Search Results (314)

Salinization hinders the restoration of vegetation in salt-affected soils by negatively impacting plant growth and development. Halophytes play a key role in the restoration of saline and degraded lands due to unique features explaining their growth aptitude in such extreme ecosystems. Suaeda fruticosa is an euhalophyte well known for its medicinal properties and its potential for saline soil phytoremediation. However, excessive salt accumulation in soil limits the development of this species. Research findings increasingly advocate the use of extremophile rhizosphere bacteria as an effective approach to reclaim salinized soils, in conjunction with their salt-alleviating effect on plants. Here, a pot experiment was conducted to assess the role of a halotolerant plant growth-promoting actinobacterium, Glutamicibacter sp., on the growth, nutritional status, and shoot content of proline, total soluble carbohydrates, and phenolic compounds in the halophyte S. fruticosa grown for 60 d under high salinity (600 mM NaCl). Results showed that inoculation with Glutamicibacter sp. significantly promoted the growth of inoculated plants under stress conditions. More specifically, bacterial inoculation increased the shoot concentration of proline, total polyphenols, potassium (K⁺), nitrogen (N), and K⁺/Na⁺ ratio in shoots, while significantly decreasing Na⁺ concentrations. These mechanisms partly explain S. fruticosa tolerance to high saline concentrations. Our findings provide some mechanistic elements at the ecophysiological level, enabling a better understanding of the crucial role of plant growth-promoting rhizobacteria (PGPRs) in enhancing halophyte growth and highlight their potential for utilization in restoring vegetation in salt-affected soils. Full article

In the process of the work of a coal power station is formed ash and slag, which, along with process water, are deposited in the dumps. Coal ash waste dumps significantly degrade the surrounding environment due to their unprotected surfaces, which are highly susceptible to wind and water erosion. This results in the dispersion of contaminants into adjacent ecosystems. Pollutants migrate into terrestrial and aquatic systems, compromising soil quality and water resources, and posing documented risks to the environment and human health. Primary succession on the coal ash dumps of the Apatity thermal power plant (Murmansk Region, NW Russia) was initiated by cyanobacterial colonization. We studied cyanobacterial communities inhabiting three spoil sites that varied in time since decommissioning. These sites are characterized by exceptionally high concentrations of calcium and magnesium oxides—levels approximately double those found in the region’s natural soils. A total of 18 cyanobacterial taxa were identified in disposal sites. Morphological analysis of visible surface crusts revealed 16 distinct species. Furthermore, 24 cyanobacterial strains representing 11 species were successfully isolated into unialgal culture and tested with a molecular genetic approach to confirm their identification from 16S rRNA. Three species were determined with molecular evidence. Cyanobacterial colonization of coal fly ash disposal sites begins immediately after deposition. Primary communities initially exhibit low species diversity (four taxa) and do not form a continuous ground cover in the early years. However, as succession progresses—illustrated by observations from a 30-year-old deposit—spontaneous surface revegetation occurs, accompanied by a marked increase in cyanobacterial diversity, reaching 12 species. Full article

Reclaimed fields have a low soil fertility and low productivity compared to conventional arable land, necessitating research on productivity enhancement. The rice–frog co-culture model is an ecologically intensive practice that combines biodiversity objectives with agricultural production needs, offering high ecological and economic value. However, there is a lack of research on this model that has focused on factors other than soil nutrient levels. The present study evaluated the rice–frog co-culture model in a reclaimed paddy field across three experimental plots with varying frog stocking densities: a rice monoculture (CG), low-density co-culture (LRF), and high-density co-culture (HRF). We investigated the effects of the frog density on greenhouse gas emissions throughout the rice growth. The rice–frog co-culture model significantly reduced methane (CH₄) emissions, with fluxes highest in the CG plot, followed by the LRF and then HRF plots. This reduction was achieved by altering the soil pH, the cation exchange capacity, the mcrA gene abundance, and the mcrA/pmoA gene abundance ratio. However, there was a contrasting nitrous oxide (N₂O) emission pattern. The co-culture model actually increased N₂O emissions, with fluxes being highest in the HRF plots, followed by the LRF and then CG plots. The correlation analysis identified the soil nosZ gene abundance, redox potential, urease activity, nirS gene abundance, and ratio of the combined nirK and nirS abundance to the nosZ abundance as key factors associated with N₂O emissions. While the co-cultivation model increased N₂O emissions, it also significantly reduced CH₄ emissions. Overall, the rice–frog co-culture model, especially at a high density, offers a favorable sustainable agricultural production model. Full article

