Search Results (24)

Urban heat islands (UHIs) are a growing sustainability challenge impacting public health, energy use, and climate resilience, especially in hot, arid cities like San Antonio, Texas, where land surface temperatures reach up to 47.63 °C. This study advances a data-driven, interdisciplinary approach to UHI mitigation by integrating Machine Learning (ML) with physical and socio-demographic data for sustainable urban planning. Using high-resolution spatial data across five functional zones (residential, commercial, industrial, official, and downtown), we apply three ML models, Random Forest (RF), Support Vector Machine (SVM), and Gradient Boosting Machine (GBM), to predict land surface temperature (LST). The models incorporate both environmental variables, such as imperviousness, Normalized Difference Vegetation Index (NDVI), building area, and solar influx, and social determinants, such as population density, income, education, and age distribution. SVM achieved the highest R² (0.870), while RF yielded the lowest RMSE (0.488 °C), confirming robust predictive performance. Key predictors of elevated LST included imperviousness, building area, solar influx, and NDVI. Our results underscore the need for zone-specific strategies like more greenery, less impervious cover, and improved building design. These findings offer actionable insights for urban planners and policymakers seeking to develop equitable and sustainable UHI mitigation strategies aligned with climate adaptation and environmental justice goals. Full article

Background: Human activity is recognised as a major contributor to changes in Earth’s climate, land surface, oceans, ecosystems, and biodiversity. These alterations are largely due to greenhouse gas emissions, deforestation, mass pollution, and land degradation. In light of these environmental challenges, examining the psychological determinants of pro-environmental behaviour has become increasingly important. Study’s Aim: To provide a comprehensive model evaluating the structural relationships among biospheric values, green self-identity, green self-efficacy, and eco-anxiety to investigate the underlying mechanisms relating to the adoption of various pro-environmental behaviours (PEBs). Methods: An online self-report questionnaire was completed by 510 Italian participants (aged 18–55, M = 35.18, SD = 12.58) between November and December 2023. Data analysis was performed using R statistical software, employing Structural Equation Modelling. Results: The results indicate that eco-anxiety, green self-efficacy, and green self-identity are significant positive predictors of PEBs. Furthermore, green self-identity significantly influences eco-anxiety and green self-efficacy, while biospheric values are a major trigger for both green self-efficacy and green self-identity, but not for eco-anxiety. Conclusions: These findings suggest that while eco-anxiety can be an adaptive motivator for PEBs, biospheric values foster a green self-identity and self-efficacy, which in turn drive pro-environmental actions. The study concludes that encouraging biospheric values and strong green self-identity is crucial for promoting sustainable behaviours. Full article

One of the important effects of global warming is the use of fossil fuels. Disadvantaged individuals may be affected by fossil fuel use more than others. In this study, the Kepez district of Antalya province, where the Social Vulnerability Index (SVI) is high, was selected as the study area. Five-year (2019–2023) NO₂, SO₂, and CO concentrations were extracted from the Sentinel-5P TROPOMI satellite with open-source code. These values were combined and compared with Land Use Land Cover (LULC) land classes obtained from the Sentinel-2 satellite. The same process was performed for Land Surface Temperature (LST) obtained from MODIS Terra and Aqua satellites, and interpretation was made according to the LST-LULC map and surface temperature. The integrated SVI was calculated with population, age, education, and gender data from the Turkish Statistical Institute and NO₂, SO₂, and CO concentrations from the Sentinel-5P TROPOMI satellite. It was mapped on a neighborhood basis with zonal statistics. Accordingly, 20.6% of the neighborhoods in Kepez were categorized as very high risk, and 16.2% were categorized as high risk. Integrated SVI with the determination made by evaluating only air pollution gave different neighborhood results. This revealed the importance of using the SVI in disaster risk assessments. This study has the potential to shed light on the social vulnerability-supported disaster risk information system that is likely to be created in the following years. Full article

