energy landscape is undergoing a transformative shift driven by the dual imperatives of digitalization and decarbonization, essential for creating sustainable and resilient power systems (Lichtenthaler, 2021, [1]). This transformation is particularly critical for developing nations like Sri Lanka, where the integration of smart technologies and renewable energy sources can significantly enhance system efficiency and contribute to a robust response to climate change challenges (Lichtenthaler, 2021, [1]). This paper examines the potential of leveraging advanced digital technologies—such as artificial intelligence, big data analytics, and the Internet of Things—to optimize energy management and facilitate a swift transition toward a low-emission economy in Sri Lanka, while addressing the socio-economic implications of this transition. Furthermore, this study highlights the importance of fostering a circular economy through these technological advancements, emphasizing that innovative solutions can not only improve energy efficiency but also contribute to broader sustainability goals, ensuring equitable access to resources and combating the adverse effects of climate change. Through this lens, the investigation underscores the necessity of a holistic approach that integrates digital transformation with sustainable practices, enabling the decoupling of economic activity from resource depletion and environmental degradation, thereby fostering a resilient energy future for Sri Lanka.

Combining insitu rainwater harvesting and integrated nutrient management of organic manure improves soil moisture, fertility and crop yields in marginalized areas: A review

Soil moisture stress and infertility are major biophysical constraints which limit crop production and food security in marginalized areas. Marginal areas are mainly associated with low rainfall which is insufficient to support crops until maturity is reached. The use of insitu rainwater harvesting methods such as planting pits, tied ridges, mulching, Zai pits and half-moon can be a solution to reduce moisture stress. This alone cannot improve crop yields hence the need to use integrated nutrient management (INM) of animal manure, biofertilisers, mineral fertiliser and composts to improve soil fertility, structure and increase water retention ability. Combining rainwater harvesting with INM has the potential to mitigate effects of climate change, improve crop yields and meet food demand in marginal areas. Various nutrient sources used as INM can restore soil health, increase microbial population, nutrient mineralisation and improve soil quality. Use of biofertilisers in agriculture reduces soil toxicity, improve nutrient availability and create a conducive environment for crop growth and development. Integration of tied ridges with cattle manure and mineral fertiliser has the potential of increasing infiltration rates, reducing surface runoff and increase crop yields with 50-150% regardless of soil type. This chapter sought to come up review the effects of rainwater harvesting methods and INM on soil fertility, moisture stress and crop yields in marginalized areas.

Impact of regional investment on the sustainable development goals: A group analysis of economic and territorial development

AbstractThe European Green Deal aims at increasing the sustainability of European economic sectors to mitigate the effects of climate change. Complementing this initiative, the Next Generation EU (NGEU) program, whose budget will exceed 800 billion € by 2026, is not merely a recovery plan but also a catalyst for green technologies and sustainable activities. Within this framework, Italy stands as the largest beneficiary of funds. The present study explored the distribution to date of 194.4 billion € NGEU funds across Italian regions and the Sustainable Development Goals (SDGs) that have received the most significant attention as a result of this funding. Leveraging multiple comprehensive datasets, including one encompassing more than 306,706 measures and sub‐measures, the analysis revealed that 55.5 billion € was directed towards Italy's “Green Revolution and Ecological Transition,” with a further 104.1 billion € allocated towards (predominantly) SDGs 7 and 9. Moreover, 70.3 billion € was directed towards southern Italy (including the islands), while 81.0 billion € was allocated to the north. Although the population in the north is approximately one‐third larger than that of the south, on a per capita basis, the north received 2930 € while the south received a significantly greater sum of 3470 €. Thus, the NGEU has not significantly reduced the north–south divide in economic terms. Furthermore, some southern regions have shown satisfactory sustainability performance, despite receiving a relatively lower allocation of NGEU funds. The “Made in Italy” initiative may represent a strategic approach to increasing competitiveness in the global and digital markets and fostering fraternity among Italian regions. The present research offers valuable insights into the regional distribution of funds and their impact on sustainable development, suggesting that territorial gaps may be mitigated through a pragmatic, community‐based approach.