Reclaiming coastal wetlands for agricultural purposes has led to intensified farming activities, which are anticipated to affect greenhouse gas (GHG) flux processes within coastal wetland ecosystems. However, how greenhouse gas exchanges respond to variations in agricultural reclamation activities across different years remains uncertain. To address this knowledge gap, this study characterized dynamic exchanges within the soil–plant–atmosphere continuum by employing continuous monitoring across four representative coastal wetland soil–vegetation systems in Jiangsu, China. The results show the carbon dioxide (CO₂) and nitrous oxide (N₂O) flux exchanges between the system and the atmosphere and soil–vegetation carbon pools, which revealed the drivers of carbon dynamics in the coastal wetland system. The four study sites, converted from coastal wetlands to agricultural lands at different times (years), generally act as CO₂ sinks and N₂O sources. Higher levels of CO₂ sequestration occur as the age of reclamation rises. In terms of time scale, crops lands were found to be CO₂ sinks during the growing period but became CO₂ sources during the crop fallow period. Although the temporal trend of the N₂O flux was generally smooth, reclaimed farmlands acted as net sources of N₂O, particularly during the crop-growing period. The RDA and PLS-PM models illustrate that soil salinity, acidity, and hydrothermal conditions were the key drivers affecting the magnitude of the GHG flux exchanges under reclamation. This study demonstrates that GHG emissions from reclaimed wetlands can be effectively regulated through science-based land management, calling for prioritized attention to post-development practices rather than blanket restrictions on coastal exploitation. Full article

Remotely sensed cropland abandonment monitoring is crucial for providing spatially explicit references for maintaining sustainable agricultural practices and ensuring food security. However, abandoned cropland is commonly detected based on multi-date classification or the dynamics of a single vegetation index, with the interactions between vegetation and soil time series often being neglected, leading to a failure to understand its full-life-cycle succession processes. To fill this gap, we propose a new full-life-cycle modeling framework based on the interactive trajectories of vegetation–soil-related endmembers to identify abandoned and reclaimed cropland in Jinan from 2000 to 2022. In this framework, highly accurate annual fractional vegetation- and soil-related endmember time series are generated for Jinan City for the 2000–2022 period using spectral mixture models. These are then used to integrally reconstruct temporal trajectories for complex scenarios (e.g., abandonment, weed invasion, reclamation, and fallow) using logistic and double-logistic models. The parameters of the optimization model (fitting type, change magnitude, start timing, and change duration) are subsequently integrated to develop a rule-based hierarchical identification scheme for cropland abandonment based on these complex scenarios. After applying this scheme, we observed a significant decline in green vegetation (a slope of −0.40% per year) and an increase in the soil fraction (a rate of 0.53% per year). These pathways are mostly linked to a duration between 8 and 15 years, with the beginning of the change trend around 2010. Finally, the results show that our framework can effectively separate abandoned cropland from reclamation dynamics and other classes with satisfactory precision, as indicated by an overall accuracy of 86.02%. Compared to the traditional yearly land cover-based approach (with an overall accuracy of 77.39%), this algorithm can overcome the propagation of classification errors (with product accuracy from 74.47% to 85.11%), especially in terms of improving the ability to capture changes at finer spatial scales. Furthermore, it also provides a better understanding of the whole abandonment process under the influence of multi-factor interactions in the context of specific climatic backgrounds and human disturbances, thus helping to inform adaptive abandonment management and sustainable agricultural policies. Full article

