Land use, land cover changes and expansion of artificial reservoirs in Eastern Thailand: implications for agriculture and vegetation drought reduction.

Eastern Thailand and Rayong province face perennial drought and water scarcity due to natural characteristics of climate and geology. Therefore, increasing water surface by man-made reservoirs is one of the priorities in the regional development plan to provide water adequately for industrial purposes, domestic consumption, and agriculture. The large reservoir constructions may induce land use, land cover changes (LULCC), yet it also is expected to alleviate the drought harshness in the region. By delineating Landsat satellite images and spatial analysis, this study revealed the LULCC in Rayong from 1990 to 2020. The most prominent LULCC was surface water expansion, about 10.9% per year, yet the increase was the most substantial in the first decade rather than the last two decades. Vegetation expansion was observed, contributing to an increase in forests/plantations and intensified agriculture by 39.19% and 25.54%, respectively. The LULCC corresponded to a 3.64% increase in ecosystem service values (ESV), implying positive benefits from the LULCC. Vegetation drought conditions monitored by the vegetation health index (VHI) exhibited an improvement trend, especially in the eastern basins. The development of artificial reservoirs was proven to stimulate the expansion of intensive agriculture and vegetation drought mitigation with spatial heterogeneity, spreading mainly across areas of the basins rather than remote areas. The research findings inform the efficiency of the reservoirs and irrigation systems regarding the beneficial effects on drought mitigation and water scarcity for agricultural cultivation. They also provide spatial information on areas still hindered by water problems that should be addressed in future strategies.

Stingless Bee Foraging Activity Related to Environmental Aspects.

The environment where bee colonies are inserted must provide the necessary resources for their survival. Given this, any biotic and abiotic changes in the environment can affect the development and survival of the colonies. We evaluated the foraging activity of Plebeia droryana (Friese), Scaptotrigona bipunctata (Lepetelier), and Melipona quadrifasciata (Lepetelier) in areas with different land uses and land cover. These areas were classified as predominantly (i) urbanized/forest (CDA-Cidade das Abelhas), (ii) agricultural (FER-Fazenda Experimental da Ressacada), and (iii) with dense vegetation (SFB-Sitio Florbela). We correlated the morphometric characteristics of the bees with the pollen load transported. Four colonies from each species were installed in the three areas. We recorded light, wind speed, humidity, and temperature and counted the foragers returning with nectar, pollen, and resin. Plebeia droryana and S. bipunctata collected more resin and nectar in with dense vegetation area compared to agricultural area. Scaptotrigona bipunctata collected more pollen in urbanized/forest area and with dense vegetation area, and M. quadrifasciata did not show differences in foraging activity between areas. Plebeia droryana and M. quadrifasciata showed moderate and strong correlations between morphometric characteristics and pollen load. SFB had higher luminosity and wind speed. CDA had higher average temperature. FER had higher humidity. The three species showed positive and negative correlations between temperature and light and foraging in the different areas. Smaller species showed a higher gathering of resources in the area predominantly covered by dense vegetation. The reduction of vegetation cover can affect the resource collection activity of stingless bees.

Long-term changes of mangrove distribution and its response to anthropogenic impacts in the Vietnamese Southern Coastal Region.

