Unraveling spatial heterogeneity of soil legacy phosphorus in subtropical grasslands.

Humans have profoundly altered phosphorus (P) cycling across scales. Agriculturally driven changes (e.g., excessive P-fertilization and manure addition), in particular, have resulted in pronounced P accumulations in soils, often known as "soil legacy P." These legacy P reserves serve as persistent and long-term nonpoint sources, inducing downstream eutrophication and ecosystem services degradation. While there is considerable scientific and policy interest in legacy P, its fine-scale spatial heterogeneity, underlying drivers, and scales of variance remain unclear. Here we present an extensive field sampling (150-m interval grid) and analysis of 1438 surface soils (0-15 cm) in 2020 for two typical subtropical grassland types managed for livestock production: Intensively managed (IM) and Semi-natural (SN) pastures. We ask the following questions: (1) What is the spatial variability, and are there hotspots of soil legacy P? (2) Does soil legacy P vary primarily within pastures, among pastures, or between pasture types? (3) How does soil legacy P relate to pasture management intensity, soil and geographic characteristics? and (4) What is the relationship between soil legacy P and aboveground plant tissue P concentration? Our results showed that three measurements of soil legacy P (total P, Mehlich-1, and Mehlich-3 extractable P representing labile P pools) varied substantially across the landscape. Spatial autoregressive models revealed that soil organic matter, pH, available Fe and Al, elevation, and pasture management intensity were crucial predictors for spatial patterns of soil P, although models were more reliable for predicting total P (68.9%) than labile P. Our analysis further demonstrated that total variance in soil legacy P was greater in IM than SN pastures, and intensified pasture management rescaled spatial patterns of soil legacy P. In particular, after controlling for sample size, soil P was extremely variable at small scales, with variance diminished as spatial scale increased. Our results suggest that broad pasture- or farm-level best management practices may be limited and less efficient, especially for more IM pastures. Rather, management to curtail soil legacy P and mitigate P loading and losses should be implemented at fine scales designed to target spatially distinct P hotspots across the landscape.

Heterogeneity in post-fire thermal responses across Pacific Northwest streams: A multi-site study.

Over the past century, water temperatures in many streams across the Pacific Northwest (PNW) have steadily risen, shrinking endangered salmonid habitats. The warming of PNW stream reaches can be further accelerated by wildfires burning forest stands that provide shade to streams. However, previous research on the effect of wildfires on stream water temperatures has focused on individual streams or burn events, limiting our understanding of the diversity in post-fire thermal responses across PNW streams. To bridge this knowledge gap, we assessed the impact of wildfires on daily summer water temperatures across 31 PNW stream sites, where 10-100% of their riparian area burned. To ensure robustness of our results, we employed multiple approaches to characterize and quantify fire effects on post-fire stream water temperature changes. Averaged across the 31 burned sites, wildfires corresponded to a 0.3 - 1°C increase in daily summer water temperatures over the subsequent three years. Nonetheless, post-fire summer thermal responses displayed extensive heterogeneity across burned sites where the likelihood and rate of a post-fire summer water temperature warming was higher for stream sites with greater proportion of their riparian area burned under high severity. Also, watershed features such as basin area, post-fire weather, bedrock permeability, pre-fire riparian forest cover, and winter snowpack depth were identified as strong predictors of the post-fire summer water temperature responses across burned sites. Our study offers a multi-site perspective on the effect of wildfires on summer stream temperatures in the PNW, providing insights that can inform freshwater management efforts beyond individual streams and basins.

Identification of environmental and methodological factors driving variability of Pepper Mild Mottle Virus (PMMoV) across three wastewater treatment plants in the City of Toronto.

