Changes In Land Use Types Research Articles

Evolution of karst rocky desertification and its response to land use changes in different geomorphologic environments

Studying the evolution of karst rocky desertification (KRD) in control areas of diverse geomorphologic types and its correlation with land use provides valuable insights for identifying priority areas and implementing effective treatment measures. Employing Remote Sensing (RS) and GIS, this research quantitatively examines the evolution of KRD and its relationship with land use in the karst mountain and gorge areas of Guizhou Province over the period 2010 to 2020. The findings reveal continuous improvement in KRD across the study areas, albeit with noticeable regional disparities. Notably, the karst mountain region exhibited significantly higher change areas and rates of KRD, non-KRD, light KRD, and moderate KRD compared to the gorge area, underscoring better desertification control in the former region. A discernible correlation emerges between different karst geomorphologic types, the distribution and changes in land use types, and the evolution of KRD. Land use change emerges as a pivotal factor influencing the improvement of KRD in these areas. Changes in land use patterns corresponded with a decrease in KRD in dry land, other woodland, grassland, and bare land across both regions. However, the response of KRD to land use patterns varied across control areas with different geomorphologic environments, resulting in geographical differentiation in KRD evolution. Key land use conversions, notably from shrubland to forestland and dry land to garden land in the gorge, and shrubland to forestland in the mountain, contributed significantly to KRD dynamics in these regions. Notably, in the gorge area, KRD primarily occurred in garden land, other woodland, dry land, and grassland. In contrast, in the mountain area, KRD was prevalent in shrubland, dry land, and grassland, highlighting distinct responses and contributions to its evolution. The study observes substantial land use change in KRD-improved areas, particularly in the gorge region. Notably, the responsiveness of KRD to woodland conversions (shrubland, forestland, other woodland) varied across different geomorphologic environments. The dynamics of rocky desertification occurrence (RDO) and the occurrence structure of KRD in various land use types exhibited significant differences between the two regions. The gorge area demonstrated generally higher RDO, with a relatively stable and simpler occurrence structure of KRD compared to the more dynamic and varied structure observed in the mountain area. The sequencing of KRD occurrence in both areas displayed stability in specific land use types, with varying intensities noted between them.

Effects of Different Land Use Types on Surface Temperature in the Northwest Arid Zone

This study analyzed the spatial and temporal characteristics of surface temperature in Uttarakhand Banner, and explored the correlation between land use types and surface temperature. The results show that the surface temperature of Urumqi Banner is greatly influenced by the change of land use types, and the difference of surface temperature between different land use types is obvious; the spatial and temporal trend of surface temperature in Urumqi Banner is different from the trend of gradual warming of the global climate change, which is mainly due to the change of the land use types by human activities.

Impacts of Land Use Conversion on Soil Erosion in the Urban Agglomeration on the Northern Slopes of the Tianshan Mountains

The serious problem of soil erosion not only has a profound impact on people’s lives but also results in a series of ecological and environmental challenges. To determine the impact of changes in land use type on soil erosion in the urban agglomeration on the northern slopes of the Tianshan Mountains, this study commences by employing the InVEST-SDR (integrated valuation of ecosystem services and tradeoffs–sediment delivery ratio) model to calculate soil erosion levels spanning from 2000 to 2020. Subsequently, it forecasts land use and land cover (LULC) conditions for the year 2030 under three scenarios: Q1 (natural development), Q2 (ecological protection), and Q3 (economic priority). This projection is accomplished through the integration of a coupled Markov chain and multi-objective planning model (MOP) alongside patch-generating land use simulation (PLUS) models. Ultimately, based on these outcomes, the study predicts soil erosion levels for the year 2030. There has been a consistent decline in soil erosion from 2000 to 2020 with high-intensity erosion concentrated in the Tianshan Mountain region. Grasslands, glaciers, and permafrost are identified as the most erosion-prone land types in the study area, with forests exhibiting the highest capacity for soil retention. Converting from grassland and barren land to forest within the same area results in a substantial reduction in soil erosion, specifically by 27.3% and 46.3%, respectively. Furthermore, the transformation from barren land to grassland also leads to a noteworthy 19% decrease in soil erosion. Over the past two decades, the study area has witnessed a significant decline in the area of grasslands, with a notable shift towards barren and impervious surfaces due to economic development and mining activities. The three predicted scenarios depict significant expansion towards barren land, grassland, and impervious area, respectively. Soil erosion decreases under different shared socio-economic pathway (SSP) scenarios relative to 2020. There is an increase in soil erosion in the Q1 scenario and in the Q3 scenario, whereas the amount of soil erosion in the Q2 scenario exhibits a continued decrease when only the effect of land change on soil erosion is considered. Persistently rapid economic development can exacerbate soil erosion problems, underscoring the need to find a balance between economic growth and ecological conservation. As economic expansion slows down, greater emphasis should be placed on environmental protection to maintain ecological stability.