Basic inventory is required for proper understanding and utilization of Earth’s natural resources, especially with increasing soil degradation and species loss. Soil carbon is newly refined at >30,000 Gt C (gigatonnes C), ten times above prior totals. Soil organic carbon (SOC) is up to 24,000 Gt C, plus plant stocks at ~2400 Gt C, both above- and below-ground, hold >99% of Earth’s biomass. On a topographic surface area of 25 Gha with mean 21 m depth, Soil has more organic carbon than all trees, seas, fossil fuels, or the Atmosphere combined. Soils are both the greatest biotic carbon store and the most active CO₂ source. Values are raised considerably. Disparity is due to lack of full soil depth survey, neglect of terrain, and other omissions. Herein, totals for mineral soils, Permafrost, and Peat (of all forms and ages), are determined to full depth (easily doubling shallow values), then raised for terrain that is ignored in all terrestrial models (doubling most values again), plus SOC in recalcitrant glomalin (+25%) and friable saprock (+26%). Additional factors include soil inorganic carbon (SIC some of biotic origin), aquatic sediments (SeOC), and dissolved fractions (DIC/DOC). Soil biota (e.g., forests, fungi, bacteria, and earthworms) are similarly upgraded. Primary productivity is confirmed at >220 Gt C/yr on land supported by Barrow’s “bounce” flux, C/O isotopes, glomalin, and Rubisco. Priority issues of species extinction, humic topsoil loss, and atmospheric CO₂ are remedied by SOC restoration and biomass recycling via (vermi-)compost for 100% organic husbandry under Permaculture principals, based upon the Scientific observation of Nature. Full article

Lake sediment records are of great importance for understanding the evolution of watershed environments. Various studies have been carried out to determine the depositional ages of lake sediments and to examine their physical, chemical, and biological characteristics. The aim is to construct the historical vegetation, environment, and climate patterns in Chinese lake watersheds. In this review, we obtained relevant studies on lake sediment records by searching the key word ‘age-depth’ from the following databases: Web of Science and the China National Knowledge Infrastructure (CNKI, the largest Chinese academic database). We analyzed the literature based on its type (published in a Chinese/English journal or as a Master’s/PhD thesis), period of publication, journal (if published in a journal), key authors, study area, dating scale, and main aims. The results suggest that the lakes in the plateau regions are the most popular research topic, typically covering 100–200 years (short-term) and 500–30,000 years (long-term). The literature focuses on a wide range of topics, from past environmental evolution in watersheds to lake ecology, and it provides a solid foundation for a better understanding of the regional climate change and the preservation of lake environments and ecosystems. In the future, the resulting data obtained from environmental reconstructions with lake sediments will need to be integrated with emerging information processing technologies (e.g., artificial intelligence and meta-analysis) to disentangle the complex interplay between the Earth’s surface processes and global climate change; furthermore, strengthening interdisciplinary collaboration will deepen our comprehension of the man-land relationship and promote the sustainable management of lake ecosystems in the context of global climate change. Full article

The spatial distribution of soil moisture is a critical determinant for the success of vegetation restoration initiatives in semi-arid and arid regions. The Qilian Mountains, situated within a semi-arid zone in China, have been subject to significant water-induced soil erosion, which has led to extensive restoration activities, predominantly utilizing the species P. crassifolia. However, the interconnections between soil moisture and various land cover types within this region remain unclear, presenting challenges to effective woodland rehabilitation. This study examines the surface soil moisture dynamics in afforested areas with varying ages of plantation to determine the influence of tree planting on the moisture content of the upper soil layer. It investigates the characteristics and temporal patterns of surface soil moisture as the age of the plantation increases. The findings indicate that: (1) soil moisture levels follow a descending sequence from natural forest, through shrubland and grassland, to planted forest and mixed forest, with statistically significant differences observed between natural and mixed forests (p < 0.05); (2) young afforested areas (less than 50 years old) have lower soil moisture levels compared to natural forests, shrublands, or grasslands, and the ecohydrological impacts of afforestation become apparent with a temporal delay; and (3) the analysis using Generalized Additive Mixed Models (GAMM) and the application of Kriging interpolation to determine the spatial distribution of soil moisture reveals that in semi-arid and arid regions, several factors have a pronounced a non-linear relationship with the moisture content of the surface soil. These factors include the duration of afforestation, the position on the lower slope, the presence of shade on the slope, and the scale at which the study is conducted. Therefore, a comprehensive understanding of the dynamics of soil water content is essential to prevent the potential failure of artificially established forests due to inadequate soil moisture in their later stages. Full article