PMMoV has been widely used to normalize the concentration of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA, influenza, and respiratory syncytial virus (RSV) to account for variations in the fecal content of wastewater. PMMoV is also used as an internal RNA recovery control for wastewater-based epidemiology (WBE) tests. While potentially useful for the interpretation of WBE data, previous studies have suggested that PMMoV concentration can be affected by various physico-chemical characteristics of wastewater. There is also the possibility that laboratory methods, particularly the variability in centrifugation steps to remove supernatant from pellets can cause PMMoV variability. The goal of this study is to improve our understanding of the main drivers of PMMoV variability by assessing the relationship between PMMoV concentration, the physico-chemical characteristics of wastewater, and the methodological approach for concentrating wastewater samples. We analyzed 24-hour composite wastewater samples collected from the influent stream of three wastewater treatment plants (WWTPs) located in the City of Toronto, Ontario, Canada. Samples were collected 3 to 5 times per week starting from the beginning of March 2021 to mid-July 2023. The influent flow rate was used to partition the data into wet and dry weather conditions. Physico-chemical characteristics (e.g., total suspended solids (TSS), biological oxygen demand (BOD), alkalinity, electrical conductivity (EC), and ammonia (NH3)) of the raw wastewater were measured, and PMMoV was quantified. Spatial and temporal variability of PMMoV was observed throughout the study period. PMMoV concentration was significantly higher during dry weather conditions. Multiple linear regression analysis demonstrates that the number and type of physico-chemical parameters that drive PMMoV variability are site-specific, but overall BOD and alkalinity were the most important predictors. Differences in PMMoV concentration for a single WWTP between two different laboratory methods, along with a weak correlation between pellet mass and TSS using one method may indicate that differences in sample concentration and subjective subsampling bias could alter viral recovery and introduce variability to the data.

Improving the performance of macroinvertebrate based multi-metric indices by incorporating functional traits and an index performance-driven approach.

Human-driven multiple pressures impact freshwater ecosystems worldwide, reducing biodiversity, and impacting ecosystem functioning and services provided to human societies. Multi-metric indices (MMIs) are suitable tools for tracking the effects of anthropogenic pressures on freshwater ecosystems because they incorporate various biological metrics responding to multiple pressures at different levels of biological organization. However, the performance and applicability of MMIs depend on their metrics' selection and their calibration against natural environmental gradients. In this study, we aimed to unravel i) how incorporating functional trait-based metrics affects the performance of MMIs, ii) how disentangling the natural environmental gradients from anthropogenic pressures effects affects the performance of MMIs, and iii) how the performance of MMIs developed using a metric performance-driven approach compares with MMIs developed using an index performance-driven approach. We carried out a field survey measuring abiotic and biotic variables at 53 sites in the Karun River basin (Iran) in 2018. For functional trait-based metrics, we used 15 macroinvertebrate traits and calculated community-weighted mean trait values and functional diversity indices. We used random forest modeling to account for the effect of natural environmental gradients on each metric. Based on our results, incorporating functional traits increased the MMI performance significantly and facilitated ecological interpretation of MMIs. Both taxonomic and functional components of macroinvertebrate assemblages co-varied strongly with natural environmental gradients, and accounting for these covariations improved the performance of MMIs. Finally, we found that index performance-driven MMIs performed better in terms of precision, bias, sensitivity, and responsiveness than metric performance-driven MMIs.

Characterize and analysis of meteorological and hydrological drought trends under future climate change conditions in South Wollo, North Wollo, and Oromia Zones, in Ethiopia.

This research was conducted on North Wollo, South Wollo, and Oromia special zones, in Ethiopia. The study aimed to analyze the temporal and spatial variability of meteorological and hydrological drought trends using the selected drought indices and to predict its future trend in the selected areas. To achieve these objectives, meteorological and hydrological data were collected from the Ethiopian Meteorology Institute and the Ministry of Water and Energy respectively. The historical and future drought condition was analyzed by using the standardized precipitation index (SPI), reconnaissance drought index (RDI), and streamflow drought index (SDI) from the drought indicator calculator (DrinC) software. Based on the availability of the data, for historical drought analysis, ten meteorological stations with thirty-two years of daily data were selected. For the future scenario, RCP 4.5 was used to downscale the future climate data and to forecast SPI and RDI values. Also, an artificial neural network (ANN) was applied to forecast the future streamflow data using Python software, then the future hydrological drought was determined using the forecasted streamflow data. The result indicates that all zones were historically affected by severe to extreme droughts, especially 1984, 1986, 1987, 1989, 1991, 1992, 2003, 2007, 2010, 2013, and 2014 years. From 1984 to 1992 the probability of severe to extreme drought occurrence was on average of two years intervals and from 1992 to 2003 there is a huge gap. From the future drought analysis results, the probability of severe to extreme drought occurrence will be at five-year intervals on average. Based on the analyzed results, the frequency of severe to extreme drought occurrence of historical drought which was two and three years was increased to five years for the future conditions on average. But, these are short intervals and the magnitude of the event is very high. So, the regional water and energy office and other concerned bodies in the area have to plan a good drought mitigation mechanism and should develop a drought early warning system for the communities in and around the study area.