Predicting the effect of climate change on the spatiotemporal distribution of two endangered plant species, Silene leucophylla Boiss. and Silene schimperiana Boiss., using machine learning, in Saint Catherine Protected Area, Egypt

BackgroundClimate change significantly influences the geographical distribution of plant species worldwide, especially endemics. Endemic species are plants that live in limited distribution ranges of unique ecology and, thus, are the most vulnerable species to climate change. Therefore, understanding the impacts of climate change on the distribution of these species can assist in developing appropriate plans for their conservation. In this study, we aimed to apply various species distribution models (SDMs) to predict the current potential distributions of two endangered plant species, Silene leucophylla (S. leucophylla, endemic) and Silene schimperiana (S. schimperiana, near-endemic), in Saint Catherine protected area (St. Catherine PA), Egypt. Then, using the best-fit model to project their future distribution under the maximum climate emission scenario (Representative Concentration Pathway 8.5 (RCP8.5)). Six different SDMs were constructed using different geospatial raster imagery sets of environmental factors. For each model, five machine learning (ML) algorithms were used. The results of these ML algorithms were then ensembled by calculating the weighted average of their predictions.ResultsBased on the analysis of digital geospatial imageries produced by the best-fitting model, the predicted suitable areas of S. leucophylla and S. schimperiana were 23.1 km2 and 125 km2, respectively. These sites are located mainly in the high-elevation middle northern part of the study area. Annual precipitation, mean temperature of the driest quarter, altitude, and precipitation seasonality were the essential predictors of the distributions of both species. Future predictions of both species indicated opposing results between the studied species. Predictions in the 2050 and 2070 future conditions revealed significant range contraction for the distribution of S. leucophylla. For S. schimperiana, a range shift is predicted, with both range contraction and range expansion of its current suitable habitats, for the same future projections. Unfortunately, in 2080 predictions, both species could be projected to a complete loss from the entire area.ConclusionThis study highlights the importance of including diverse types of environmental variables in SDMs to produce more accurate predictions, rather than relying only on one variable type. It also revealed the potential negative impacts of future climate change on the distributions of two endangered plant species, S. leucophylla and S. schimperiana, inhabiting St. Catherine PA. Consequently, we urgently recommend the initiation of different plans and strategies seeking their conservation.

Assessing the phenology and reproductive output of loggerhead turtles in relation to climatic variables at Patara Beach, Türkiye

AbstractLoggerhead turtles (Caretta caretta), being ectothermic organisms, could be especially susceptible to climate change effects, and may exhibit climate‐related variation in their reproductive behaviours such as phenology, annual nest numbers, clutch size, hatching success, incubation period and sex ratio. This study investigated the reproductive phenology and outputs of loggerhead turtles and their relationships with climatic variables over a 5‐year period (2019–2023) at Patara Beach, Türkiye. We found significant fluctuations in atmospheric temperature, sea surface temperature and relative humidity, and that female turtle emergences on Patara Beach could temporarily adjust their phenology in response to these minor environmental changes. We highlight the importance of understanding the impacts of phenological shifts on the ability to satisfy the conditions over the nesting season that determine reproductive output. Our statistical analyses also showed that increasing sea water temperatures and atmospheric temperatures, as well as decreasing precipitation and relative humidity, had direct and/or indirect effects on the nesting phenology and reproductive output of loggerhead turtles. The findings from this study indicate that atmospheric temperature significantly affected incubation period, hatching success rate, the number of dead embryos and the number of empty eggshells. Additionally, relative humidity had a significant impact on the incubation period and the number of empty eggshells. In this context, rising temperatures led to drier nest conditions, decreased incubation periods and increased nest temperatures, resulting in higher proportions of female offspring. In conclusion, there are still gaps in our understanding of the effects of climate change on the reproductive biology of loggerhead turtles, and more studies are needed at both the Mediterranean and global scales to better understand these effects.