Human activities related to land use and land cover (LULC) conversion have been the primary factor driving changes to mangrove distribution over recent decades. In order to quantify the anthropogenic influences associated with LULC changes on mangroves in the Vietnamese Southern Coast (VSC), we investigated the variations and trends in mangrove distribution between 1988 and 2023. We used a time-series of Landsat spectral indices from Google Earth Engine and applied hot spot analysis and machine learning algorithms to analyse mangrove variations and LULC classification, respectively. Our findings revealed that over the past 36 years, approximately half of the mangrove area has been lost due to LULC conversions. The most significant losses in mangrove cover occurred during the 1998-2011 period, with a decline of 46.79% in total area (an average of 3.6% per annum). The rate of mangrove deforestation more than halved to 17.49% (1.5% per annum) in the period between from 2011 to 2023. We attribute the reduction in mangrove loss to conservation efforts and natural regeneration processes. The emerging hot spot analysis indicated that the most significant restoration of new mangrove areas occurred between 1988 and 1998, totalling 1795 ha (1.4%), while the highest rate of mangrove deforestation was observed between 1998 and 2011, amounting to 2249 ha (2.0%). The primary causes of these variations in mangrove distribution were the conversion of mangrove areas to shrimp farming (38.91%), followed by other agricultural land use (5.82%) and the expansion of impervious surfaces (3.34%). In contrast, a result of enhanced conservation efforts and natural regeneration was associated with a 17.91% of mangrove area gain in the 2011-2023 period. Despite the regeneration potential of mangroves, our study highlighted the ongoing need to manage and protect mangrove forests to facilitate their expansion in the VSC. The analytical approach adopted in this study is applicable to other coastal areas when assessing changes in mangroves and land use practices.

Landscape transition-induced ecological risk modeling using GIS and remote sensing techniques: a case of Saint Martin Island, Bangladesh.

Uncontrolled human activity and nature are causing the deterioration of Saint Martin Island, Bangladesh's only tropical island, necessitating sustainable land use strategies and ecological practices. Therefore, the present study measures the land use/cover transition from 1974 to 2021, predicts 2032 and 2042, and constructs the spatiotemporal features of the Landscape Ecological Risk Index based on land use changes. The study utilized Maximum Likelihood Classification (MLC) on Landsat images from 1974, 1988, 2001, 2013, and Sentinel 2B in 2021, achieving ≥ 80% accuracy. The MLP-MC approach was also used to predict 2032 and 2042 LULC change patterns. The eco-risk index was developed using landscape disturbance and vulnerability indices, Bayesian Kriging interpolation, and spatial autocorrelations to indicate spatial clustering. The research found that settlements increased from 2.06 to 28.62 ha between 1974 and 2021 and would cover 41.22 ha in 2042, causing considerable losses in agricultural areas, waterbodies, sand, coral reefs, and vegetation. The area under study showed a more uniform and homogenous environment as Shannon's diversity and evenness scores decreased. The ecological risk of Saint Martin Island increased from 4.31 to 31.05 ha between 1974 and 2042 due to natural and human factors like erosion, tidal bores, population growth, coral mining, habitat destruction, and intensive agricultural practices and tourism, primarily in Nazrul Para, Galachipa, and Western Dakhin Para. The findings will benefit St. Martin Island stakeholders and policymakers by providing insights into current and potential landscape changes and land eco-management.

Land use & land cover dynamics and its relationship with nitrate pollution in groundwater around inactive mine areas using geospatial techniques, SW part of Cuddapah basin, Southern India.

Geospatial maps can show how the ineffective operations of inactive mines affect water and aquifer quality. As such, the purpose of this study is to assess the impact of mining and irrigation on the aquifer ecosystem through the evaluation of LULC and slope maps through the application of Landsat 8 OLI/TIRS and DEM data. A total of 50 groundwater samples were prepared from villages in the close proximity to inactive mines during pre and post monsoon periods in 2021. The results of the analysis revealed alarming statistics, that 14% of groundwater samples exceeded the WHO nitrate limit in pre & post monsoon season, indicating a high-risk in the study area. According to guidelines (USEPA, 2014), 34% in pre-monsoon and 26% post-monsoon of samples exceeded the THI levels for adults and children respectively, indicating non-carcinogenic health risks. In addition, 80% of the samples in both seasons exhibited high NPI values, indicating nitrate contamination associated with blue baby syndrome. From the Geospatial analysis the findings from the LULC classification indicate that there has been a significant increase in cropland area from 2016 to 2021 due to changes in forest land, fallow land, and water resources. These problems have been exacerbated by the expansion of cultivated land, which has increased from 71.1 square kilometers in 2016 to 118 square kilometers in 2021, accounting for 13.1% of the total area. This expansion, coupled with elevated water body resource availability, has compounded the nitrate pollution including in intensely irrigated regions. The slope map analysis revealed that the inactive mines occur at low slope, high rainfall areas and these are compounded by runoff from other sources such as domestic and agricultural wastes. For these matters, sealing and remediating these inactive mines is essential so as to prevent further nitrate leakage.