One gravity core retrieved from the Niger Delta was used to explore the origin of deposited organic matter (OM) and the paleo-climatic and environmental conditions over the Holocene in equatorial West Africa. The geochemical properties of sediments including glycerol dialkyl glycerol tetraethers (GDGTs) and elemental (%OC, %N, C/N) and isotopic (δ¹³C_org, δ¹⁵N) signatures were determined. The determination constrained the age of the column and revealed that the sediment OM was mainly derived from a marine source. The isoprenoid (iso)GDGTs were the dominant GDGTs, with a small amount of branched (br)GDGTs, which led to a low-branched and isoprenoid tetraether index (BIT, 0.02–0.21) and represented a low terrestrial input. Most isoGDGTs and OH-GDGTs were produced in situ by Marine Group I (MG-I) Thaumarchaeota, while the brGDGTs were mainly transported from land. A two-endmember model quantified the contribution of terrestrial OM, as 0.9–19.9% by BIT and 1.1–32.6% by δ¹³C. Accordingly, the millennium-scale sea surface temperatures (SSTs) were reconstructed based on the cyclopentane ring distribution (${\mathrm{T}\mathrm{E}\mathrm{X}}_{86}^{\mathrm{H}}$) and the ring index of OH-GDGTs (RI-OH). The top core SSTs were lower than the modern mean annual SST due to the growth season and habitat depth of Thaumarchaeota. The reconstructed SSTs clearly revealed the four stages of paleoclimate change, in particular, the drought episode of 8.2 kyr and the following humid period. The above research has enhanced our understanding of the paleoclimate change in river outflow during the Holocene at the millennium scale. Full article

The identification and delineation, through aerial photography, of the archaeological structures that present temporal resolution, as well as their characterization based on high-resolution LiDAR (Light Detection and Ranging)-derived DEMs (Digital Elevation Models) are modern techniques widely used in the archaeological prospecting of various landscapes. In this study, we present an application of Airborne Laser Scanning (ALS) and aerial photography (AP) techniques, used in order to compute geomorphometric indices specific to the ashmound structures of Late Bronze Age (LBA) archaeological sites that are visible on the soil surface. The necessity of determining the ashmounds’ geoarchaeological description stems from the fact that despite the majority of archaeologists weighing in on the subject, there is still no accepted explanation regarding their initial functionality. Thus, we believe that the GIS-based high-resolution characterization of 200 ashmound features identified in 21 Noua Culture (NC) archaeological sites will contribute to a better understanding of the ashmounds’ functionality and evolution in the heterogeneous landscape of the study area (NE Romania). Therefore, various shape indices, such as the area (A), perimeter (P), length (L), form factor (RF), circularity ratio (RC), and elongation ratio (RE) were computed for microlevel characterizations of the visible ashmounds’ structures. Additionally, LiDAR-derived DEMs with a 0.5 m resolution were used to generate more surface characteristics such as the slope (S) and hypsometric indices (HI). The outcomes indicate that the ashmounds have relatively diverse shapes (an RF range from 0.37 to 0.77; a RC range from 0.79 to 0.99; a RE range from 0.68 to 0.99), and the micro-relief slightly varies from positive to negative landforms (HI range from 0.34 to 0.61) depending on the erosion intensity (S range from 1.17° to 19.69°) and anthropogenic impact (e.g., current land use and agriculture type). Furthermore, each morphometric parameter is an indicator for surface processes, aiding in the identification of the geomorphologic and surface-erosion aspects that affect the archaeological remains, contributing to the assessment of the conservation status of the ashmound structures within the current landscape configuration. In this regard, this article presents and discusses the remote sensing (RS) techniques used, as well as the morphometric data obtained, exploring the implications of our findings for a better characterization of the NC in Romania. Full article