The aim of this study was to observe soil erosion by wind, depending on the soil physical properties, climatic conditions, and plant canopy, for three representative soil series in the reclaimed tidal flats. Soil samples were collected from the Ap horizon of three soil series to analyze soil physical properties and particle distribution. Precipitation and wind velocities were measured by the weather station installed at the filed. The particle distribution curves showed that the actual proportions of erodible soil particle were in the order of 74.7%(TH), 66.1%(PS), and 62%(JB). The instantaneous and daily maximum wind speeds exceeded the threshold friction velocity (5.78 m s⁻¹) suggested by Chepil. However, the dynamic velocities, depending on the radius of 0.125 mm and 0.42 mm belonging to erodible particle size, were much lower than the threshold friction velocity suggested by Chepil. The wind profile increases logarithmically with height, just above the plant canopy. The vertical gradients of wind velocity for the winter wheat plot were smaller than that of the bare plot due to the relatively rough canopy, and U(Z)c of the bare plot was slightly higher than that of the winter wheat plot with a plant canopy for the given U(Z)m. Conclusively, the actual proportion of erodible particles was much less than that of the particle size limit. Full article

The emergence of Lamanite Studies exemplifies the need for decolonial and Indigenous-centered reevaluations of Mormon–Indigenous relations. This article advocates for the reclamation of Indigenous identity independent of the constraints imposed by Mormon doctrine. The incorporation of Indigenous genealogies into Mormon theology results in epistemic violence, disconnecting Indigenous peoples from their ancestral identities and substituting the latter with the settler/invader colonial construct of “Lamanite”. This paper advocates for the decolonization of Indigenous identities within Mormonism, emphasizing the need for a radical intervention that prioritizes Indigenous sovereignty and self-definition over the maintenance of colonial categories. I present approaches and scholarship in Lamanite Studies that align with Indigenous land and spiritual repatriation, promoting the restoration of Indigenous epistemologies to Indigenous communities. Theoretical colonialism must be supplemented by grassroots initiatives that empower Indigenous communities to reclaim their spiritual and cultural identities. Full article

Coal mines play an important role in the global energy supply. Monitoring the displacement of open-pit mines is crucial to preventing geological disasters, such as landslides and surface displacement, caused by high-intensity mining activities. In recent years, multi-temporal Synthetic Aperture Radar Interferometry (InSAR) technology has advanced and become widely used for monitoring the displacement of open-pit mines. However, the scattering characteristics of surfaces in open-pit mining areas are unstable, resulting in few coherence points with uneven distribution. Small BAseline Subset InSAR (SABS-InSAR) technology struggles to extract high-density points and fails to capture the overall displacement trend of the monitoring area. To address these challenges, this study focused on the Shengli West No. 2 open-pit coal mine in eastern Inner Mongolia, China, using 201 Sentinel-1 images collected from 20 May 2017 to 13 April 2024. We applied both SBAS-InSAR and distributed scatterer InSAR (DS-InSAR) methods to investigate the surface displacement and long-term behavior of the open-pit coal mine over the past seven years. The relationship between this displacement and mining activities was analyzed. The results indicate significant land subsidence was observed in reclaimed areas, with rates exceeding 281.2 mm/y. The compaction process of waste materials was the main contributor to land subsidence. Land uplift or horizontal displacement was observed over the areas near the active working parts of the mines. Compared to SBAS-InSAR, DS-InSAR was shown to more effectively capture the spatiotemporal distribution of surface displacement in open-pit coal mines, offering more intuitive, comprehensive, and high-precision monitoring of open-pit coal mines. Full article