Resilience to climate change by improving air circulation efficiency and pollutant dispersion in cities: A 3D-UFO approach to urban block design.

Urbanization presents significant challenges to air quality and climate resilience, necessitating pioneering urban design solutions to enhance air circulation and mitigate pollutants. This urgency intensifies in densely populated and rapidly evolving regions like Wuhan, China, where effective strategies are crucial for sustainable development. This study introduces an innovative 3D Urban Form Optimization (3D-UFO) methodology aimed at advancing urban block design configurations to improve urbanization quality. The 3D-UFO approach systematically addresses the multifaceted challenges of climate change and air quality degradation in rapidly urbanizing areas. Integrating GIS-based analysis for comprehensive Land-Use and Land-Cover Change (LULCC) evaluation with Computational Fluid Dynamics (CFD), our approach employs systematic exploration guided by established urban airflow study protocols. Robust metrics-Airspeed-Ratio (ASR) and Average-Age-of-Local-Air (ALA)-quantify the impact of diverse urban block design strategies on air-circulation efficiency and pollutant dispersion. Analysis across various urban scenarios, yielded by the proposed 3D-UFO approach, reveal significant variations in air-circulation efficiency at street and building levels (SBLs). Optimal urban air circulation achieves efficiency levels of 50-70 % when airflow aligns orthogonally across and parallel to streets. Adjusting street-level building heights, especially incorporating taller structures, boosts ventilation efficiency by 20-30 %, which is crucial for improving airflow dynamics in urban settings. Higher Height-to-Width (H/W) ratios (>5.5) yield a 218.5 % increase in ventilation in specific urban layouts. Notably, the synergy of street-aspect-ratio and building-height-ratio adjustments significantly enhance ASR and ALA, providing a quantitative foundation for sustainable urban development. This 3D-UFO methodology, fusing LULCC analysis, CFD simulations, and systematic exploration, emerge as a valuable framework for urban planners and designers. The study offers informed insights into urban sustainability challenges, demonstrating advancements in addressing environmental concerns and improving living conditions within densely populated environments.

Evaluating land use and climate change impacts on Ravi river flows using GIS and hydrological modeling approach.

The study investigates the interplay of land use dynamics and climate change on the hydrological regime of the Ravi River using a comprehensive approach integrating Geographic Information System (GIS), remote sensing, and hydrological modeling at the catchment scale. Employing the Soil and Water Assessment Tool (SWAT) model, simulations were conducted to evaluate the hydrological response of the Ravi River to both current conditions and projected future scenarios of land use and climate change. This study differs from previous ones by simulating future land use and climate scenarios, offering a solid framework for understanding their impact on river flow dynamics. Model calibration and validation were performed for distinct periods (1999-2002 and 2003-2005), yielding satisfactory performance indicators (NSE, R2, PBIAS = 0.85, 0.83, and 10.01 in calibration and 0.87, 0.89, and 7.2 in validation). Through supervised classification techniques on Landsat imagery and TerrSet modeling, current and future land use maps were generated, revealing a notable increase in built-up areas from 1990 to 2020 and projections indicating further expansion by 31.7% from 2020 to 2100. Climate change projections under different socioeconomic pathways (SSP2 and SSP5) were derived for precipitation and temperature, with statistical downscaling applied using the CMhyd model. Results suggest substantial increases in precipitation (10.9 - 14.9%) and temperature (12.2 - 15.9%) across the SSP scenarios by the end of the century. Two scenarios, considering future climate conditions with current and future land use patterns, were analyzed to understand their combined impact on hydrological responses. In both scenarios, inflows to the Ravi River are projected to rise significantly (19.4 - 28.4%) from 2016 to 2100, indicating a considerable alteration in seasonal flow patterns. Additionally, historical data indicate a concerning trend of annual groundwater depth decline (0.8 m/year) from 1996 to 2020, attributed to land use and climate changes. The findings underscore the urgency for planners and managers to incorporate climate and land cover considerations into their strategies, given the potential implications for water resource management and environmental sustainability.