[Spatial Variability and Source Apportionment of PM2.5 Carbon Components in Tianjin].

The contents of eight carbonaceous subfractions were determined by simultaneously collecting PM2.5 samples from four sites in different functional areas of Tianjin in 2021. The results showed that the organic carbon (OC) concentration was 3.7 µg·m-3 to 4.4 µg·m-3, and the elemental carbon (EC) concentration was 1.6 µg·m-3 to 1.7 µg·m-3, with the highest OC concentration in the central urban area. There was no significant difference in EC concentration. The concentration of PM2.5 showed the distribution characteristics of the surrounding city>central city>peripheral area. The OC/EC minimum ratio method was used to estimate the concentrations of secondary organic carbon (SOC) in PM2.5, and the results showed that the secondary pollution was more prominent in the surrounding city, with SOC accounting for 48.8%. The correlation between carbon subcomponents in each functional area showed the characteristics of the peripheral area>central area>surrounding area, all showing the strongest correlation between EC1 and OC2 and EC1 and OC4. By including the carbon component concentration into the positive definite matrix factorization (PMF) model for source apportionment, the results showed that road dust sources(9.7%-23.5%), coal-combustion sources (10.2%-13.3%), diesel vehicle exhaust (12.6%-20.2%)and gasoline vehicle exhaust (18.9%-38.8%)were the main sources of carbon components in PM2.5 in Tianjin. The pollution sources of carbon components were different in different functional areas, with the central city and peripheral areas mainly affected by gasoline vehicle exhaust; the surrounding city was more prominently affected by the secondary pollution and diesel vehicle exhaust.

Variability of ambient air ammonia in urban Europe (Finland, France, Italy, Spain, and the UK).

This study addressed the scarcity of NH3 measurements in urban Europe and the diverse monitoring protocols, hindering direct data comparison. Sixty-nine datasets from Finland, France, Italy, Spain, and the UK across various site types, including industrial (IND, 8), traffic (TR, 12), urban (UB, 22), suburban (SUB, 12), and regional background (RB, 15), are analyzed to this study. Among these, 26 sites provided 5, or more, years of data for time series analysis. Despite varied protocols, necessitating future harmonization, the average NH3 concentration across sites reached 8.0 ± 8.9 µg/m3. Excluding farming/agricultural hotspots (FAHs), IND and TR sites had the highest concentrations (4.7 ± 3.2 and 4.5 ± 1.0 µg/m3), followed by UB, SUB, and RB sites (3.3 ± 1.5, 2.7 ± 1.3, and 1.0 ± 0.3 µg/m3, respectively) indicating that industrial, traffic, and other urban sources were primary contributors to NH3 outside FAH regions. When referring exclusively to the FAHs, concentrations ranged from 10.0 ± 2.3 to 15.6 ± 17.2 µg/m3, with the highest concentrations being reached in RB sites close to the farming and agricultural sources, and that, on average for FAHs there is a decreasing NH3 concentration gradient towards the city. Time trends showed that over half of the sites (18/26) observed statistically significant trends. Approximately 50 % of UB and TR sites showed a decreasing trend, while 30 % an increasing one. Meta-analysis revealed a small insignificant decreasing trend for non-FAH RB sites. In FAHs, there was a significant upward trend at a rate of 3.51[0.45,6.57]%/yr. Seasonal patterns of NH3 concentrations varied, with urban areas experiencing fluctuations influenced by surrounding emissions, particularly in FAHs. Diel variation showed differing patterns at urban monitoring sites, all with higher daytime concentrations, but with variations in peak times depending on major emission sources and meteorological patterns. These results offer valuable insights into the spatio-temporal patterns of gas-phase NH3 concentrations in urban Europe, contributing to future efforts in benchmarking NH3 pollution control in urban areas.