Farmers’ Awareness of the Negative Effects of Climate Change on Strategic Grain Crops and Adaptation Mechanisms in Kafr El-Sheikh Governorate in the Arab Republic of Egypt

Farmers’ Awareness of the Negative Effects of Climate Change on Strategic Grain Crops and Adaptation Mechanisms in Kafr El-Sheikh Governorate in the Arab Republic of Egypt

A spatio-temporal model for temporal evolution of spatial extremal dependence

Few spatio-temporal models allow temporal non-stationarity. When modeling environmental data recorded over the last decades of the 20th century until now, it seems not reasonable to assume temporal stationarity, since it would not capture climate change effects. In this paper, we propose a space–time max-stable model for modeling some temporal non-stationarity of the spatial extremal dependence. Our model consists of a mixture of max-stable spatial processes, with a rate of mixing depending on time. We use maximum composite likelihood for estimation, model selection, and a non-stationarity test. The assessment of its performance is done through wide simulation experiments. The proposed model is used to investigate how the rainfall in the south of France evolves with time. The results demonstrate that the spatial extremal dependence is significantly non-stationary over time, with a decrease in the strength of dependence.

Impacts of Irrigated Water Use on Household’s Income in South Wollo Zone, Amhara Regional State, Ethiopia

Agriculture is the backbone of the Sub-Saharan African economy. Ethiopia's GDP is also shared by 45 from the agriculture sectors. However, it is confronted and challenged by variable rainfall and climate changes. Particularly, in South Wollo zone, agriculture is not exceptional in facing such daunting challenges and effects of variable rainfall and climate change despite there are abundant alternative irrigated water resources. River and groundwater sources have not yet been used as alternative uses for agricultural production. As a result, rural households' income couldn’t meet their minimum food and nonfood requirements. This study, thus, attempted to evaluate the impact of irrigated water use on rural household's income in South Wollo Zone, Amhara regional state, Ethiopia. In pursuit of this, it employed a descriptive type of research design and triangulated research approach that consists of both quantitative and qualitative techniques. Primary and secondary data were collected from small scale irrigated households and secondary sources. Binary logistic regression was used to determine major significant factors that affect households' irrigated water use for agricultural production. A propensity core matching model was employed to evaluate irrigated water use and agriculture on household’s income. This study result (binary logistic regression result) showed that the household’s family size, land size and willingness were significant factors that determined irrigated water use for agricultural production at 95 percent level of significance. The propensity score matching model result also shows that irrigated water use significantly created significant impact on household’s income. It is, thus, keenly important to change and improve the smallholder farmer’s land size, extension services, rural credit, technology, education level, awareness about family size, and willingness to use irrigated water sources, such as, ground and river water for agriculture agricultural production that increase their level of income.

Assessment of Habitat Quality in Arid Regions Incorporating Remote Sensing Data and Field Experiments

China’s arid regions are particularly vulnerable to the adverse effects of climate change and human activities, which pose threats to habitat quality. Consequently, evaluations of these effects are vital for devising ecological strategies and initiating regional remediation efforts. However, environmental variations in arid areas can cause habitat quality fluctuations, which complicates precise assessments. This study introduces a refined methodology that integrates remote sensing data and field survey biomass data to modify the habitat quality estimates obtained from the InVEST model in the Altai region over three decades. A comparative analysis of the unmodified, normalized difference vegetation index (NDVI)-modified and biomass-modified habitat quality estimates was conducted. The results revealed an improvement in the correlation between habitat quality and field observations, with a significant increase in the R2 value from 0.129 to 0.603. The unmodified model exhibits subtle variations in habitat quality in mountainous areas, with a slight decline in the plains. However, the modified model shows an increasing trend in mountainous areas. This finding contrasts with the reductions in mountains typically reported by other studies. The refined approach accurately expresses the variations in habitat quality across different habitat types, with declines in forested areas and improvements in shrubland and grassland regions. This model is suitable for arid regions and accommodates urban and agricultural ecosystems affected by human activities, offering empirical data for biodiversity and habitat management.