Drivers of the taxonomic and functional structuring of aquatic and terrestrial floodplain bird communities.

Context: There has been a limited amount of research which comparatively examines the local and landscape scale ecological determinants of the community structure of both riparian and aquatic bird communities in floodplain ecosystems. Objectives: Here, we quantified the contribution of local habitat structure, land cover and spatial configuration of the sampling sites to the taxonomical and functional structuring of aquatic and terrestrial bird communities in a relatively intact floodplain of the river Danube, Hungary. Methods: We used the relative abundance of species and foraging guilds as response variables in partial redundancy analyses to determine the relative importance of each variable group. Results: Local-scale characteristics of the water bodies proved to be less influential than land cover and spatial variables both for aquatic and terrestrial birds and both for taxonomic and foraging guild structures. Purely spatial variables were important determinants, besides purely environmental and the shared proportion of variation explained by environmental and spatial variables. The predictability of community structuring generally increased towards the lowest land cover measurement scales (i.e., 500, 250 or 125 m radius buffers). Different land cover types contributed at each scale, and their importance depended on aquatic vs terrestrial communities. Conclusions: These results indicate the relatively strong response of floodplain bird communities to land cover and spatial configuration. They also suggest that dispersal dynamics and mass-effect mechanisms are critically important for understanding the structuring of floodplain bird communities, and should therefore be considered by conservation management strategies. Supplementary Information: The online version contains supplementary material available at 10.1007/s10980-024-01948-3.

Application of a Multi-Layer Perceptron and Markov Chain Analysis-Based Hybrid Approach for Predicting and Monitoring LULCC Patterns Using Random Forest Classification in Jhelum District, Punjab, Pakistan.

Land-use and land-cover change (LULCC) is a critical environmental issue that has significant effects on biodiversity, ecosystem services, and climate change. This study examines the land-use and land-cover (LULC) spatiotemporal dynamics across a three-decade period (1998-2023) in a district area. In order to forecast the LULCC patterns, this study suggests a hybrid strategy that combines the random forest method with multi-layer perceptron (MLP) and Markov chain analysis. To predict the dynamics of LULC changes for the year 2035, a hybrid technique based on multi-layer perceptron and Markov chain model analysis (MLP-MCA) was employed. The area of developed land has increased significantly, while the amount of bare land, vegetation, and forest cover have all decreased. This is because the principal land types have changed due to population growth and economic expansion. This study also discovered that between 1998 and 2023, the built-up area increased by 468 km2 as a result of the replacement of natural resources. It is estimated that 25.04% of the study area's urbanization will increase by 2035. The performance of the model was confirmed with an overall accuracy of 90% and a kappa coefficient of around 0.89. It is important to use advanced predictive models to guide sustainable urban development strategies. The model provides valuable insights for policymakers, land managers, and researchers to support sustainable land-use planning, conservation efforts, and climate change mitigation strategies.

Assessing sediment dynamics and retention services in the vulnerable mountain ecosystem of the Indian Himalayas.