Landscape Ecological Risk Assessment of Saihanba under the Change in Forest Landscape Pattern

Examining the Saihanba Mechanical Forest Farm, this study utilized Landsat remote sensing data from 1987, 1997, 2001, 2013, and 2020 to interpret land use from the Support Vector Machine (SVM) method, and to decipher evolving land use patterns over the last four decades. Grounded in landscape ecology theory, an innovative evaluation index for landscape ecological risk was introduced, leading to the delineation of 382 ecological risk evaluation units. Employing landscape pattern indices and a method of spatial autocorrelation, we analyzed the spatial and temporal distribution characteristics and spatial correlation patterns of landscape ecological risk across five distinct periods. Geostatistical approaches were used to explore the driving factors of landscape risk. The results indicate that since 1987, there have been significant changes in land use types, especially in forest landscapes, their proportion increasing from 23.19% to 74.55%. In 1987, the proportion of high-risk areas was 72.30%, but in 2020, high-risk areas had significantly decreased and clustered in specific locations. The landscape ecological risks in each period of the study area showed a positive spatial correlation and tended to gather in space. After comprehensive exploration using a geographic detector, we found that landscape type, temperature, and vegetation coverage are the main risk factors. Among them, landscape type has the greatest impact on the landscape and works together with slope, aspect, and precipitation. In forest farm management, only the adaptation and adjustment of single factors are often paid attention to, while the compound effects of multiple factors are ignored. The results of this study bring important reference value to the operation and development of forest farms.

Multi-Scenario Simulation and Eco-Environmental Effects Analysis of Land Use/Cover Change in China by an Integrated Cellular Automata and Markov Model

Land use transitions play a critical role in ecological environmental restoration, but they are also plagued by ecological environmental problems caused by excessive land resource development. In this study, we propose a methodological framework for unveiling the nexus profile of land use/cover change (LUCC) and eco-environmental effects. This study explored the spatiotemporal evolution patterns of LUCC over a long time series based on high-precision land use data from 1990 to 2020. Then, the ecological values (EVs) of various cities were calculated to obtain the ecological contribution rate of different land use types in the process of change. Finally, the future development trends of land use and ecological environmental quality were predicted under multiple scenarios using the cellular automata–Markov model, and scientific policy recommendations were proposed. The results showed that the expansion trajectory of the construction land in the urban agglomeration mainly expanded inwards along the mouth of the Pearl River, and the conversion of cultivated land to construction land was the most significant type of land use change. The overall ecological environmental quality of the study area showed a downwards trend, with Shenzhen exhibiting the largest decrease in EVs. Cultivated land contributed significantly to improving regional ecological environmental quality, while the land use transition types with relatively large contributions to environmental quality deterioration were conversions to construction land. Under the scenario of coordinated protection, the degree of cultivated land area reduction was significantly reduced, and the area of forestland showed a positive growth trend, with the expansion trend of construction land being reversed. These research findings can enrich the theoretical research on the sustainable development of urban agglomerations and provide reliable data support for policy-making.