As the area of land being reclaimed for cotton cultivation in the inland cotton region of Northwest China continues to expand, new requirements for variety selection and promotion have emerged. Therefore, research on the effects of cotton varieties and the environment is becoming increasingly essential. This study focuses on the role of variety and site factors in cotton production, specifically examining the impact of these factors on lint, seed cotton, and lint percentage. The research extends the application of the allometry allocation model by analyzing long-term experimental data from ecological network sites and national regional trials of cotton varieties. The results indicated that between 2012 and 2018, the average seed cotton yield in the regional trials in the inland northwest cotton region ranged from 44,667.8 kg/ha to 5462.7 kg/ha, while lint yield ranged from 2044.4 kg/ha to 2261.5 kg/ha. The fluctuations in seed cotton and lint yields were not consistent. Using the GGE model to evaluate the zoning of sites, it was found that cotton performance in the inland northwest cotton region showed considerable variation between subzones, with most sites exhibiting significant differentiation across years or indicators. At the site scale, lint yield and seed weight generally aligned with the allometry distribution model. For example, the allometry distribution index fluctuated year-to-year in sites like Shihezi, Tahe, and Aksu, while interannual fluctuations were smaller at sites like Kuqa and Shache. The results from the GGE model analysis of lint percentage differentiation were consistent with the allometry distribution index. These findings suggest that the allometry distribution model can effectively assess interannual variations in varietal differences across sites. These research findings provide a theoretical foundation for future crop variety selection, habitat selection, and variety structure development in the inland cotton region of Northwest China and similar regions. Full article

Alley cropping, an agroforestry system that integrates trees and arable crops, holds the potential to improve both crop yields and soil health. It has been found to be effective for upland crops in many countries of the world. However, the utilization of alley cropping to improve soil health in the terrace ecosystem of Bangladesh is poorly understood. Therefore, this study was undertaken to assess the changes in soil biochemical properties and quantify the cabbage yield under three alley widths of Leucaena leucocephala (3.0, 4.5, and 6.0 m size) and five nitrogen (N) levels [0, 40, 80, 120, and 160 kg N ha⁻¹ (0, 25, 50, 75, and 100% of recommended N rates, respectively) with the addition of pruned materials of L. leucocephala (Ipil-ipil)]. The field experiment was conducted following a split-plot design, where alley width was considered as the main-plot factor and N rate as the sub-plot factor. Within each main plot, the five N rates were replicated thrice. Control plots with similar N doses were applied accordingly without addition of pruned materials to compare the results with alley cropping. Data were collected on the biochemical properties of the soil [soil pH, organic carbon (C), total N, available phosphorus (P), exchangeable potassium (K), microbial biomass C, and biomass N] and the yield of cabbage quantified [edible head weight (kg plant⁻¹) and head yield (t ha⁻¹)] under different alley widths and control. Findings revealed that organic C, total N, available P, exchangeable K, microbial biomass C, and biomass N in the topsoil exhibited maximum values in the L. leucocephala-based alley plot, which is proved to be a possible solution of restoration of degradable land. Additionally, L. leucocephala-based alley cropping improved the soil pH, indicating a potential avenue for more-sustainable land management practices. Results also showed that alley widths and N rates have significant effects on cabbage (Brassica oleracea L. var. capitata) yield. Alley width of 6.0 m along with 100% N provided the highest cabbage yield followed by 75% N in 6.0 m alley, and the control with 100%. The wider alley minimizes tree–crop competition, allowing for optimal cabbage production. These aforementioned results suggest that alley cropping with L. leucocephala is a promising approach to enhance soil fertility and crop productivity in the terrace ecosystem of Bangladesh. Full article

Settlement issues at airports pose a significant threat to operational safety, particularly in coastal regions, where land reclamation introduces unique challenges. The complexities of marine foundations, the difficulties in investigating reclaimed land, and the heightened risks of excessive settlement require timely and accurate monitoring and prediction to effectively identify risks and minimize unnecessary maintenance costs. To address these challenges, this study introduces a dynamic prediction model based on grey system theory, enhanced by a variable-size sliding window mechanism that continuously integrates the latest monitoring data. Validation using datasets from Kansai International Airport and Xiamen Xiang’an International Airport demonstrates that the model improves prediction accuracy by over 20% compared to existing models. Additionally, an exponential forecasting mechanism for long-term settlement prediction is developed and verified with data from Pudong International Airport. The proposed model demonstrates robust predictive capabilities across both long-term and short-term forecasting scenarios. Full article

