Analysis of land use/ land cover changes and landscape fragmentation in the Baro-Akobo Basin, Southwestern Ethiopia.

This study investigated the relationship between land use/land cover (LULC) changes and forested landscape fragmentation in the southwestern region of Ethiopia. Satellite images from 1986, 2002 and 2019 were collected and analyzed using standard procedures in ERDAS 2015 software. Fragstat 4.2.1 software was utilized to assess landscape fragmentation by examining a raster datasets derived from the classified LULC map over the research period. The study identified seven LULC classes in the study area. Findings revealed a substantial reduction in shrubland by 46.3%, dense forest by 23.75%, open forest by 17.3%, and wetland by 32.63%, while cropland increased by 38.06%, agroforestry by 20.29%, and settlements by 163.8% during the study period. These changes varied across different agroecological zones and slope gradients. Landscape metrics results indicated an increase in the number of patches and patch density for all LULC classes, demonstrating significant fragmentation of the landscape. The largest patch index, mean patch areas, and the percentage of landscape occupied by open forest, dense forest, shrubland, and wetland declined as a result of conversion to cropland, agroforestry, and settlement. Conversely, the largest patch index, the mean patch area and the percentage of the landscape occupied by agroforestry, cropland and settlement increased, indicating their increasing dominance in the landscape over the study periods. The findings highlighted the potential deleterious impacts of ongoing land use change and fragmentation on the environment, ecosystem function and local livelihoods. Therefore, it is crucial to implement appropriate conservation efforts and sustainable land management practices to mitigate the rapid change and fragmentation of land use and its negative impacts on sub-watershed ecosystems.

Exploring optical descriptors for rapid estimation of coastal sediment organic carbon and nearby land-use classifications via machine learning models.

This study utilizes ultraviolet and fluorescence spectroscopic indices of dissolved organic matter (DOM) from sediments, combined with machine learning (ML) models, to develop an optimized predictive model for estimating sediment total organic carbon (TOC) and identifying adjacent land-use types in coastal sediments from the Yellow and Bohai Seas. Our results indicate that ML models surpass traditional regression techniques in estimating TOC and classifying land-use types. Penalized Least Squares Regression (PLR) and Cubist models show exceptional TOC estimation capabilities, with PLR exhibiting the lowest training error and Cubist achieving a correlation coefficient 0.79. In land-use classification, Support Vector Machines achieved 85.6 % accuracy in training and 92.2 % in testing. Maximum fluorescence intensity and ultraviolet absorbance at 254 nm were crucial factors influencing TOC variations in coastal sediments. This study underscores the efficacy of ML models utilizing DOM optical indices for near real-time estimation of marine sediment TOC and land-use classification.

Spatiotemporal assessment of the nexus between urban sprawl and land surface temperature as microclimatic effect: implications for urban planning.

Rapid urbanisation has led to significant environmental and climatic changes worldwide, especially in urban heat islands where increased land surface temperature (LST) poses a major challenge to sustainable urban living. In the city of Abha in southwestern Saudi Arabia, a region experiencing rapid urban growth, the impact of such expansion on LST and the resulting microclimatic changes are still poorly understood. This study aims to explore the dynamics of urban sprawl and its direct impact on LST to provide important insights for urban planning and climate change mitigation strategies. Using the random forest (RF) algorithm optimised for land use and land cover (LULC) mapping, LULC models were derived that had an overall accuracy of 87.70%, 86.27% and 93.53% for 1990, 2000 and 2020, respectively. The mono-window algorithm facilitated the derivation of LST, while Markovian transition matrices and spatial linear regression models assessed LULC dynamics and LST trends. Notably, built-up areas grew from 69.40 km2 in 1990 to 338.74 km2 in 2020, while LST in urban areas showed a pronounced warming trend, with temperatures increasing from an average of 43.71 °C in 1990 to 50.46 °C in 2020. Six landscape fragmentation indices were then calculated for urban areas over three decades. The results show that the Largest Patch Index (LPI) increases from 22.78 in 1990 to 65.24 in 2020, and the number of patches (NP) escalates from 2,531 in 1990 to an impressive 10,710 in 2020. Further regression analyses highlighted the morphological changes in the cities and attributed almost 97% of the LST variability to these urban patch dynamics. In addition, water bodies showed a cooling trend with a temperature decrease from 33.76 °C in 2000 to 29.69 °C in 2020, suggesting an anthropogenic influence. The conclusion emphasises the urgent need for sustainable urban planning to counteract the warming trends associated with urban sprawl and promote climate resilience.