Sediment loss and export pose significant global environmental issues, profoundly affecting water quality, soil fertility, and ecosystem stability, particularly in vulnerable mountain ecosystems like the Indian Himalayas. The present study used remote sensing data and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) sediment delivery ratio (SDR) model to analyze spatial-temporal variations in soil loss (SL), sediment export (SE), and sediment retention (SR) capabilities in the South Shimla watershed, Himachal Pradesh, India, from 1993 to 2023. The findings showed significant changes in land use and land cover (LULC): evergreen forest and scrub land decreased sharply by 11.53% and 36.43%, respectively, while agricultural areas and built-up areas increased notably by 71.16% and 215.76%, respectively. Despite a decline of 19.18% in SL and 24.43% in SE, sediment loss and export varied across the study area, highlighting the heterogeneous nature of sediment dynamics. The overall retention capacity increased by 2.59%, with scrub forests playing a critical role in SR, while built-up areas showed the lowest retention. Northern and central sub-watersheds (SWs) experienced a significant decrease in retention capacity (from - 1.92 to - 11.6%), whereas those in the southern and eastern regions saw an increase in SR (from 3.69 to 28.24%). These results underscore the complex interactions between LULC changes, sediment dynamics, and retention services, highlighting the importance of preserving natural ecosystems and informing policy for landscape-based conservation and development planning in the vulnerable Himalayan region.

Foraging Habitat Availability and the Non-Fish Diet Composition of the Grey Heron (Ardea cinerea) at Two Spatial Scales.

Habitat structure on foraging ground is one of the crucial factors determining diet diversity in colonially breeding avian predators. Quantifying the habitat and diet composition at different spatial scales (regional and local inter-colonial) can help provide understanding of the drivers of diet composition. In this study, we examined the composition of the non-fish diet of an opportunistic predator, the Grey Heron (Ardea cinerea), based on pellets. We compared pellets from 21 colonies in two different regions of Poland that differing in composition of foraging habitats. Multivariate statistical techniques were used to analyze the relationship between diet and habitat compositions in a 20 km radius around these colonies. Significant inter-regional and inter-colony differences in Grey Heron diet and habitat composition were detected in foraging areas. However, some prey were present in the diet only from one of the regions. Around the heronries with a predominance of farmland habitats, the European water vole (Arvicola amphibius) and terrestrial invertebrates were present in relatively low frequencies, and the striped field mouse (Apodemus agrarius) was present in high frequencies. Voles (Microtus sp.) were more frequent in colonies with prevalence of non-irrigated arable land around the colony, in contrast to the bank vole (Myodes glareolus), which was less common in heronries with a higher contribution of this habitat type. Remains of aquatic invertebrates were less abundant in colonies surrounded by extensive forests. The results of our research indicate the opportunistic character of the non-fish part of the diet of the Grey Heron adapted to the local foraging habitat and prey availability.

The state of nitrogen in rivers and streams across sub-Saharan Africa.

The nutrient status of rivers and streams is less researched in sub-Saharan Africa than in many other inhabited regions of the world. Given the expected population growth, intensification of agriculture, increased pressure on natural ecosystems and projected climate change in sub-Saharan Africa, it is crucial to quantify and understand drivers behind spatiotemporal patterns of nitrogen concentrations and loads in rivers and streams. Such knowledge can support sustainable management of water resources with the goal to provide clean water, create and maintain healthy ecosystems and prevent excessive pollution of water resources with nitrogen compounds, as is found in large parts of North America, Europe and Asia. This review provides a synthesis of the current available data from peer-reviewed literature (n = 243) on particulate and dissolved nitrogen in rivers and streams in sub-Saharan Africa, looking into seasonal and land cover-related differences. The review shows that data on nitrogen concentrations in rivers and streams is available for 32 out of the 48 countries (67 %) in sub-Saharan Africa, highlighting large data gaps given the size of the region. Differences in nitrogen concentrations between land cover types are reported, with highest median total nitrogen (3.9 mg N L-1) and nitrate (1.2 mg N L-1) concentrations observed at sites characterised by settlement and industry. In contrast, natural land cover types, like forest, have higher median (N:P) ratios (> 14.6) than cropland and urban areas (< 12.0). The analysis of paired samples from dry and wet seasons reveals varying effects of seasonality on the concentration of different nitrogen compounds between land cover types. However, the processes driving these spatiotemporal differences are still poorly understood. These findings highlight the need for a targeted research agenda for Africa to advance our understanding of the role of rivers and streams in nitrogen cycling in different ecosystems and their interaction with anthropogenic and natural drivers of change.