Integrated application of multiple indicators and geographic information system-based approaches for comprehensive assessment of environmental impacts of toxic metals-contaminated agricultural soils and vegetables.

Conventional monitoring and mapping approaches are laborious, expensive, and time-consuming because they need a large number of data and consequently extensive sampling and experimental operations. Therefore, due to the growing concern about the potential of contamination of soils and agricultural products with heavy metals (HMs), a field experiment was conducted on 77 farm lands in an area of 2300 ha in the southeast of Shiraz (Iran) to investigate the source of metal contamination in the soils and vegetables and to model spatial distribution of HMs (iron, Fe; manganese, Mn; copper, Cu; zinc, Zn; cadmium, Cd; nickel, Ni, and lead, Pb) over the region using geographic information system (GIS) and geostatistical (Ordinary Kriging, OK) approaches and compare the results with deterministic approaches (Inverse Distance Weighting, IDW with different weighting power). Furthermore, some ecological and health risks indices including Pollution index (PI), Nemerow integrated pollution index (NIPI), pollution load index (PLI), degree of contamination (Cdeg), modified contamination degree (mCd), PIaverage and PIvector for soil quality, multi-element contamination (MEC), the probability of toxicity (MERMQ), the potential ecological index (RI), total hazard index (THI) and total carcinogenic risk index (TCR) based on ingestion, inhalation, and dermal exposure pathways for adults and children respectively for analyzing the noncarcinogenic and carcinogenic risks were calculated. Experimental semivariogram of the mentioned HMs were calculated and theoretical models (i.e., exponential, spherical, Gaussian, and linear models) were fitted in order to model their spatial structures and to investigate the most representative models. Moreover, principal component analysis (PCA) and cluster analysis (CA) were used to identify sources of HMs in the soils. Results showed that IDW method was more efficient than the OK approach to estimate the properties and HMs contents in the soils and plants. The estimated daily intake of metals (DIM) values of Pb and Ni exceeded their safe limits. In addition, Cd was the main element responsible for ecological risk. The PIave and PIvector indices showed that soil quality in the study area is not suitable. According to mCd values, the soils classified as ultra-high contaminated for Cu and Cd, extremely high for Zn and Pb, very high, high, and very low degree of contamination for Ni, Mn, and Fe, respectively. 36, 60, and 4 % of the sampling sites had high, medium, and low risk levels with 49, 21, and 9 % probability of toxicity, respectively. The maximum health risk index (HRI) value of 20.42 with extremely high risk for children was obtained for Ni and the HI for adults and children were 0.22 and 1.55, respectively. The THI values of Pb and Cd were the highest compared to the other HMs studied, revealing a possible non-cancer risk in children associated with exposure to these metals. The routes of exposure with the greatest influence on the THI and TCR indices were in the order of ingestion > inhalation > dermal. Therefore, ingestion, as the main route of exposure, is the route of greatest contribution to health risks. PCA analysis revealed that Fe, Mn, Cu, and Ni may originate from natural sources, while Fe was appeared to be controlled by fertilizer, and Cu primarily coming from pesticide, while Cd and Pb were mainly associated with the anthropogenic contamination, atmospheric depositions, and terrific in the urban soils. While, Zn mainly originated from fertilization. Findings are vital for developing remediation approaches for controlling the contaminants distribution as well as for monitoring and mapping the quality and health of soil resources.

Identifying childhood malaria hotspots and risk factors in a Nigerian city using geostatistical modelling approach.