Predicting macroinvertebrate average score per taxon (ASPT) at water quality monitoring sites in Japanese rivers.

Biomonitoring with bioindicators such as river macroinvertebrates is fundamental for assessing the status of freshwater ecosystems. In Japan, water quality and biomonitoring surveys are conducted separately, leading to a lack of nationwide information on their relationships and the biological status of water quality monitoring (WQM) sites. To understand the biological status of WQM sites across Japan, we developed a multiple linear regression model to estimate the average score per taxon (ASPT) using river macroinvertebrate data surveyed at a total of 237 "aligned" sites based on the co-occurrence of biomonitoring and WQM sites. The resulting regression model with eight predictors, such as biological oxygen demand, the proportion of urban areas in the catchment, could predict ASPT with reasonable accuracy (e.g., an error of ±1 for 96% of the aligned data). Using this model, we estimated ASPT values at 2925 WQM sites in rivers nationwide, categorizing them into four levels of river environment quality: "very good" (29% of WQM sites), "good" (50%), "fairly good" (14%), and "not good" (8%). Furthermore, we observed statistically significant correlations (p < 0.05; 0.4 ≤ r ≤ 0.7) between ASPT and all eight macroinvertebrate metrics examined, such as mayfly and stonefly richness, providing ecological implications of changes in ASPT.

Parameterization of nutrients and sediment build-up/wash-off processes for simulating stormwater quality from specific land uses.

Urbanization changes land cover through the expansion of impermeable surfaces, leading to a significant rise in runoff, sediment, and nutrient loading. The quality of stormwater is related to land use and is highly variable. Currently, stormwater is predominantly described through watershed models that rely minimally, if at all, on field monitoring data. The simple event mean concentration (EMC) wash-off approach by land use is a common method for estimating urban runoff loads. However, a major drawback of the EMC approach is it assumes concentration remains constant across events for a specific land use. Build-up/wash-off equations have been formulated to consider variations in concentration between events. However, several equation parameters are challenging to estimate, making them difficult to use. We conducted a monitoring and modeling study and investigated the impact of land use on stormwater quantity and quality and optimized and investigated the build-up/wash-off parameters for three homogenous urban land uses to estimate nutrients (nitrogen and phosphorus) and sediment loads. Stormwater from commercial, medium-density residential, and transportation land uses was sampled using automatic samplers during storm events, and water quality was characterized for a variety of them for 14 months. Analysis of stormwater samples included assessments for total nitrogen, total phosphorus, and total suspended solids. Results showed that medium-density residential land use had the highest median total nitrogen and total phosphorus event mean concentrations and commercial had the highest median total suspended solids EMCs. Water quality parameters (or build-up/wash-off parameters) exhibited significant variation between land uses, confirming that land use is a key determinant of stormwater quality. The median particle size for each land use was less than 150 µm, indicating that the most common particle size in stormwater was a very fine sand or smaller. This small size should be considered by stakeholders in the design of stormwater treatment systems.

Impacts of climate and land use change on terrestrial carbon storage: A multi-scenario case study in the Yellow River basin (1992-2050).