Comprehensive analysis of land use and cover dynamics in djibouti using machine learning technique: A multi-temporal assessment from 1990 to 2023

Understanding land use and land cover (LULC) dynamics in semi-arid regions is vital for unraveling complex environmental processes and resource management. This study delves into the intricate interplay of land patterns and resource dynamics, offering indispensable insights into the environmental repercussions of these changes. The study aims to quantify land use categories in Djibouti's semi-desert region using remote sensing. It analyzes temporal changes and evaluates Random Forest (RF) algorithms for land use classification. Through meticulous quantification and comprehensive temporal analysis, the research contributes significantly to remote sensing and environmental science by enhancing understanding of land use dynamics and informing sustainable land management practices. Leveraging machine learning supervised classification on the Google Earth Engine (GEE) platform using Landsat data spanning four time periods (1990, 2002, 2012, and 2023), alongside spectral indices and Digital Elevation Model (DEM) data, our study achieves unprecedented insights. Our findings reveal a significant landscape transformation, delineating seven major land cover classes: mangroves, bushes, farmland, built-up areas, water bodies, barren land, and salt plains. With overall accuracy ranging from 89 % to 95 %, our assessments demonstrate significant changes in land use types over the studied period. Notably, mangroves, bushes, farmland, and salt areas witnessed declines, while built-up areas, water bodies, and barren lands expanded. This research underscores the pivotal role of remote sensing in monitoring long-term land use changes and their ecological impacts. By harnessing technological advancements, our study empowers stakeholders to make informed decisions for sustainable resource management and environmental conservation in semi-arid landscapes.

QGIS-based modeling and analysis of urban dynamics affecting land surface temperature towards climate hazards in coastal zones of Portugal

Climate risk creates considerable concern due to the density of natural and socio-economic assets in coastal areas. Monitoring land use/cover changes, detecting population growth, and analyzing their impact on land surface temperature (LST) are necessary for effective urban management. In this study, land use/land cover (LULC), population, and LST changes in coastal regions of Portugal. Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery was examined using World Bank population and CORINE data. Changes in land use types and LST values from 1990 to 2018 were analyzed. At the same time, LULC predictions were made using the Modules for Land Use Change Simulation (MOLUSCE) plug-in included in the QGIS software, and population projections were analyzed with LULC predictions in 2046. The results show the significant impact of land use on temperatures. It has been demonstrated that green and water areas can effectively cool cities. In the LULC changes between 1990 and 2018, the Leiria region stands out, with an annual increase of 4.04% in built areas from 121.58 to 259.06 km2. According to the simulations between 2018 and 2046, it was predicted that 18.74% of agricultural areas and 14.43% of forest areas would be transformed into built environments. The study is also essential as it confirms that the MOLUSCE plug-in can be effectively applied to land cover simulation on a large regional scale.

Impacts of land use changes on discharge and water quality in rivers and streams: Case study of the continental United States

AbstractWater quality trends in streams and rivers are impacted by several factors including land use of the watershed; however, it is unclear what influence changes in the land use of a watershed subsequently have on changes in discharge and water quality in streams and rivers. This study seeks to fill this gap by evaluating the relationship between changes in land use and changes in discharge and water quality at United States Geological Survey (USGS) stream gages over the period of 2008–2016. Using land cover data and discharge and water quality data from 60 USGS gages, regression methods were applied to determine the strength of relationship between land use changes and changes in water quality and quantity. Trends in discharge and water quality were mixed, with a majority of watersheds demonstrating a decrease in dissolved oxygen and turbidity, no overall trend for discharge, and increases in specific conductance. A regression analysis revealed that discharge, turbidity, and specific conductance were correlated with changes in individual land use types with an R2 between 0.12 and 0.25. Combining the influences of multiple land uses in multivariate regression improved the predictions for discharge (R2 0.58) and specific conductance (R2 0.47), highlighting the magnitude for which land cover changes influence trends in water quality. Overall, this study demonstrates the impact that large‐scale land use changes have on surface water quality.

Rice straw increases microbial nitrogen fixation, bacterial and nifH genes abundance with the change of land use types.