The cementation mechanisms and processes of aggregate binding agents are important in understanding aggregate formation. However, the role of threshold values and the proportions of organic and inorganic binding agents in aggregate formation remain unclear. This research investigated the dominant aggregate binding agent dynamics in a sequence comprising buried ancient red soil unaffected by modern climate changes and human activities, alongside nearby exposed Quaternary ancient red soils subjected to different land use patterns influenced by these factors in northeastern China. By analyzing soil age, aggregate compositions, and organic/inorganic indicators of binding agents, including soil organic matter (SOM), free iron oxide (Fed), poorly crystalline iron oxide (Feo), crystalline iron oxide (Fed-Feo), and total clay particles (TCL), we determined the relative contributions of different binding agents using redundancy analysis (RDA). The results revealed that the buried ancient red soil did not contain dominant binding agents in the aggregate formation before 91.01 ka BP. Due to denudation, the buried ancient red soil was exposed at the surface and experienced the importation of soil organic matter, weathering of silicate-bound iron oxides, and crystallization of poorly crystalline iron oxides resulting from the effects of different land use patterns from 91.01 ka to the present. Under the influence of binding agent dynamics, dominant binding agents in the exposed Quaternary ancient red soils’ aggregate formation changed into SOM and Fed. When the C/(Fed-Feo) molar ratio was less than 2.13, Fed-Feo was the dominant aggregate binding agent. When the C/(Fed-Feo) molar ratio was greater than 2.13, SOM was the dominant aggregate binding agent. The results of this study improve our understanding of aggregate formation and the relationship between soil organic matter and iron oxides. Full article

Climate, human disturbances, and management practices jointly control the spatial and temporal patterns of land surface phenology. However, most studies solely focus on analyzing the climatic controls on the inter-annual variability and trends in vegetation phenology. Investigating the main and interacting effects of management practices and climate might be crucial in determining vegetation phenology and productivity. This study examined the impacts of climate and management practices on vegetation phenology and productivity in adjacent native and introduced prairie pastures, which have detailed long-term management records, by combining climate, management, and satellite remote sensing data (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat). Modeled gross primary production (GPP) using vegetation photosynthesis model (VPM) was also included to investigate the dynamics of productivity. When comparing the impacts of the same management practices on different pastures, we used paired comparison, namely, comparing the native and introduced prairies side by side in the same year. The interactions of management practices and climate were investigated through comparing years with similar management but different climate (e.g., years with rainfall or not following baling events) in the same pasture. Results showed that air temperature (Ta) was an important factor in determining the start of the season (SOS) and the length of the season (LOS). Total rainfall (RF) during the annual growing season (AGS, derived from vegetation indices (VIs)) had the largest explanatory power (R² = 0.53) in explaining the variations in the seasonal sums of VIs. The variations in GPP were better explained by RF (R² = 0.43) than Ta (R² = 0.14). Using the thermal growing season (March–October) or AGS climate factors did not show large differences in determining the relationships between phenology, GPP, and climate factors. Drought shortened the LOS and decreased GPP. In terms of management practices, grazing generally reduced the VIs and burning induced early greening-up and enhanced vegetation growth. Drought plus other management practices (e.g., grazing or baling) greatly affected vegetation phenology and suppressed GPP. The negative impacts (i.e., removal of biomass) of grazing on vegetation was compensated by enhanced vegetation growth after good RF. This study demonstrated that the interactions of climate and management practices could be positive (burning plus baling in a good RF year) or negative (grazing/baling plus drought), and can significantly affect vegetation phenology and production. Full article