Currently, socioeconomic development and climate change pose new challenges to the assessment and management of terrestrial carbon storage (CS). Accurate prediction of future changes in land use and CS under different climate scenarios is of great significance for regional land use decision-making and carbon management. Taking the Yellow River Basin (YRB) in China as the study area, this study proposed a framework integrating the land use harmonization2 (LUH2) dataset, the patch-generating land use simulation (PLUS) model, and the integrated valuation of ecosystem services and trade-offs (InVEST) model. Under this framework, we systematically analyzed the spatiotemporal evolution characteristics of land use and their impact on CS in the YRB from 1992 to 2050. The results showed that (1) CS was highest in forestland and lowest in construction land, with a spatial distribution of high in the south and low in the north. From 1992 to 2020, construction land, forestland, and grassland increased while cropland decreased, reducing the total CS by 74.04 Tg. (2) From 2020 to 2050, under SSP1-2.6 scenario, forestland increased by 158.87 %; under SSP2-4.5 scenario, unused land decreased by 65.55 %; and under SSP5-8.5 scenario, construction land increased by 13.88 %. By 2050, SSP1-2.6 scenario exhibited the highest CS (8105.25 Tg), followed by SSP2-4.5 scenario (7363.61 Tg), and SSP5-8.5 scenario was the lowest (7315.86 Tg). (3) Forestland and construction land were the most critical factors affecting the CS. Shaanxi and Shanxi had the largest CS in all scenarios, and Qinghai had a huge carbon sink potential under SSP1-2.6 scenario. Scenario modeling demonstrated that future climate and land-use changes would have significant impacts on terrestrial CS in the YRB, and green development pathways could strongly contribute to meeting the dual­carbon target. Overall, this study provides a scientific basis for promoting low-carbon development, land-use optimization, and ecological civilization construction in YRB, China.

[Scale Effects of Landscape Pattern on Impacts of River Water Quality： A Meta-analysis].

The landscape pattern determines water pollution source and sink processes and plays an important role in regulating river water quality. Due to scale effects, studies on the relationship between landscape pattern and river water quality showed variance at different scales. However, there is still a lack of integrated study on the scale effect of landscape pattern and river water quality dynamics. This study collected 4 041 data from results of previous publications to address the characteristics of landscape pattern and river water quality dynamics at different scales and to identify the key temporal and spatial scales as well as landscape pattern indices for regulating river water quality. The results indicated that, compared to precipitation events, base flow periods, and interannual scales, the high-flow period was the key temporal scale for linking landscape pattern on river water quality. Compared to the watershed scale, the landscape pattern of buffer zones had a greater impact on river water quality. The high-flow period-buffer zone scale was the key spatiotemporal coupling scale for linking landscape pattern and river water quality. Compared to croplands, water bodies, grasslands, and the overall landscape of the watershed, the landscape pattern of forests and urban areas had a greater impact on river water quality. Fragmentation degree was the most important landscape pattern factor regulating river water quality. In river water quality management, it is important to focus on the landscape configuration of buffer zones, increase forest area, reduce patch density of forests and water bodies, and decrease the aggregation degree of urban areas.

[Land Change Simulation and Grassland Carbon Storage in the Loess Plateau Based on SSP-RCP Scenarios].

Exploring the spatial distribution of land use/coverage (LUCC) and ecosystem carbon reserves in the future of climate change can provide a scientific basis for optimizing the distribution of land resources and formulating social economic sustainable development policies. In this study, we integrated the plaques generating land use simulation (PLUS) model and ecosystem services and weighing comprehensive evaluation (InVEST) model. Based on the CMIP6-based sharing socio-economic path and representative concentration path (SSP-RCP), we evaluated the Loess Plateau for time and space dynamic changes in LUCC and ecosystem carbon reserves, analyzed the impact of driving factors on different regions, and explored the correlation between carbon reserves in various regions. The results showed:① In the future, the three scenarios were similar to the LUCC changes. The area of cultivated land, grassland, and unused land would be reduced to varying degrees, and the construction land had expanded sharply. The increase in the three scenarios was 29.23%-53.56% (SSP126), 34.59%-63.28% (SSP245), and 42.80%-73.27% (SSP585). ② Compared with that in 2020, the carbon reserves of SSP126 sites in 2040 increased by 1.813 8×106 t, and in the remaining scenarios it would continue to decline. By 2060, the grassland carbon reserves in the three scenarios decreased by 13.391×106, 33.548×106, and 85.871×106 t, respectively. ③ From the perspective of space correlation, the carbon reserves of the Loess Plateau were correlated between cities. The difference in future scenarios was not significant. The hotspots were distributed in the middle and north of the research area. There was no obvious cold spot area. ④ The changes in land use were predicted to increase or lose carbon reserves. Forestry, cultivated land, and grassland had more carbon reserves those in than other land types. Increasing their area and restrictions on the conversion of other land types should increase the ecosystem carbon reserves.