The impacts of climate change, early agriculture and internal fluvial dynamics on paleo-flooding episodes in Central China.

Floods clustered in episodes are the most prevalent natural disaster worldwide, causing substantial economic and human losses. Although these events are often linked to time-periods of extreme rainstorms and unique atmospheric circulation patterns, the river basin characteristics affected by anthropogenic land use changes could exert a strong influence. However, the way and extent of how land use changes across different time scales affect flooding periods are still unclear, especially considering the historical land use changes. This study uses the Landlab landscape evolution model, coupled with an evapotranspiration model, to investigate the forcing factors for the paleo-flooding trends in the Wei River catchment over the last 5000 years. The results indicate that the flooding period from 4400 to 4000 BP was caused by an increase of 28 % in antecedent moisture content as well as a decrease of 28 % in its spatial variability, which are primarily due to climate change, and that the contribution of land-use change is less than 5 %. The increases of about 14 % and 8 % in main channel sedimentation rate play a leading role in flood generation during the time periods from 3400 to 2800 BP and 2000-1400 BP, respectively. These two periods of increased flooding are primarily caused by the erosional effects of increasing anthropogenic land use, whose contributions range from 33 % to 64 %. Furthermore, based on our modelling results, we suggest that the downstream propagation of the main flooding locations, from the Wei River to the lower reaches of the Yellow River, can be explained by the downstream migrating sediment wave. In conclusion, our simulation results give new insights into the causes of Holocene flooding periods in the middle Yellow River from the perspective of dynamic changes in catchment characteristics, which is helpful to improve regional flood risk management under future climate change and anthropogenic activities.

Intrapopulation germinability may help the Mediterranean plant species Poterium spinosum L. to cope with climate changes and landscape fragmentation.

Poterium spinosum L. is a key plant species forming typical shrub communities, distributed across the Mediterranean eastern coasts. The conservation of P. spinosum is thus of the utmost importance, especially due to the ever-increasing environmental pressures like climate changes and habitat fragmentation. This study, in particular, investigated for the first time the germination variability of P. spinosum at intrapopulation level, by analysing the germination behavior of five different subpopulations growing along the coasts of Sicily. For a more exhaustive picture of the main drivers of biodiversity loss affecting the distributional area of P. spinosum, the trends of climate and land-cover changes were also studied over the periods 1931-2020 and 1958-2018, respectively. The results found significant intrapopulation variability in P. spinosum, whose germination parameters showed that fruits and seeds from distinct subpopulations respond differently to diverse temperatures. Seeds showed generally higher values of final germination percentage (FGP) compared to fruits, and at higher temperatures: the highest FGP in seeds was 70% at 20 °C, whereas in fruits was 58.2% at 15 °C. The environmental threats showed worrying trends across the study area: during 1931-2020, the average temperature increased by 1.5 °C, whereas the average rainfall declined from 710 to 650 mm. Similarly, in the period 1958-2018, the analysis of the CORINE land-cover changes showed a highly fragmented agricultural landscape, where natural areas were reduced to 2.5-5.0%. Germination variability at intrapopulation level should be considered as a fundamental adaptation strategy, which can increase the reproductive success of P. spinosum under climate and land-cover changes.

Spatio-temporal assessment of landscape ecological risk using spatial statistical analysis in a basin of Turkiye.

Monitoring the land use/land cover (LU/LC) changes that have occurred with rapid population growth and urbanization since the Industrial Revolution is important for the optimal configuration of landscape patterns and ensuring the sustainability of ecological functions. Spatiotemporal dynamic pattern of LU/LC change using high-resolution land use data is an indicator to evaluate the landscape ecological risk through landscape pattern index analysis. In this study, the landscape ecological risk index (LERi) based on LU/LC change was calculated using remote sensing images of Landsat TM (Thematic Mapper) and OLI (Operational Land Imager) Rdata of a Gediz Mainstream Sub-basin in Turkiye between 1992 and 2022, and the spatial distribution regularity of LERi values was determined with spatial statistical analysis. According to the results, it was determined that the LERi values of the study area changed by 45% in 30 years. The highest change is in the very high-risk class, with an increase of 10.96%, and the least change occurred in the very low-risk class, with a decrease of 1.29%. According to the obtained statistical analysis results, it was determined that the global spatial autocorrelation values analyzed at different grain levels showed positive autocorrelation for both years and that the LERi values tended to have strong spatial clustering. As a result, it is emphasized that strict control measures should be taken for areas showing High-High (HH) autocorrelation type located in the southeast and north-southwest line of the study area at the local level, and ecological restoration applications should be given priority in these areas.