Over the centuries, the reclamation of marshy areas has significantly transformed the Italian rural landscape. The Piana di Sibari (North of Calabria) represents a paradigmatic case of this process, because the current landscape is the result of a vast rural transformation. This paper discusses the results of a survey conducted to evaluate students’ knowledge and perception of this “Reclaim Lands” landscape, focusing on their emotional connection and awareness of its cultural and environmental heritage. The survey was administered to 149 middle school and 177 high school students. The study aims to investigate awareness and perception of landscape among mid-to-late adolescents living in the Piana di Sibari, highlighting the key aspects of the relationship between students and the places they inhabit, recognizing the catalytic role of the landscape in fostering a sense of belonging and identity. The results of this survey encourage reflection on a cultural shift that integrates ecological, social, and cultural perspectives, aligned with the European Landscape Convention, advocating for greater investment in youth education and participation to promote active citizenship and chart a course toward a fairer and more sustainable society. Full article

Assessing water demand is essential for urban planning, aligning with socio-economic and climatic needs. The territorial water footprint identifies water requirements across sectors and detects sources of consumption. This aids in mitigating impacts and evaluating alternative water sources like reclaimed water. In Gavà, water impacts were assessed for residential, commercial, municipal, tourism, industrial, agricultural, and livestock sectors. The total water footprint is 6,458,118 m³, comprising 3,293,589 m³ from blue water, 2,250,849 m³ from green water, and 913,680 m³ from grey water. Agriculture (54.2%), residential (30.9%), and industrial activities (5.8%) are the main water footprint contributors. A key methodological advancement of this study is the refinement of grey water footprint calculations for livestock facilities within the RWF framework, allowing for a more precise assessment of their environmental impact. Integrating geographic information systems with land use mapping helps localize impacts, detect hotspots, and identify infrastructure improvement opportunities. Full article

Coastal areas are highly dynamic regions where surface deformation due to natural and anthropogenic activities poses significant challenges. Synthetic Aperture Radar (SAR) interferometry techniques, such as Persistent Scatterer Interferometry (PSInSAR), provide advanced capabilities to monitor surface deformation with high precision. This study applies PSInSAR techniques to estimate surface deformation along coastal zones from 2017 to 2020 using Sentinel-1 data. In the densely populated areas of Pasni, an annual subsidence rate of 130 mm is observed, while the northern, less populated region experiences an uplift of 70 mm per year. Seawater intrusion is an emerging issue causing surface deformation in Pasni’s coastal areas. It infiltrates freshwater aquifers, primarily due to excessive groundwater extraction and rising sea levels. Over time, seawater intrusion destabilizes the underlying soil and rock structures, leading to subsidence or gradual sinking of the ground surface. This form of surface deformation poses significant risks to infrastructure, agriculture, and the local ecosystem. Land deformation varies along the study area’s coastline. The eastern region, which is highly reclaimed, is particularly affected by erosion. The results derived from Sentinel-1 SAR data indicate significant subsidence in major urban districts. This information is crucial for coastal management, hazard assessment, and planning sustainable development in the region. Full article

The compression index (C_c) is a critical soil parameter that is used to estimate the consolidation settlement of ground. In this study, the compression index, typically obtained through consolidation tests, was predicted using machine learning techniques after preprocessing data that considered the geotechnical and hydrogeological characteristics of the study area. This approach enabled an analysis of how geotechnical and hydrogeological characteristics affect the performance of machine learning models. Data obtained from geotechnical investigations were used to train models for each classified zone. Suitable models were then selected to predict the compression index, and their performance was evaluated. Predictions that considered the geotechnical and hydrogeological characteristics showed improved accuracy in zones influenced by a single water system or zones near the coast. However, in offshore areas with complex water systems, using the entire dataset proved to be more effective. Differences in the clay mineral of the soil also affected the prediction accuracy, indicating a correlation between clay mineral properties and model performance. These findings suggest that classifying data based on geotechnical and hydrogeological characteristics is necessary when developing compression index prediction models to achieve relatively stable results. Full article