[Effects of Land Use Change on Soil Aggregate Stability and Soil Aggregate Organic Carbon in Karst Area of Southwest China].

Investigating the relationship of soil aggregate stability with the organic carbon in the aggregate and its response to land use change is conducive to the estimation of soil carbon sink potential, improvement of rocky desertification, and rational land use in karst areas of Southwest China. In order to explore the effects of land use change on the composition and stability of soil aggregate stability as well as the content of aggregate organic carbon, the soil (0-30 cm) of five land use types (secondary forest, pomelo forest, paddy field, pepper forest, and dry land) was selected as the research object. The characteristics and correlation of soil aggregate components and organic carbon under different land use patterns were obtained, and the contribution of soil aggregates to the change in organic carbon after land use change was calculated. The results showed that the macroaggregates in the surface soil (0-15 cm) of the secondary forest, pomelo forest, and paddy field were 63.32%, 52.38%, and 47.77%, respectively, which were significantly higher than that of dry land (23.70%), as was also seen in the lower layer (15-30 cm). The geometric mean diameter (GMD) and mean weight diameter (MWD) of soil aggregates in the secondary forest, pomelo forest, and paddy field were significantly higher than those in dry land. In the surface soil, the organic carbon of the secondary forest and paddy field was significantly higher than that of other land use patterns. By contrast, in the lower soil layer, only the organic carbon of the paddy field was significantly higher than that of the others. Under different land use patterns, the organic carbon content of aggregates followed the same order of macroaggregates > microaggregates > silt and clay, indicating that macroaggregates allowed soil organic carbon to accumulate, whereas silt and clay did the opposite. According to correlation analysis, the content of soil macroaggregates was significantly positively correlated with GMD, MWD, and soil aggregate organic carbon, suggesting that the increase in soil macroaggregates could improve the stability of soil aggregates and store more soil organic carbon. Further, as land use change may have significantly affected the soil aggregate, moderate development of forestry and paddy cultivation is suggested to improve the soil carbon sequestration potential in the karst area of Southwest China.

[Effects of Land Use Patterns on Soil Microplastic Pollution in the Luoshijiang Sub-watershed of Erhai Lake Basin].

Microplastic pollution in the soil environment has received extensive attention, but the effects of different land use patterns on the sub-watershed scale on soil microplastic pollution are poorly understood. The Luoshijiang sub-watershed in the north of Erhai Lake was selected as the research object, and the characteristics of microplastic pollution in farmland, riparian zone, grassland, and woodland soils were analyzed. The pollution risks of microplastics in the four types of soil were assessed using the polymer risk index method, and the effects of land use patterns on the distribution and risk of microplastic pollution were further explored. The results showed that:① The abundance of microplastics in the soil of the Luoshijiang sub-watershed ranged from 220 to 1 900 n·kg-1, and the average abundance was (711 ± 55) n·kg-1. The main polymer types were polyester (PES, 32.52%) and polyethylene terephthalate (PET, 21.95%). The particle size of microplastics was concentrated in the range of 0.5-2 mm (61.89%). Fiber was the main shape of microplastics (>75%), and the dominant color was transparent (58.50%). ② Land use patterns determined the abundance and pollution characteristics of soil microplastics in the Luoshijiang sub-watershed. A significantly higher abundance of microplastics was found in the soil of farmland[(885 ± 95) n·kg-1] and riparian zone[(837 ± 155) n·kg-1], which had stronger intensities of human activity, than that in woodland soil[(491 ± 53) n·kg-1] (P<0.05). Film and fragment microplastics mainly occurred in farmland soil, which also had the largest number of polymer types and the most abundant colors. ③ The risk index level of microplastics (Level Ⅲ) in the soil of farmland was higher than that of the other three land use patterns (Level Ⅰ). This research indicated that the higher the intensity of human activities of a sub-watershed was, the more complex the occurrence characteristics of soil microplastics, the richer the types of polymers, and the higher the potential pollution risks would be. Therefore, it is necessary to strengthen the control of soil microplastic pollution in farmland.