Malaria ranks high among prevalent and ravaging infectious diseases in sub-Saharan Africa (SSA). The negative impacts, disease burden, and risk are higher among children and pregnant women as part of the most vulnerable groups to malaria in Nigeria. However, the burden of malaria is not even in space and time. This study explores the spatial variability of malaria prevalence among children under five years (U5) in medium-sized rapidly growing city of Akure, Nigeria using model-based geostatistical modeling (MBG) technique to predict U5 malaria burden at a 100 × 100 m grid, while the parameter estimation was done using Monte Carlo maximum likelihood method. The non-spatial logistic regression model shows that U5 malaria prevalence is significantly influenced by the usage of insecticide-treated nets-ITNs, window protection, and water source. Furthermore, the MBG model shows predicted U5 malaria prevalence in Akure is greater than 35% at certain locations while we were able to ascertain places with U5 prevalence > 10% (i.e. hotspots) using exceedance probability modelling which is a vital tool for policy development. The map provides place-based evidence on the spatial variation of U5 malaria in Akure, and direction on where intensified interventions are crucial for the reduction of U5 malaria burden and improvement of urban health in Akure, Nigeria.

Multiple Probe Measurements at Uranus Motivated by Spatial Variability.

A major motivation for multiple atmospheric probe measurements at Uranus is the understanding of dynamic processes that create and maintain spatial variation in thermal structure, composition, and horizontal winds. But origin questions-regarding the planet's formation and evolution, and conditions in the protoplanetary disk-are also major science drivers for multiprobe exploration. Spatial variation in thermal structure reveals how the atmosphere transports heat from the interior, and measuring compositional variability in the atmosphere is key to ultimately gaining an understanding of the bulk abundances of several heavy elements. We review the current knowledge of spatial variability in Uranus' atmosphere, and we outline how multiple probe exploration would advance our understanding of this variability. The other giant planets are discussed, both to connect multiprobe exploration of those atmospheres to open questions at Uranus, and to demonstrate how multiprobe exploration of Uranus itself is motivated by lessons learned about the spatial variation at Jupiter, Saturn, and Neptune. We outline the measurements of highest value from miniature secondary probes (which would complement more detailed investigation by a larger flagship probe), and present the path toward overcoming current challenges and uncertainties in areas including mission design, cost, trajectory, instrument maturity, power, and timeline.

Cross-scale spatial variability and associations of carbon pools provide insight into regulating carbon sequestration in tropical montane rainforests.

The spatial distribution of plant, soil, and microbial carbon pools, along with their intricate interactions, presents a great challenge for the current carbon cycle research. However, it is not clear what are the characteristics of the spatial variability of these carbon pools, particularly their cross-scale relationships. We investigated the cross-scale spatial variability of microbial necromass carbon (MNC), soil organic carbon (SOC) and plant biomass (PB), as well as their correlation in a tropical montane rainforest using multifractal analysis. The results showed multifractal spatial variations of MNC, SOC, and PB, demonstrating their adherence to power-law scaling. MNC, especially low MNC, exhibited stronger spatial heterogeneity and weaker evenness compared with SOC and PB. The cross-scale correlation between MNC and SOC was stronger than their correlations at the measurement scale. Furthermore, the cross-scale spatial variability of MNC and SOC exhibited stronger and more stable correlations than those with PB. Additionally, this research suggests that when SOC and PB are both low, it is advisable for reforestations to potentiate MNC formation, whereas when both SOC and PB are high some thinning can be advisable to favour MNC formation. Thus, these results support the utilization of management measures such as reforestation or thinning as nature-based solutions to regulate carbon sequestration capacity of tropical forests by affecting the correlations among various carbon pools.

Spatial variability in herbaceous plant phenology is mostly explained by variability in temperature but also by photoperiod and functional traits.

Whereas temporal variability of plant phenology in response to climate change has already been well studied, the spatial variability of phenology is not well understood. Given that phenological shifts may affect biotic interactions, there is a need to investigate how the variability in environmental factors relates to the spatial variability in herbaceous species' phenology by at the same time considering their functional traits to predict their general and species-specific responses to future climate change. In this project, we analysed phenology records of 148 herbaceous species, which were observed for a single year by the PhenObs network in 15 botanical gardens. For each species, we characterised the spatial variability in six different phenological stages across gardens. We used boosted regression trees to link these variabilities in phenology to the variability in environmental parameters (temperature, latitude and local habitat conditions) as well as species traits (seed mass, vegetative height, specific leaf area and temporal niche) hypothesised to be related to phenology variability. We found that spatial variability in the phenology of herbaceous species was mainly driven by the variability in temperature but also photoperiod was an important driving factor for some phenological stages. In addition, we found that early-flowering and less competitive species characterised by small specific leaf area and vegetative height were more variable in their phenology. Our findings contribute to the field of phenology by showing that besides temperature, photoperiod and functional traits are important to be included when spatial variability of herbaceous species is investigated.