Creating a Responsible Renewable Energy Investment Model for the MENA Region's Low-Carbon Transition

Addressing climate change presents specific challenges for the countries of the Middle East and North Africa (MENA), particularly concerning oil production and water scarcity, but it also offers opportunities for new paths toward sustainability. The transition to low-carbon energy raises significant concerns for oil and gas producers in the MENA region, especially regarding their dependence on hydrocarbon revenues. Without proper adjustments, this transition could worsen macroeconomic imbalances and potentially threaten existing social contracts. Policymakers are working to promote various renewable energy sources and implementation strategies to mitigate the adverse effects of climate change. As a result, the development of an index capable of accurately measuring and benchmarking a country's overall sustainability and economic performance becomes essential. This index should provide a comprehensive assessment of both the current and future state of renewable energy. Additionally, it must highlight key environmental, social, governance (ESG), and economic factors within the renewable energy sector. This proposal aims to establish a composite index, referred to as the Renewable Energy Responsible Investment Index (RERII), covering 19 countries and utilizing 22 distinct metrics. The RERII trend is calculated from 2010 to 2019. The proposed index can serve as a screening tool, decision-making aid, benchmarking instrument, and guide for sustainable development.

Dynamics and internal structure of a rock glacier: Inferring relationships from the combined use of differential synthetic aperture radar interferometry, electrical resistivity tomography and ground‐penetrating radar

AbstractRock glaciers are characteristic landforms in alpine environments originating from the movement of permanently frozen ground. Hereby, rock glacier velocity (RGV) is an important parameter for understanding the effects of climate change on mountain permafrost. Although understanding of rock glacier dynamics has increased during the last decades, linking small‐scale surface kinematics to sub‐surface properties and heterogeneities remains a challenge. To address this gap, we conducted geophysical surveys (electrical resistivity tomography [ERT] and ground‐penetrating radar [GPR]) along two profile lines of 450 and 950 m in length on a rock glacier in the Central Swiss Alps. Additionally, RGV was derived from Sentinel‐1 differential synthetic aperture radar interferometry (DInSAR) to quantify annual east–west displacement and elevation change as well as seasonal acceleration during the snow‐free summer months with a ground sampling distance of 5 m. Our results show that movement angle and seasonality are highly associated with different patterns in sub‐surface structure. These different movement patterns are linked to subunits of different morphological origins. Thereby, we can upscale the geophysical results based on the DInSAR surface movement parameters and outline an area within the study site probably affected by ice of glacial origin. Hence, DInSAR movement angle and seasonality can help to bring local sub‐surface information derived from time‐consuming geophysical investigations into the spatial domain. In this way, a better understanding of the current morphodynamics as well as the past and future evolution of the landform can be reached. Applying the approach to other sites with available geophysical investigations could enhance our knowledge about systematic links between surface kinematics and the internal structure of rock glaciers and other ice‐rich glacial and peri‐glacial landforms, as well as their response to a warming climate.

Factors Influencing the Adoption of Green Practices: A Case of Five Selected Shopping Malls in Lusaka District