Developing an agricultural drought monitoring index through integrating multiple input variables into a single index is vital to facilitate the decision-making process. This study aims to develop an agricultural drought index (agCDI) to monitor and characterize the spatial and temporal patterns of drought in Sri Lanka. Long-term (1982 to 2020) remote sensing and model-based agroclimatic input parameters—normalized difference vegetation index (NDVI), land surface temperature (LST), 3-month precipitation z-score (stdPCP), and evaporative demand drought index (EDDI)—were used to develop agCDI. The principal component analysis (PCA) approach was employed to qualitatively determine the grid-based percentage contribution of each input parameter. The agCDI was apparently evaluated using an independent dataset, including the crop yield for the major crop growing districts and observed streamflow-based surface runoff index (SRI) for the two main crop growing seasons locally, called Yala (April to September) and Maha (October to March), using 20-years of data (from 2000 to 2020). The results illustrate the good performance of agCDI, in terms of predominantly capturing and characterizing the historic drought conditions in the main agricultural producing districts both during the Yala and Maha seasons. There is a relatively higher chance of the occurrence of moderate to extreme droughts in the Yala season, compared to the Maha season. The result further depicts that relatively good correlation coefficient values (> 0.6) were obtained when agCDI was evaluated using a rice crop yield in the selected districts. Although the agCDI correlated well with SRI in some of the stations (>0.6), its performance was somehow underestimated in some of the stations, perhaps due to the time lag of the streamflow response to drought. In general, agCDI showed its good performance in capturing the spatial and temporal patterns of the historic drought and, hence, the model can be used to develop agricultural drought monitoring and an early warning system to mitigate the adverse impacts of drought in Sri Lanka. Full article

Global climate changes have a great impact on terrestrial ecosystems. Vegetation is an important component of ecosystems, and the impact of climate changes on ecosystems can be determined by studying vegetation phenology. Vegetation phenology refers to the phenomenon of periodic changes in plants, such as germination, flowering and defoliation, with the seasonal change of climate during the annual growth cycle, and it is considered to be one of the most efficient indicators to monitor climate changes. This study collected the global land surface satellite leaf area index (GLASS LAI) products, meteorological data sets and other auxiliary data in the Three-River headwaters region from 2001 to 2018; rebuilt the vegetation LAI annual growth curve by using the asymmetric Gaussian (A-G) fitting method and extracted the three vegetation phenological data (including Start of Growing Season (SOS), End of Growing Season (EOS) and Length of Growing Season (LOS)) by the maximum slope method. In addition, it also integrated Sen’s trend analysis method and the Mann-Kendall test method to explore the temporal and spatial variation trends of vegetation phenology and explored the relationship between vegetation phenology and meteorological factors through a partial correlation analysis and multiple linear regression models. The results of this study showed that: (1) the SOS of vegetation in the Three-River headwaters region is concentrated between the beginning and the end of May, with an interannual change rate of −0.14 d/a. The EOS of vegetation is concentrated between the beginning and the middle of October, with an interannual change rate of 0.02 d/a. The LOS of vegetation is concentrated between 4 and 5 months, with an interannual change rate of 0.21 d/a. (2) Through the comparison and verification with the vegetation phenological data observed at the stations, it was found that the precision of the vegetation phonology extracted by the A-G method and the maximum slope method based on GLASS LAI data is higher (MAE is 7.6 d, RMSE is 8.4 d) and slightly better than the vegetation phenological data (MAE is 9.9 d, RMSE is 10.9 d) extracted based on the moderate resolution imaging spectroradiometer normalized difference vegetation index (MODIS NDVI) product. (3) The correlation between the SOS of vegetation and the average temperature in March–May is the strongest. The SOS of vegetation is advanced by 1.97 days for every 1 °C increase in the average temperature in March–May; the correlation between the EOS of vegetation and the cumulative sunshine duration in August–October is the strongest. The EOS of vegetation is advanced by 0.07 days for every 10-h increase in the cumulative sunshine duration in August–October. Full article