Using patterns of shared taxa to infer bacterial dispersal in human living environment in urban and rural areas.

Contact with environmental microbial communities primes the human immune system. Factors determining the distribution of microorganisms, such as dispersal, are thus important for human health. Here, we used the relative number of bacteria shared between environmental and human samples as a measure of bacterial dispersal and studied these associations with living environment and lifestyles. We analyzed amplicon sequence variants (ASVs) of the V4 region of 16S rDNA gene from 347 samples of doormat dust as well as samples of saliva, skin swabs, and feces from 53 elderly people in urban and rural areas in Finland at three timepoints. We first enumerated the ASVs shared between doormat and one of the human sample types (i.e., saliva, skin swab, or feces) of each individual subject and calculated the shared ASVs as a proportion of all ASVs in the given sample type of that individual. We observed that the patterns for the proportions of shared ASVs differed among seasons and human sample type. In skin samples, there was a negative association between the proportion of shared ASVs and the coverage of built environment (a proxy for degree of urbanization), whereas in saliva data, this association was positive. We discuss these findings in the context of differing species pools in urban and rural environments. IMPORTANCE: Understanding how environmental microorganisms reach and interact with humans is a key question when aiming to increase human contacts with natural microbiota. Few methods are suitable for studying microbial dispersal at relatively large spatial scales. Thus, we tested an indirect method and studied patterns of bacterial taxa that are shared between humans and their living environment.

Impact of Land use dynamics on the water yields in the Gorgan river basin.

This research investigates the future dynamics of water yield services in the Gorgan River Basin in the North of Iran by analyzing land cover changes from 1990 to 2020, using Landsat images and predicting up to 2040 with the Land Change Modeler and InVEST model under three scenarios: continuation, conservation, and mitigation. The results indicate significant shifts in agricultural land impacted water yields, which fluctuated from 324.7 million cubic meters (MCM) in 1990 to 279.7 MCM in 2010, before rising to 320.1 MCM by 2020. The study uniquely assesses the effects of land use changes on water yields, projecting a 13.6 % increase in water yield by 2040 under the continuation scenario, a 3.9 % increase under conservation, and a 1.6 % decrease under mitigation, which limits changes on steep slopes to prevent soil erosion and floods. This underscores the interplay between land use, vegetation cover, and water yield, emphasizing strategic land management for water resource preservation and effective watershed management in the GRB.

Assessment of water quality and identification of priority areas for intervention in Guanabara Bay basin, Rio de Janeiro, Brazil, using nonparametric and multivariate statistical methods.

The Guanabara Bay hydrographic region (GBHR) has served as a central hub for human settlement and resource utilization throughout Brazil's history. However, the region's high population density and intense industrial activity have come at a cost, leading to a significant decline in water quality. This work aimed to identify homogeneous regions in GBHR according to water quality parameters in dry and rainy periods. The following water quality monitoring variables were monitored at 49 gauge stations: total phosphorus (TP), nitrate (NO3-), dissolved oxygen (DO), hydrogenionic potential (pH), turbidity (Turb), thermotolerant coliforms (TCol), total dissolved solids (TDS), biochemical oxygen demand (BOD), water temperature (Tw), and air temperature (Ta). The statistical analysis consisted of determining principal components, cluster analysis, seasonal differences, and Spearman's correlation. The water quality parameter correlations were not expressively influenced by seasonality, but there are differences in the concentrations of these parameters in the dry and rainy periods. In the dry period, urban pressure on water quality is mainly due to fecal coliforms. The resulting clusters delimited areas under urban, agricultural, and forestry influence. Clusters located in areas with high demographic density showed high concentrations of TCol and TP, while clusters influenced by forestry and agriculture had better water quality. In the rainy season, clusters with urban influence showed problems with TCol and TP, in addition to some characteristics in each group, such as high TDS, NO3-, and BOD. Forested areas showed high DO, and clusters under agricultural influence had higher concentrations of TCol, BOD, and NO3- concerning forested regions. The troubling state of sanitation in GBHR occurs in metropolitan regions due to lack of a formal sanitation system.