Soil microorganisms play an important role in soil ecosystems as the main decomposers of carbon and nitrogen. They have an indispensable impact on soil health, and any alterations in the levels of organic carbon and inorganic nitrogen can significantly affect soil chemical properties and microbial community composition. Previous studies have focused on the effects of carbon and nitrogen addition on a single type of soil, but the response of soil microorganisms to varying carbon and nitrogen inputs under different land soil use types have been relatively understudied, leaving a gap in our understanding of the key influencing factors. To address this gap, we conducted a study in the tropical regions of Hainan province, focusing on four distinct land use types: natural forest soil (NS), healthy banana soil (HS), diseased banana garden soil (DS), and paddy soil (PS). Within each of these environments, we implemented five treatments: CK, RS (rice straw), RSN (rice straw and NH4NO3), RR (rice root), and RRN (rice root and NH4NO3). Our aim was to investigate how soil bacteria response to changes in carbon and nitrogen inputs, and to assess their potential for biological nitrogen fixation. The results showed that the addition of rice straw increased the absorption and utilization of nitrate nitrogen by microorganisms. The addition of rice roots (RR) did not increase the absorption capacity of inorganic nitrogen by microorganisms, but increased the content of poorly soluble organic carbon. Most importantly, the addition of rice straw increased microbial respiration and the utilization efficiency of N2 by microorganisms, and the further addition of ammonium nitrate increased microbial respiration intensity. With the change of soil type, the rice straw increases microbial nitrogen fixation, bacterial and nifH genes abundance. Meanwhile, microbial respiration intensity is an important factor influencing the differences in the structure of bacterial communities. The addition of inorganic nitrogen resulted in ammonium nitrogen accumulation, reduced microbial richness and diversity, consequently diminishing the soil microorganisms to resist the environment. Therefore, we believe that with the change of soil types, corresponding soil nutrient retention strategies should be devised and incorporated while reducing the application of ammonium nitrogen, thus ensuring healthy soil development.

Floods and Land Use Land Cover Changes in the Kalu River Basin: A Call to Action


 
 
 Floods are one of the most common natural disasters worldwide. Apart from rainfall, Land Use Land Cover (LULC) changes too are a main contributory factor for floods. This study attempted to understand the link between floods and LULC changes in Kalu river basin, which is the second largest river basin and an area that experiences recurrent floods in Sri Lanka. We studied peak water levels, number of flood events, changes in land use types and impacts in rapidly urbanizing two districts, Rathnapura (upper basin) and Kalutara (lower basin) during 2001-2020. The satellite images (LANDSAT) were obtained for 2001, 2009, 2015 and 2020 and land use classification was done using ArcGIS and Remote Sensing Tools. Main land use types and their transformations were investigated and ground-truthing was carried out. Accordingly, the main types of land uses identified were Natural Vegetation and forests (NV), Settlements (ST- housing and industrial lands), Cultivated Lands (CL), Water Bodies (WB) and Bare Lands (BL). The results indicated that the most drastic change was found in the natural areas (NV) and they have diminished while the lands with anthropogenic impacts (ST, CL and BL) have increased across years. The NV had occupied the highest land area in 2001 (42.4%) and has reduced by 14.2% by 2020. The ST and CL have increased by 8.6 % and 5.2% respectively. The monthly rainfall of Rathnapura and Kalutara (Source: Department of Meteorology, Sri Lanka) has increased with time, which is a main reason for the increasing peak water levels of these areas (Source: Department of Irrigation, Sri Lanka). However, a significant correlation also exists between the change of the settlement area with the peak river water levels in the lower basin (p=0.03, R2=99%; regression analysis). Rathnapura has experienced 3 major floods (floods above the high water alert level) from 2001-2020, while 16 major floods have occurred in Kalutara. During the major flood in 2017, the number of child deaths in Rathnapura was 14 while in Kalutara it was 24. Accordingly, the LULC changes of the whole basin along with rainfall seem to influence on the severity of floods in Kalutara more, as it is located in the lowest elevation level. When natural lands are transformed to anthropogenic- impacted areas with disturbances to the water cycle, increased impervious surfaces, reduced water storage capacities and loss of natural drainage, the flood risk tends to increase. Proactive approaches including proper land use planning and rainwater storage are urgently needed as the climate change too would trigger more floods. Thus, the flood mitigatory actions, especially, in the lower river basin should be a priority to ensure resilience and sustainability.
 Keywords: Kalu river basin, Land Use Land Cover (LULC) changes, Floods
 
 

Study on the response of ecological sensitivity to land use and land cover changes in Jinzhai, China

Changes in land use types are often influenced by human activities, natural factors, and other factors. To explore the changes in land use types, in this paper, we focused on Jinzhai County in Anhui Province. Landsat series data from 2000 to 2020 were utilized as the primary remote sensing data source and combined with land use investigations, and the land use types were classified to better analyze their changes in Jinzhai County from 2000 to 2020. The main calculation indicators, such as the land use change rate and land use transfer matrix, were used to study the proportions of the different land use types during the past two decades, the comprehensive land use dynamics, and the directions of change of the different land use types.