To explore the impact of artificial shelterbelt construction with saline irrigation on the soil water characteristic curve (SWCC) of shifting sandy soil in extreme arid desert areas, three treatments including under the shelterbelt (US), bare land in the shelterbelt (BL) and shifting sandy land (CK) in the hinterland of the Taklimakan Desert were selected. The age of the shelterbelt is 16, and the vegetation cover is mainly Calligonum mongolicum. The soils from different depths of 0–30 cm were taken keeping in view the objective of the study. The SWCCs were determined by the centrifugal method and fitting was performed using various models such as the Gardner (G) model, Brooks–Corey (BC) model and Van Genuchten (VG) model. Then, the most suitable SWCC model was selected. The results showed that electrical conductivity (EC) and organic matter content of BL and US decreased with the increasing soil depth, while the EC and organic matter content of CK increased with the soil depth. The changes in soil bulk density, EC and organic matter of 0–5 cm soil were mostly significant (p < 0.05) for different treatments, and the differences in SWCCs were also significant among different treatments. Moreover, the construction of an artificial shelterbelt improved soil water-holding capacity and had the most significant impacts on the surface soil. The increase in soil water-holding capacity decreased with increasing soil depth, and the available soil water existed in the form of readily available water. The BC model and VG model were found to be better than the G model in fitting results, and the BC model had the best fitting result on CK, while the VG Model had the best fitting result on BL with higher organic matter and salt contents. Comparing the fitting results of the three models, we concluded that although the fitting accuracy of the VG model tended to decrease with increasing organic matter and salinity, the VG model had the highest fitting accuracy when comparing with BC and G models for the BL treatment with high organic matter and salinity. Therefore, the influence of organic matter and salinity should be considered when establishing soil water transfer function. Full article

Athletic taping is widely used in sports to prevent injury. However, the effect of anterior cruciate ligament (ACL) protective taping on neuromuscular control during dynamic tasks remains unclear. Therefore, this study aimed to investigate the immediate effect of ACL protective taping on landing mechanics and muscle activations during side hops in healthy individuals. Fifteen healthy individuals (11 males and 4 females; age, 23.1 ± 1.4 years; height, 175.1 ± 10.4 cm; weight, 66.3 ± 11.2 kg) volunteered to participate in this study. Landing mechanics and muscle activations were measured while each participant performed single-leg hops side-to-side for ten repetitions with and without taping. An optical motion capture system and two force plates were used to collect the kinematic and kinetic data during the side hops. Surface electromyogram recordings were performed using a wireless electromyography system. Paired t-tests were performed to determine the differences in landing mechanics and muscle activations between the two conditions (taping and non-taping). The level of significance was set at p < 0.05. Compared with the non-taping condition, participants landed with a smaller knee abduction angle, greater knee external rotation angle, and smaller knee extensor moment in the taping condition. Given that greater knee abduction, internal rotation, and knee extension moment are associated with a greater risk of ACL injury, our findings suggest that ACL protective taping can have an immediate effect on dynamic knee stability. Clinicians should consider using ACL protective taping to facilitate the use of favorable landing mechanics for ACL injuries. Full article

The high mountains stretch over 20.4% of Nepal’s land surface with diverse climatic conditions and associated vegetation types. An understanding of tree species and forest structural pattern variations across different climatic regions is crucial for mountain ecology. This study strived to carry out a comparative evaluation of species diversity, main stand variables, and canopy cover of forests with contrasting precipitation conditions in the Annapurna range. Firstly, climate data provided by CHELSA version 1.2, were used to identify distinct precipitation regimes. Lamjung and Mustang were selected as two contrasting precipitation regions, and have average annual precipitation of 2965 mm and 723 mm, respectively. Stratified random sampling was used to study 16 plots, each measuring 500 m² and near the tree line at an elevation range of 3000 to 4000 m across different precipitation conditions. In total, 870 trees were identified and measured. Five hemispherical photos using a fisheye lens were taken in each plot for recording and analyzing canopy cover. Margalef’s index was used to measure species richness, while two diversity indices: the Shannon–Wiener Index and Simpson Index were used for species diversity. Dominant tree species in both study regions were identified through the Important Value Index (IVI). The Wilcoxon rank-sum test was employed to determine the differences in forest structure and composition variables between the two precipitation regimes. In total, 13 species were recorded with broadleaved species predominating in the high precipitation region and coniferous species in the low precipitation region. Higher species richness and species diversity were recorded in the low precipitation region, whereas the main stand variables: basal area and stem density were found to be higher in the high precipitation region. Overall, an inverse J-shaped diameter distribution was found in both precipitation regions signifying uneven-aged forest. A higher proportion of leaning and buttressed trees were recorded in the high precipitation region. However, similar forest canopy cover conditions (>90%) were observed in both study regions. The findings of this research provide a comprehensive narrative of tree species and forest structure across distinct precipitation regimes, which can be crucial to administrators and local people for the sustainable management of resources in this complex region. Full article