Spatial and temporal variations of microclimate and outdoor thermal comfort in informal settlements of warm humid Dar es Salaam, Tanzania.

In developing countries, urbanization is dominated by the growth of informal settlements which represents 40-80% of major cities. The challenges brought up by the growth of informal settlements spans from social-economic to environmental. Previously, upgrading of the informal settlements focused on social-economic aspects such as provision of necessary services for the residents, whereas the quality of the outdoor thermal environment has not received much attention. This paper entails to investigate the potential of upgrading the outdoor thermal environment in informal settlements in the warm humid city of Dar es Salaam, Tanzania through examining the influence of addition of trees with different Leaf Area Index (LAI) and incremental increase of buildings heights. The study uses simulation as a method for analysis of the warm season and calculates the Physiological Equivalent Temperature (PET) as a thermal index. Results show substantial improvement of both microclimate and outdoor thermal comfort. Incremental increase of buildings heights in a street canyon to 12, 18, and 24 m leads to the reduction of PET by 2.5, 2.8, and 3.8 °C respectively at 2:00 p.m. Similarly, applying LAI's of 2, 4, and 6 m2/m2 leads to reduction of the mean radiant temperature by 7.9, 10.1, and 12.2 °C; while PET was reduced by 3.9, 4.7, and 5.6 °C respectively at 2:00 p.m. Nonetheless, upgrading of informal settlements shows marginal influence on the reduction of air temperature. Despite the noted thermal improvement in the studied area, the thermal comfort limits of the warm season were difficult to reach. The findings suggest that addition of vegetation is the economically most effective way for upgrading thermal conditions in informal urban fabric areas.

Impacts of recent rainfall changes on agricultural productivity and water resources within the Southern Western Ghats of Kerala, India.

Significant changes in rainfall patterns are critical to agriculture, and the dependency of cropping systems on rainfall variability would engender appropriate farming practices and agriculture policies for a climate-resilient agriculture system. This study analyses the significance of rainfall variability on agriculture productivity in the Wayanad district of Kerala (India) using time series data on rainfall (1989-2019) and crop yield (2000-2019). The spatial variability of rainfall patterns reveals a dichotomy between the rain gauge stations in the northern and southern parts of the region. Despite the absence of statistically significant trends in the monthly, seasonal and annual rainfall, based on the Mann-Kendall trend analysis, an increase in the yield of many crops (e.g., winter paddy, banana) is evident, which emphasises the critical role of irrigation in driving the crop productivity. As an adaptation strategy to changing rainfall patterns, irrigation would meet the additional crop water requirement for sustainable agricultural production under the varying rainfall distributions. However, the increase in the area under irrigation in recent years has had significant implications for both surface water and groundwater resources. The conclusive findings suggest that the region requires climate-resilient agriculture, focusing on optimising irrigation and developing sustainable agriculture and water conservation strategies.

Biodiversity patterns of the benthic macrofaunal communities across the intertidal sedimentary shores of two Antarctic islands.