Coupling coordination analysis of production, living, and ecological spaces in wetlands: A case study of Xianghai Wetland nature reserve, China

With the global alterations in ecological conditions and population growth, the study of production-living-ecological space (PLES) offers a new perspective in balancing land resource utilization with the sustainable development of society, economy, and environment. China has incorporated the optimization of PLES into its sustainable development strategy. However, research concerning the PLES functions within wetland ecosystems remains notably sparse. Wetlands, distinguished by their unique ecosystem, command a special place in the realm of production, living and ecology research. Their importance is multifaceted, stemming from their roles in ecology, economy, and socio-cultural dimensions, and further accentuated by their distinct geographical, climatic, and biodiversity attributes. In light of this, the Xianghai Wetland Nature Reserve in Jilin, China, was chosen as the focal point of this study to probe into the coupling coordination degree of its PLES functions. The study commenced with a thorough analysis of the changes in land use types from 2000 to 2020 using a land use transition matrix model. Following this, a customized land use function assessment framework called LUF-PLE was formulated, offering a quantitative assessment of the Xianghai wetland’s production, living, and ecological space functions and shedding light on their spatiotemporal dynamics. Finally, a coupling coordination degree model (CCDM) was employed to elucidate the evolution of the PLES functions of Xianghai wetlands. Key findings revealed that: (1) the Xianghai wetland’s PLES coupling coordination degree exhibited a pattern of decline, stabilizing post-2010, with the most pronounced dip observed between 2000–2010; (2) the coordination between production and living functions was notably subdued, whereas the coordination between production and ecological functions saw the steepest decline. In the future, a sustainable wetland development strategy should be formulated and implemented based on the observed trends in coupling coordination and the spatiotemporal differentiation of production-liveling-ecological functions in the local context. This research furnishes scientific substantiation and serves as a reference for the sustainable stewardship and preservation of wetlands.

The temporal variation of sediment connectivity from 1982 to 2020 in the Wei River basin, China

AbstractSediment connectivity is a valuable metric that characterizes the relationship between sediment transport from the source to the sink, and the ease of sediment erosion. Over the past four decades, changes in land use types and vegetation cover have significantly altered sediment dynamics in the Wei River basin. In this study, we used the index of connectivity (IC) to assess the temporal changes in sediment connectivity at a watershed scale. We employed Landsat images to analyse the relationship between changes in vegetation cover or land use type and sediment connectivity. We used factor detector and interaction detector in Geodetector to analyse the importance and impact of vegetation and slope on IC changes. We assessed the correlation of sediment yield and connectivity to validate our results and it shows that IC has strong or moderate positive correlation with sediment yield from eight out of nine stations in the Wei River Basin. Our findings demonstrate that soil and water conservation measures, as well as the grain for green project, have led to the transformation of cropland and grassland into woodland. This change is reflected in the decrease of the maximum IC value from 6.24 to 5.72 in the Beiluo sub‐basin, indicating a decreasing trend in sediment connectivity. Although the maximum IC value increased from 5.76 to 5.08 in the Jing sub‐basin, driven by human activity, showing an increasing trend. Furthermore, the IC value decreased in the western part of the Wei sub‐basin. Overall, sediment connectivity exhibits a weak decreasing trend in most regions of the Wei River basin, while it shows an increasing trend slightly in the Jing sub‐basin. The correlation coefficients ranged from 0.47 to 0.86, with sediment yield being moderately or strongly correlated with IC. Our study identified vegetation, human activity, and slope as the main influencing factors of IC. The results of factor detector showed that the q value of vegetation was 0.63 and the slope was 0.1, Vegetation played a major role in the change of IC. The results of interaction detector showed that interaction between vegetation and slope was greater than the single factor. The temporal variability of sediment connectivity in the basin provides valuable insights for sediment transport management. Our research highlights the importance of studying sediment connectivity and offers proposals for measures that can be taken to address sediment transport challenges in the Wei River basin.