There is growing recognition for the need for eco-friendly commercial buildings. However, there exists a significant gap between the potential for developing them and the actual implementation. Zambia faces the tangible impacts of climate change, such as droughts and floods, while the uptake of green initiatives remains sluggish. Environmental degradation, worsened by the absence of green initiatives, threatens ecosystems, biodiversity, and the overall health of the planet. Recognizing the urgent need for change, there is a growing consensus that economic growth should no longer be pursued at the expense of environmental degradation. Yet, despite the abundance of opportunities to develop and implement green practices, various stakeholders have not fully embraced these options. This study delved into the factors influencing green practice adoption, focusing on five prominent shopping malls in Lusaka district, Zambia. A mixed methods approach was adopted, and involved 25 purposively selected respondents that attended a questionnaire uploaded via google forms and semi-structured in-depth interviews. Quantitative data was analyzed using SPSS while content analysis was adopted for qualitative data. The study found a positive correlation between perceived benefits of green practices and willingness to adopt green practices. However, the study showed a disconnect between knowledge of climate change effects and adoption of green practices, which meant that the choice to implement green practices was not influenced by the knowledge of the consequential effects of climate change. This study findings underscore the importance of the educational knowledge on the benefits green implementation and government incentives had in fostering green practice adoption within commercial establishments. While the study provides valuable insights into the dynamics of green practice adoption in the context of Lusaka district, limitations and potential biases underscore the need for further research in this area.

Waste Management, Waste Indicators and the Relationship with Sustainable Development Goals (SDGs): A Systematic Literature Review

Waste management plays an important role in sustainable development. The innovative management of waste results in minimizing the adverse effects of climate change, and social and economic sustainability. The creation of Sustainable Development Goals (SDGs) by the United Nations in 2015 was an important step toward environmental sustainability, whereby the 17 goals focus on strengthening the means of implementing and revitalizing the Global Partnership for Sustainable Development. This research paper applies a systematic literature review using the PRISMA methodology to analyze different published research papers and research reports mainly focused on waste management and its relationship with the SDGs. This paper extensively discusses the context of waste management, SDGs, waste indicators in SDGs, and the relationship between SDGs and waste management. This paper also widely discusses the aspects of waste management regarding SDGs. The results are further divided into two sub-categories, including descriptive results, which elaborate the different approaches that are used to review the literature for this paper, and thematic results, which include the key results and discussions of different aspects of this paper. The analysis of different published research papers and research reports mainly focuses on waste management and its relationship with the SDGs. This study presents a discussion of (1) the detailed context of waste management about SDGs, (2) the waste indicators in SDGs and (3) the relationship between waste management and SDGs. This study suggests future possible areas of research by extending the regional boundaries, increasing the number of papers, focusing on more specific SDG goals and targets and studying case studies based on the specific targets and indicators.

The Spatial Variation of Soil Structure Fractal Derived from Particle Size Distributions at the Basin Scale

The accurate characterization of soil structure is fundamental to groundwater science, environmental ecology, and Earth systems science. To address the challenge of quantifying the high spatial variability of large-scale soil structures, this study used a laser particle size analyzer to measure the distribution of soil particle size in 207 samples from ten profiles across the Daqing and Ziya River basins in the North China Plain. The quantified soil structure, expressed as soil fractal dimension D, was derived using monofractal theory. Various spatial analysis techniques, including Moran’s I index, correlation analysis heat maps, the Kolmogorov–Smirnov one-sample test, and geostatistical semivariogram function, were jointly applied to investigate the spatial variability of soil structural fractals across different depths in the piedmont plain–coastal areas of the two river basins. The results indicate the following: (1) Quantitative analysis confirms that under the influence of piedmont alluvial and fluvial dynamics, soil D values homogenize from the piedmont to the coastal areas, with decreasing particle size differences closer to the coast. However, the spatial variability of the soil structural fractals in the Ziya River Basin was greater than that in the Daqing River Basin. (2) The combined effects of climate change, regional differences, and human activity led to greater spatial variability in the soil structural fractals in the Ziya River Basin than in the Daqing River Basin. The correlation between D values and burial depth was strongest in the Xianxian profile (−0.78), whereas the spatial correlation was strongest in the Hengshui and Dacheng profiles (−0.47). (3) The greatest spatial variability in soil D values occurred at depths of 1–2 m, with a coefficient of variation of 23.595%, which was significantly higher than those at depths of 0–1 (14.569%) and 2–3 m (16.284%).