Antarctic benthic ecosystems support a unique fauna characterized by high levels of diversity and endemism. However, our knowledge of the macrofauna communities across the Antarctic intertidal sedimentary shore is limited, and their fundamental ecological features, including spatial variability, remain poorly understood. This study aimed to investigate the abundance, community structure (i.e. taxa-specific abundance), and biodiversity patterns (α-, ß-, and λ-diversity) of benthic macrofauna communities on intertidal sedimentary shores of two Antarctic islands (South Shetland archipelago, N of Antarctic Peninsula): Livingston and Deception. We conducted a quantitative sampling during two Austral summer campaigns (2004 and 2005), studying eleven intertidal sites, with five sites located on Livingston and six on Deception. Our results demonstrated a significantly higher abundance of intertidal benthic macrofauna communities on Livingston than on Deception. Furthermore, significant differences in community structure were observed between the two islands. In terms of biodiversity patterns, there were no significant differences in the number of taxa within communities (α-diversity) between the two islands. However, significant differences in the variation of community composition (determined by the number and identity of taxa) between intertidal sites (ß-diversity) were observed, shedding light on the higher total taxa count (λ-diversity) on Livingston compared to Deception. We suggest that the island-specific characteristics (e.g., granulometric characteristics, ice disturbance, sedimentation rates, and geothermal activity) determine the differences observed in macrofauna communities. However, other ecological processes and factors are operating on different spatial and temporal scales (e.g., population dynamics, biotic interactions, oceanographic conditions, and climate change) that influence the occurrence and abundance of macrofaunal taxa. Our findings contribute to the fundamental understanding of the spatial variability of these communities and provide essential information for better management decisions and conservation practices in Antarctic coastal ecosystems.

Groundwater quality index development using the ANN model of Delhi Metropolitan City, India.

Groundwater is widely recognized as a vital source of fresh drinking water worldwide. However, the rapid, unregulated population growth and increased industrialization, coupled with a rise in human activities, have significantly harmed the quality of groundwater. Changes in the local topography and drainage systems in an area have negative impacts on both the quality and quantity of groundwater. This underscores the critical need to assess the susceptibility of groundwater to pollution and implement measures to mitigate these risks. The water quality index (WQI) is an approach that simulates the water quality at peculiar locations for a particular period of time. The artificial neural network (ANN) model approach is such an idealistic methodology that can be utilized for WQI development and provides better results for specific locations in optimum time. Therefore, the goal of the current study is to provide a unique way for using artificial neural networks (ANN) to characterize the groundwater quality of Delhi Metropolitan City, India. In order to make the water fit for residential and drinking use, the research also pinpoints the geographical variability and spots where the contaminated region has to be sufficiently cleaned. A minimum WQI of 41.51 was obtained at the Jagatpur location while a maximum value of 779.01 was at the Peeragarhi location. During the training phase, the results obtained using the ANN model were highly favorable, demonstrating a strong association with an R-value of 98.10%, thus highlighting the program's exceptional efficiency. However, in accordance with the correlation regression findings, the prediction outcomes of the ANN model in testing are observed to be an R-value of 99.99-100%. This study confirms the promise and advantages of employing advanced artificial intelligence in managing groundwater quality in the studied area.

Dietary selenium intake among Ethiopian children in areas known for selenium spatial variability.

Introduction: There is spatial variability of selenium (Se) in soil and crops in Ethiopia. We assessed the Se content of food items, breast milk, and urine among infants in Ethiopia from two areas with contrasting Se concentrations in soils. Methods: Dietary Se intakes among children (6-23 months) were evaluated using a weighed food record on two non-consecutive days. Also, spot urine samples from children and breast milk samples from their mothers were collected to determine Se concentration. Selenium concentrations in the samples were analyzed using an inductively coupled plasma mass spectrometer (ICP-MS). Results: Injera (prepared from teff and mixtures of other cereals) with a legume-based stew were the most frequently consumed foods by the children in both areas, followed by pasta. Overall, the Se concentration (mean ± SD) of food items, breast milk (12.2 ± 3.9 µg/L vs. 3.39 ± 1.5 µg/L), and urine samples (22.5 ± 11.5 µg/L vs. 3.0 ± 1.9 µg/L) from East Amhara were significantly higher than the corresponding samples from West Amhara (p < 0.001). The total Se intakes by the study children from East Amhara and West Amhara were 30.2 [IQ 25%, 14.2; IQ 75%, 54.1] and 7.4 [IQR 25%, 4.2; IQ 75%, 10.6] µg day-1, respectively; 31.5% of children from East Amhara and 92% of children from West Amhara were at risk of inadequate Se intakes. Urinary Se excretion accounted for 53 and 39% of daily dietary Se intake in East Amhara and West Amhara, respectively. Dietary Se intake was positively correlated with urinary Se excretion in East Amhara (r = 0.56; p < 0.001) but not among samples from West Amhara (r = 0.16; p ≥ 0.05), suggesting greater physiological Se conservation in a state of deficiency. Conclusion: There is spatial variability of Se in foods, breast milk, and urine in Ethiopia, suggesting the need for implementation of targeted agronomic interventions that enhance Se concentrations in the edible portion of plant foods.