Impact of typhoons on anthropogenic nitrogen sources in Lake Sihwa, South Korea.

This study investigated the nitrate dual isotopic compositions (δ15NNO3 and δ18ONO3) of water samples to trace nitrate sources in Lake Sihwa, which encompasses various land-use types (e.g., urban, industry, wetland, and agriculture). The biogeochemical interactions of anthropogenic nitrogen sources (e.g., soil, road dust, and septic water) were also evaluated through multiple pathways from terrestrial boundaries to the water column. Based on increased concentrations of dissolved total nitrogen (DTN; 3.1 ± 1.6 mg/L) after typhoon, the variation of element stoichiometry (N:P:Si) in this system shifted to the relatively N-rich conditions (DIN/DIP; 14.1 ± 8.1, DIN/DSi; 1.4 ± 1.8), potentially triggering the occurrence of harmful algal blooms. Furthermore, discriminative isotopic compositions (δ15NNO3; 4.0 ± 2.1 ‰, δ18ONO3; 6.1 ± 4.3 ‰) after the typhoon suggested the increased DTN input of anthropogenic origins within Lake Sihwa would be mainly transported from urban sources (76 ± 9 %). Consequently, the isotopic-based approach may be useful for effective water quality management under increased anthropogenic activities near aquatic systems.

Soil quality assessment in low human activity disturbance zones: a study on the Qinghai-Tibet Plateau.

The Qinghai-Tibet Plateau, located at the Third Pole and known as the "Asian water tower," serves as a crucial ecological barrier for China. Grasping the soil quality on the Qinghai-Tibet Plateau holds paramount importance for the rational and scientific exploitation of soil resources within the region and is essential for vegetation restoration and ecological reconstruction. This study, conducted in Maqin County, Qinghai Province, collected 1647 soil samples (0-20 cm) within a study area of 6300 km2. Sixteen soil indicators were selected that were split into beneficial (N, P, S, and B), harmful (Cr, Hg, As, Pb, Ni, and Cd), and essential (Cu, Zn, Se, Ga, K, and Ca) elements. The Soil Quality Index (SQI) was computed to assess soil quality across diverse geological contexts, land cover classifications, and soil profiles. The results indicate that the overall SQI in the study area was comparatively high, with most regions having an SQI between 0.4 and 0.6, categorized as moderately to highly satisfactory. Among the different geological backgrounds, the highest SQI was found in the Quaternary alluvium (0.555) and the lowest in the Precambrian Jinshuikou Formation (0.481). Regarding different land-use types, the highest SQI was observed in glacier- and snow-covered areas (0.582) and the lowest in other types of grassland (0.461). The highest SQI was recorded in typical alpine meadow soil (0.521) and the lowest in leached brown soil (0.460). The evaluation results have significant reference value for the sustainable utilization and management of soil in Maqin County, Qinghai Province, China.

Spatial and Temporal Dynamics of the Vegetation Cover from the Bijagual Massif, Boyacá, Colombia, during the 1986-2021 Period.