Assessment of Physico-chemical Properties of Soil and Irrigation Water Quality of Phulpur Blocks of Prayagraj District, Uttar Pradesh, India

We aimed to study nutrient status in Phulpur block of Prayagraj District of Uttar Pradesh, India. We collected representative soil samples covering nine villages of Phulpur division at depths like 0-15cm, 15-30cm and 30-45cm before sowing of crops. The soil samples were analyzed for their physico-chemical properties. Results show that the soil samples of the areas of the Phulpur division were found to be mildly alkaline and non-saline. There are many reasons leading to soil quality deterioration, including changes in land use types of forest to arable land and the consequences of intensive land use. The colour of soil changes between the three depths at all locations. There were differences in the colour of dry and wet soils was dark brown to dark yellowish brown. The soil bulk density varied from 1.22 to 1.41 Mg m-3, soil particle density varied from 2.291 to 2.452 Mg m-3, pore space from 41.6 to 48.2 %, water holding capacity from 36.60 to 43.30 % respectively. Soil pH varied from 7.26 to 7.84 and EC is 0.24 to 0.38 dS m-1. while soil organic carbon varied from 0.29 to 0.45 % and available nitrogen from low to medium (180 to 275 kg ha-1), available phosphorous from medium to high (10.80 to 22.5 kg ha-1), potassium was found to be medium range (132.00 to 231.00 kg ha⁻1), exchangeable calcium and magnesium low from (3.48 to 5.50 Meq 100g-1) and (1.66 to 2.72 Meq 100g-1) respectively. The water pH of varied from 6.24 to 7.50, the electrical conductivity of water ranged from 0.31 to 0.90 dS m-1, the bicarbonate of water varied from 7 to 18 Meq L-1, the chloride of water varied from 4.5 to 10.4 Meq L-1, the available calcium of water varied from 4.2 to 8 Meq L-1, the available magnesium of water varied from 2.5 to 3.6 Meq L-1, the potassium of water varied from 0.05 to 0.17 Meq L-1 and the sodium of water varied from 0.08 to 0.21 Meq L-1. The sodium absorption ratio (SAR) ranged from 0.03 to 0.1 Meq L-1, indicating low to moderate levels of sodium content in the water samples. The soluble sodium percent (SSP) ranged from 1.47 to 3.93 Meq L-1, providing further insight into the sodium content in the water. The residual sodium carbonate (RSC) varied from -2.4 to 7.4 Meq L-1. The permeability Index (PI) ranged from 28 to 56 Meq L-1, serving as an indicator of the potential impact of water on soil permeability, the Kelley's ratio (KR) ranged from 0.08 to 0.024 Meq L-1. The KR is a measure of the sodium hazard in irrigation water, with lower values indicating a lower risk of sodium-related issues in soil and crops. The range of the irrigation water quality index value ranged from 44 to 157 Meq L-1 it was determined that 100% of the samples are in suitable range for irrigation.

Analysis of Land Use Type Changes in Yulin City in the 21st Century

Using remote sensing monitoring data of land use/land cover in China in 2000 and 2020, this study explores the changes in land use types in Yulin City through the land use transfer matrix. The results indicate that the main types of land use in Yulin City are grassland, cultivated land, and unused land. From 2000 to 2020, the order of absolute changes in the area of land use types in the study area is: unused land>grassland>construction land>cultivated land>forest land>water area, and its changes are closely related to national ecological policies; The area of construction land has significantly increased after 2000, which is consistent with the process of urbanization development; The continuous decrease in water area is mainly influenced by natural factors. The changes in land use types in Yulin City are influenced by both natural and social factors, with ecological policies and urbanization development dominating.