Does the diversity of vegetation and diatoms correlate with soil and water factors in a tropical cloud forest's complex land use/land cover scenario?

Soil and water characteristics in micro basins with different land uses/land cover (LULC) can influence riparian vegetation diversity, stream water quality, and benthic diatom diversity. We analyzed 18 streams in the upper part of the La Antigua River basin, México, surrounded by cloud forests, livestock pastures, and coffee plantations. Concentrations of P, C, and N were elevated in the humus of forested streams compared to other land uses. In contrast, cations, ammonium, and total suspended solids (TSS) of water streams were higher in pastures and coffee plantations. These results indicate that LULC affects stream chemistry differently across land uses. Vegetation richness was highest (86-133 spp.) in forest streams and lowest in pastures (46-102), whereas pasture streams had the greatest richness of diatoms (9-24), likely due to higher light and temperatures. Some soil and water characteristics correlated with both true diversity and taxonomic diversity; soil carbon exchange capacity (CEC) correlated with vegetation diversity (r = 0.60), while water temperature correlated negatively (r = - 0.68). Diatom diversity was related to soil aluminum (r = - 0.59), magnesium (r = 0.57), water phosphorus (r = 0.88), and chlorophyll (r = 0.75). These findings suggest that land use affects riparian vegetation, while physical and chemical changes influence diatom diversity in stream water and soil. The lack of correlation between vegetation and diatom diversity indicates that one cannot predict the other. This research is an essential first step in understanding how land use changes impact vegetation and diatom diversity in mountain landscapes, providing valuable insights for environmental monitoring and conservation efforts in tropical cloud forests.

The urban air quality nexus: Assessing the interplay of land cover change and air pollution in emerging South Asian cities.

Air quality degradation presents a significant public health challenge, particularly in rapidly urbanizing regions where changes in land use/land cover (LULC) can dramatically influence pollution levels. This study investigates the association between LULC changes and air pollution (AP) in the five fastest-growing cities of Bangladesh from 1998 to 2021. Leveraging satellite data from Landsat and Sentinel-5P, the analysis reveals a substantial increase in urban areas and sparse vegetation, with declines in dense vegetation and water bodies over this period. Urban expansion was most pronounced in Sylhet (22-254%), while Khulna experienced the largest increase in sparse vegetation (2-124%). Dense vegetation loss was highest in Dhaka (20-77%) and water bodies (9-59%) over this period. Concentrations of six major air pollutants (APTs) - aerosol index, CO, HCHO, NO2, O3, and SO2 - were quantified, showing alarmingly high levels in densely populated industrial and commercial zones. Pearson's correlation indicates strong positive associations between APTs and urban land indices (R > 0.8), while negative correlations exist with vegetation indices. Geographically weighted regression modeling identifies city centers with dense urban built-up as pollution hotspots, where APTs exhibited stronger impacts on land cover changes (R2 > 0.8) compared to other land classes. The highest daily emissions were observed for O3 (1031 tons) and CO (356 tons) at Chittagong in 2021. In contrast, areas with substantial green cover displayed weaker pollutant-land cover associations. These findings underscore how unplanned urbanization drives AP by replacing natural land cover with emission sources, providing crucial insights to guide sustainable urban planning strategies integrating pollution mitigation and environmental resilience.