Landscape changes based on spectral responses allow showing plant cover changes through diversity, composition, and ecological connectivity. The spatial and temporal vegetation dynamics of the Bijagual Massif from 1986 to 2021 were analyzed as a measure of ecological integrity, conservation, and territory. The covers identified were high open forest (Hof), dense grassland of non-wooded mainland (Dgnm), a mosaic of pastures and crops (Mpc), lagoons (Lag), and bare and degraded lands (Bdl). The Bijagual Massif has 8574.1 ha. In 1986, Dgnm occupied 42.6% of the total area, followed by Mpc (32.8%) and Hof (24.5%); by 2000, Mpc and Hof increased (43.7 and 28.1%, respectively), while Dgnm decreased (28%); by 2021, Dgnm was restricted to the northeastern zone and continued to decrease (25.2%), Mpc occupied 52.9%, Hof 21.7% and Bdl 0.1%. Of the three fractions of the connectivity probability index, only dPCintra and dPCflux contribute to ecological connectivity. Hof and Dgnm show patches with biota habitat quality and availability. Between 1986 and 2021, Dgnm lost 1489 ha (41%) and Hof 239.5 ha (11%). Mpc replaced various covers (1722.2 ha; 38%) in 2021. Bijagual has a valuable biodiversity potential limited by Mpc. Territorial planning and sustainable agroecological and ecotourism proposals are required due to the context of the ecosystems.

Assessing the impact of Land use changes on ecosystem services in the Alledighe rangeland, Ethiopia.

Understanding the ecological, social, and economic values of protected areas, as well as assessing the services they provide to both humans and the environment is crucial for informing conservation policies and sustainable land management practices. Using the benefits transfer method, changes in ecosystem service values (ESVs) resulting from spatiotemporal land use dynamics were evaluated in the Alledighe Wildlife Reserve (AWR) spanning from 1998 to 2016. Five distinct habitat types, namely grassland, bushland, woodland, riverine forest, and highland forest, were identified across the landscape. The ESVs were estimated using regional and global ESV values. A decline in the extent of grassland, woodland, and riverine forests by 9.9%, 2.4%, and 1.5%, respectively, was observed while bushland and highland forests increased by 10.6% and 3.3%, respectively. The AWR experienced a loss of roughly 145 km2 of grassland habitat. Based on regional and global ESVs, total ESVs in the study area decreased by 28.18% from approximately US$ 180 million to approximately US$ 129 million, and by 40.85% from approximately US$ 496 million to approximately US$ 293 million. As per individual ESV assessment, the total ESV decreased by 41% from around US$ 374.5 million to US$ 264.8 million. Provisioning service declined by 41.6% from US$ 100 million to US$ 70.6 million. Regulating service declined by 42.5% from US$ 242.4 million to US$ 170 million. Supporting service declined by 67% from US$ 5.3 million to US$ 3.2 million, and cultural service decreased by 27.8% from US$ 26.7 million to US$ 20.8 million. The larger ESV change was contributed by the expansion of forestland and bushland across previously grassland-dominated areas. The results of this study could render the value of the rangeland more visible in the decision-making process, as well as provide valuable input for future planning and management interventions of the AWR's pristine rangeland, thereby enhancing ecosystem services and the livelihoods of the surrounding communities.

Characterizing landscape fragmentation of Koitobos river sub-basin, Trans-Nzoia, Kenya.

The changes in landscape structure and functioning due to unprecedented human interference are hastening across the globe and it is thus a compelling necessity to preserve and restore our ecosystems. This study aimed to characterize levels of landscape fragmentation, habitat structure, driving forces, and perceptions of the residents on the most preferred reconfiguration approaches. The land use/land cover [LULC] change was first determined by interpreting the 1973, 1986, 1995, 2002, 2014, and 2022 Landsat images using the QGIS 3.26 while the selected landscape fragmentation metrics were analyzed using FRAGSTATS 4.2. Forests, shrubs, and grasslands showed a declining trend, except for agriculture, water, and built-up areas, which depicted high increases for the study periods [1973 to 2022]. The landscape of the study area is characterized as progressively fragmenting as signified by high escalated values of patch number [374 %], edge density [7828 %] between 1986 and 2002, contagion [10.3%], and a declined value of Shannon Diversity Index [SHDI] [-17.42%], Shannon evenness index [SHEI] [-25.8 %] and connectedness [-43.3%]. Considering these results, high losses of forests and grasslands coupled with expansive farmlands and built-up areas have led to unprecedented landscape fragmentation From field surveys and oral interviews, this has not only left streams vulnerable to massive sediment loads but has also triggered annual floods which occur during wet months even though change in onset of rainfall seasons was also reported. The findings call for restoration and integrated and sustainable restoration efforts, especially for the forests, grasslands, and riparian corridors along with sustainable urban planning and community-based sensitization on watershed management.