Spatio-temporal evolution of land use and its eco-environmental effects in the Caohai National Nature Reserve of China

With the rapid development of social economy, the ecological environment problems caused by the change of wetland land use have been widely concerned. This paper takes the Caohai National Nature Reserve (CNNR) of China as the research object on the basis of referring to previous research results. Firstly, the remote sensing data was employed to examine the spatio-temporal evolution process of the CNNR from three aspects: land use structure change, land use dynamic degree and land use space change. Then the change of ecological environment quality was studied from the greenness, the wetness, the dryness and the heat. Based on the spatiotemporal changes of land use types and ecological environment quality in the CNNR from 2000 to 2020, a comprehensive index, the remote sensing ecological index (RSEI), was constructed to analyze the ecological environmental effects of land use changes. The results indicate that the land use changes in the CNNR went through two major periods: first, a period of rapid decline in cultivated land, and second, a period of sharp increase in constructed land. During the period of rapid decline in cultivated land, the ecological environment quality in the study area showed an upward trend. However, during the period of increased constructed land, the ecological environment quality gradually stabilized. This study provides a basis for the coordinated development of the ecological environment and social economy in the CNNR area.

Impacts of land-use and topography on soil physicochemical properties in the Wamancho watershed, Southern Ethiopia

For sustainable land management, clear information that accounts for changes in land-use types and landscapes is essential. The purpose of this study was to examine how land-use patterns and topographic variation affect selected soil property indicators in the Wamancho watershed of the Damot Pulasa district in southern Ethiopia. Soil samples were obtained from the topography of three types of land use (agroforestry, cultivated land, and grazing area). At a depth of 20 cm, 27 soil samples were collected (three land use categories × three topographies × three replications). The collected soil samples were analyzed using standard laboratory procedures. The results showed that soil texture classes, such as sand and clay, bulk density, pH, SOC, Av. P, total N, CEC, and exchangeable bases, changed considerably (p < 0.05) with land use type, whereas total N, sand, and silt did not vary significantly with slope. Soil pH, SOC, Av. P, CEC, percentage of silt, and exchangeable cations (Na+, Mg2+, and K+) were found to be highest in agroforestry, while sand concentration was highest in cultivated land. Exchangeable Mg and K were found to be lower on cultivated ground, while Ca+ was found to be lower on agroforestry land. Finally, most soil quality indicators revealed a significant (p < 0.05) difference between agroforestry and grazing land use. Despite the fact that soil quality varies based on topography and land use type, local-level planning has not been conducted on a priority basis or in specific locations. As a result, all involved parties, including local governments, stakeholders, and planners, should develop effective site-based sustainable land management interventions, as they need to be addressed quickly, particularly on cultivated land, grazing land, and upper topography.

Integrated approach for ecological restoration and ecological spatial network optimization with multiple ecosystem functions in mining areas

The transformation of the landscape structure in mining cities is influenced by a combination of various factors, resulting in a decline in the ecological quality of the landscape and an increased vulnerability of the ecological environment. The quality of landscape ecology directly impacts the flow and transmission of ecosystem functions, underscoring the need for careful consideration in the establishment of landscape ecological networks. In this study, an analysis was conducted using land-use data from 2005 to 2020 in Linfen City, Shanxi Province, China. A network optimization strategy was established, focusing on the capacity for ecosystem self-restoration and the connectivity of ecological patches. Additionally, the spatiotemporal characteristics of landscape ecological risk between 2005 and 2020 were examined. Taking into account the influence of the ecological value of the landscape on the resilience of the ecosystem, the Minimum Cumulative Resistance (MCR) model was employed to construct the landscape ecological network. The structural characteristics of the landscape ecological network were explored using complex network methods. In addition, an optimization strategy based on ecosystem functionality and connectivity (EC) was adopted, and by comparing the connectivity and robustness of the network before and after the optimization, it was found that the method enhanced the smoothness of energy transfer and interconnectivity among nodes of the network, and significantly enhanced the stability of the ecological network. Within the study area, local levels of risk increased due to coal mining and urban expansion. (The maximum value in 2005 was 335.) However, overall risk levels improved with the progress of land reclamation efforts. (The maximum value in 2020 was 325.) Higher risks were observed in the vicinity of urban construction and mining areas, while forested and grassland areas exhibited relatively lower risks. The changes in risk within the study area were primarily influenced by factors such as mining activities, urban expansion, government policies, changes in land use types, and village relocation. The findings of this study provide theoretical support for the optimization of the landscape structure in mining cities, the construction of systems of ecological security as well as the restoration of ecosystems.