Assessment of land use management and its effect on soil quality and carbon stock in Ebonyi State, Southeast Nigeria.

Evaluating soil quality (SQ) resulting from land management use impact is important for soil carbon (C) monitoring, land sustainability and suitability. However, the data in less developed regions of Africa like Nigeria is scarce, limiting our understanding at global scale. The study evaluated land management use on soil quality in Ebonyi State, Nigeria, a representative region of Africa. Soil samples were collected in 2021 and resampled in 2022 from regions including five land use managements (FS = forest soil; GLS = grass land soil; ACS = alley cropping Soil; SDS = sewage dump-soils; CCS = continuously cultivated soil). Soil physical and chemical properties were analyzed and discussed. The results shows that soil physical properties (bulk density, hydraulic conductivity, aggregate stability) were significantly (P < 0.05) influenced by land use management. Moderate to high bulk density, very low hydraulic conductivity (HC), and low aggregate stability were observed across land management, suggesting potential inhibition to root penetration, poor aeration, and water infiltration. Improved land management practices such as planting of cover crops either for re-grassing or addition of crop residues could be adopted as conservative options for increasing soil quality and encourage additional soil C. Soil pH decreased with the increase in soil depth in all land uses for both years. A higher soil pH of 6.78 (slightly acidic) was seen in SDS and lower mean 6.0 (moderately acidic) was obtained in CCS at 0-20 cm in 2021. The average mean nitrogen content was rated "very high" (0.81 g kg-1 and 0.69 g kg-1) in 2021 and 2022 respectively, suggesting nitrogen might not be a limiting factor for plant growth in the region. During the 2021 and 2022 study periods, the overall average mean C stock were 12.71 g kg-1 and 15.87 g kg-1 respectively suggesting 3.1 g kg-1 C stock increment in 2022. Soil inorganic C also increased by 9.86 g cm-2 in 2022. The study provided crucial information about how land management use affected soil physico-chemical properties including C stock and suggested that C stock could be improved by adopting appropriate land management use practices. The results fill a data gap in under-studied regions, but also facilitate potential land management practices.

A multi-spatial scale assessment of land-use stress on water quality in headwater streams in the Platinum Belt, South Africa.

River water quality is affected by various stressors (land-uses) operating at different hydrological spatial scales. Few studies have employed a multi-scaled analyses to differentiate effects of natural grasslands and woodlands, agriculture, impoundments, urban and mining stressors on headwater streams. Using a multi-scaled modeling approach, this study disentangled the distinct spatial signatures and mechanistic effects of specific stressors and topographic drivers on individual water quality parameters in tributaries of the Gwathle River Catchment in the Platinum Belt of South Africa. Water samples were collected on six occasions from 15 sites on three rivers over 12-months. Physio-chemical parameters as well as major anions, cations and metals were measured. Five key water quality parameters were identified using principal components analysis: sulfate, ammonium, copper, turbidity, and pH to characterise catchment water quality conditions. Using class-level composition (PLAND) and connectedness (COHESION) metrics together with topographic data, generalized linear mixed models were developed at multiple scales (sub-basin, cumulative catchment, riparian buffers) to identify the most parsimonious model with the dominant drivers of each water quality parameter. Ammonium concentrations were best explained by urban stress, Cu increased with mining and agriculture, turbidity increased with elevation heterogeneity, agriculture, urbanisation and fallow lands all at the sub-basin scale. River pH was positively predicted by slope heterogeneity, mining cover and impoundment connectivity at the catchment scale. Sulfate increased with mining and agriculture composition in the 100 m riparian buffer. Hierarchical cluster analysis of water quality and scale-dependent parsimonious drivers separated the river sites into three distinct groups distinguishing pristine, moderately impacted, and heavily mined sites. By demonstrating stressor- and scale-dependent water quality responses, this multi-scale nested modeling approach reveals the importance of developing adaptive, targeted management plans at hydrologically meaningful scales to sustain water quality amid intensifying land use.