Quantifying the impacts of natural and human factors on changes in NPP using an optimal parameters-based geographical detector

Investigating the driving mechanisms behind fluctuations in vegetation net primary productivity (NPP) has the potential to enhance our comprehension of ecosystem dynamics and their response to environmental changes. However, identifying the nonlinear and spatiotemporal heterogeneity of factors contributing to NPP variation remains a challenge. This research employed the Theil-Sen trend, Hurst index, and nonparametric Mann-Kendall test methodologies through the utilization of Google Earth Engine (GEE) to detect monotonic trends in NPP, distinguishing between upward and downward trends. The influence of individual factors and their interactive effects on NPP changes were quantified using the optimized parameter-based geographical detector (OPGD) model. The findings revealed a general upward trend in NPP, exhibiting an average growth rate of around 85.06 gC m−2.a-1. Nevertheless, these rates of growth were not uniform, leading to noteworthy fluctuations spanning from 447.44 to 543.69 gC m−2.a-1. The eastern and central regions showcased relatively elevated NPP, whereas the western and southern regions demonstrated comparatively reduced levels. Roughly 51.66% of the areas displayed a rising trend in NPP, with 44.81% of the entire area indicating a noteworthy increase (p < 0.01), including both a substantial increase (p < 0.01) and a moderate increase (0.01 ≤ p < 0.05). The areas witnessing heightened NPP were predominantly situated in the northeastern, southeastern, northwestern sections, and the southwestern portion of Sichuan. The fluctuations in NPP trends displayed mild persistence or slight antipersistence traits, with regions where 0 < H < 0.5 constituting 80.26% of the overall area. Natural factors (such as elevation, mean annual temperature, NDVI, and topographic relief) along with human influences (changes in land use type) were identified as effectively accounting for the fluctuations in NPP. These factors demonstrated interactive effects on NPP, with the synergistic effect resulting in nonlinear enhancement and bilinear enhancement effects. The interaction between these two factors strengthened the influence of each individual factor. Identifying the optimal characteristics or ranges of these factors can facilitate ecological conservation and vegetation restoration. These factors exhibited interactive effects on NPP, with the synergistic effect resulting in nonlinear enhancement and bilinear enhancement effects. The interplay between these two factors heightened the influence of each separate element. Determining the optimal attributes or ranges of these factors can contribute to the facilitation of ecological preservation and the restoration of vegetation.

Studies on physico-chemical parameters in different soil samples from Erode District, Tamil Nadu, India

Soil physicochemical properties can be regarded as an important tool to assess soil health, which further form a base for biological activity in soil. These soil physicochemical properties are comparable in identical land-uses. However, the changes in land-use types and their effects on soil physicochemical properties are largely debates and rather unclear. Soil serves as an important thing in agriculture because this determines the plant growth and health. The present circumstance of industrialization and urbanization has taken a toll on environment, polluting the soil, air and water. Pollution as well as global warming has exhibited detrimental effects on our natural resources of soil becomes the inexplicable. Failing monsoon rains due to climatic changes, population explosion, and depletion of natural water and soil resources such as ground soil, agricultural soil as well as intentional man-made pollution of agriculture pesticide to soil scarcity. Even the scarcely available water is located by contaminants and pollutants which include mutagens, carcinogens, and pathogenic microbes affecting all the file forms affecting the ecological balance. Considering the above mentioned problem criteria, a part of the present work has been designed to analyze the quality of ground soil around the industrial premises. For this objective, we have collected different types of soil samples from various locations in and around sathyamangalam area in Erode District focusing on quite far away from industrial premises considering the concepts of leaching. Basic physio-chemical properties of soil colour, pH, chloride, sulphate, phosphate, silicate, nitrate, moisture, nitrogen, phosphorous, potassium using specific techniques used in laboratory for the samples have been analyzed by APHA standards. These analysis help in the addition of the nutrients of the soil and provide a nutritive indicator value of the sampling sites. Highest possibility of soil quality issues which affects the day to day consumption of soil samples for the domestic needs of the people has been emphasized.