Integrating historical patterns and future trends for ecological management zone identification and validation: A case study in Beijing, China.

Ecological management zones (EMZs) are pivotal in improving the management of ecosystem services (ESs) and promoting sustainable regional development. In this study, we developed a comprehensive framework aimed at identifying EMZs and substantiating their efficacy through the amalgamation of historical evolutionary patterns and future trends. We applied this framework to Beijing, China, and selected five vital ESs for the study area namely, water yield (WY), carbon sequestration (CS), habitat quality (HQ), soil conservation (SC) and water purification (WP). The framework involves two key components. Firstly, the identification of EMZs is based on the historical evolution of five types of ESs and the dynamic assessment of ES bundles. Subsequently, it enables a simulation of various scenarios to predict future alterations in land use and ESs, thereby validating the effectiveness of the identified EMZs. Our findings reveal notable spatial heterogeneity among different ESs, and that CS, HQ, SC, and WP exhibited synergies, while WY and showed trade-offs with the remaining four types of ESs. Based on an analysis of ES bundle evolution trajectories, we identified four types of EMZs: ecological conservation zone, ecological restoration zone, ecological transition zone and sustainable construction zone. Through strategic EMZ planning, it becomes possible to augment the area of forestland and grassland, alleviate the contradiction between arable land and construction land, and enhance the supply of various ESs. The proposed framework not only offers a novel perspective on the scientific management of ESs but also furnishes decision-makers and planners with an intuitive understanding of the tangible benefits associated with EMZ planning.

Appling fluorescence spectroscopy with absolute principal component coefficient to explore dynamic migration of DOM fractions from an urbanized river during torrential rainfall.

This research delves into the dynamic interplay between urbanization and the characteristics of Dissolved Organic Matter (DOM) in the Anyang River, particularly under the stress of torrential rain. The motivation stems from a critical need to decipher how urban landscapes influence water quality, focusing on the intricate transformations and movements of DOM. Employing advanced fluorescence spectroscopy techniques like Excitation-Emission Matrices (EEM) and Parallel Factor Analysis (PARAFAC), the study meticulously differentiates DOM compositions in urban and agricultural settings. It unveils a pronounced distinction, with urban streams showing elevated proteinaceous DOM from wastewater, contrasting with the humic substances prevalent in agricultural runoff. The analysis also captures how intense rainfall events catalyze significant shifts in DOM profiles, thereby emphasizing the need for tailored water quality management strategies in urbanized catchments. This comprehensive approach not only bridges gaps in understanding the urban impact on riverine ecosystems but also sets a foundation for future research and policy development in the face of escalating environmental changes.

Antimicrobial resistance in rural rivers: Comparative study of the Coquet (Northumberland) and Eden (Cumbria) River catchments.

Many studies have characterised resistomes in river microbial communities. However, few have compared resistomes in parallel rural catchments that have few point-source inputs of antimicrobial genes (ARGs) and organisms (i.e., AMR) - catchments where one can contrast more nebulous drivers of AMR in rural rivers. Here, we used quantitative microbial profiling (QMP) to compare resistomes and microbiomes in two rural river catchments in Northern England, the Coquet and Eden in Northumberland and Cumbria, respectively, with different hydrological and geographical conditions. The Eden has higher flow rates, higher annual surface runoff, and longer periods of soil saturation, whereas the Coquet is drier and has lower flowrates. QMP analysis showed the Eden contained significantly more abundant microbes associated with soil sources, animal faeces, and wastewater than the Coquet, which had microbiomes like less polluted rivers (Wilcoxon test, p < 0.01). The Eden also had greater ARG abundances and resistome diversity (Kruskal Wallis, p < 0.05), and higher levels of potentially clinically relevant ARGs. The Eden catchment had greater and flashier runoff and more extensive agricultural land use in its middle reach, which explains higher levels of AMR in the river. Hydrological and geographic factors drive AMR in rural rivers, which must be considered in environmental monitoring programmes.