Latitudinal and meridional patterns of picophytoplankton variability are contrastingly associated with Ekman pumping and the warm pool in the tropical western Pacific.

Marine picophytoplankton plays a major role in marine cycling and energy conversion, and its effects on the carbon cycle and global climate change have been well documented. In this study, we investigated the response of picophytoplankton across a broad range of physicochemical conditions in two distinct regions of the tropical western Pacific. Our analysis considered the abundance, carbon biomass, size fraction, distribution, and regulatory factors of the picophytoplankton community, which included the cyanobacteria Prochlorococcus and Synechococcus, and small eukaryotic phytoplankton (picoeukaryotes). The first region was a latitudinal transect along the equator (142-163° E, 0° N), characterized by stratified oligotrophic conditions. The second region was a meridional transect (143° E, 0-22° N) known for its high-nutrient and low-chlorophyll (HNLC) conditions. Results showed that picophytoplankton contributed >80% of the chlorophyll a (Chl a), and was mainly distributed above 100 m. Prochlorococcus was the dominant organism in terms of cell abundance and estimated carbon biomass in both latitudinal and meridional transects, followed by Synechococcus and picoeukaryotes. In the warm pool, Prochlorococcus was primarily distributed below the isothermal layer, with the maximum subsurface abundance forming below it. The maximum Synechococcus abundance was restricted to the west-warm pool, due to the high temperature, and the second-highest Synechococcus abundance was associated with frontal interaction between the east-warm pool and the westward advance of Middle East Pacific water. In contrast, picoeukaryotes formed a maximum subsurface abundance corresponding to the subsurface Chl a maximum. In the mixed HNLC waters, the cell abundance and biomass of the three picophytoplankton groups were slightly lower than those in the warm pool. Due to a cyclonic eddy, the contours of the maximum subsurface Prochlorococcus abundance were uplifted, evidently with a lower value than the surrounding water. Synechococcus abundance varied greatly in patches, forming a weakly high subsurface peak when the isothermal layer rose to the near-surface (<50 m). The subsurface maximum picoeukaryote abundance was also highly consistent with that of the subsurface Chl a maximum. Correlation analysis and generalized additive models of environmental factors showed that nutrient availability had a two-faceted role in regulating the spatial patterns of picophytoplankton in diverse latitudinal and meridional environments. We concluded through regression that temperature and light irradiance were the key determinants of picophytoplankton variability in the tropical western Pacific. This study provides insights into the changing picophytoplankton community structure with potential future changing hydroclimatic force.

Temporal and spatial distribution of soil water repellency in grassland soils and its relation to soil moisture, hydrophobic matter, and particle size.

In grassland soils, soil water repellency (SWR) may be one of the triggers of soil erosion and degradation as it can reduce water infiltration and penetration into the soil. Few studies were focusing on the evaluation of soil hydro-physical properties, such as hydrophobicity, and their relation to soil moisture, hydrophobic matter, and particle size in grassland soils. In this study, 800 soil samples were collected from the Xilingol grassland in Inner Mongolia, China, using the water droplet penetration time (WDPT) test to evaluate water repellency and we aimed to investigate the temporal and spatial distribution of SWR in grassland soils using the Kriging and Inverse Distance Weighting (IDW) interpolation methods and determine the physical-chemical properties that trigger the SWR. The results showed that the grassland soils in the studied area were slightly water-repellent and a few portions of the area exhibited strong water-repellency. In April, areas of soils with a depth of 0-5 cm and slight to strong SWR accounted for 80 % of the total studied area, of which 5 % had strong water repellency. Moreover, in August, 90 % of the studied area consisted of soils with slight to strong SWR, of which 60 % accounted for soils with strong SWR. With a soil water content of 10.95 %, the SWR reached its peak, with an average value of 60.32 s. The SWR was positively correlated with total N, available N, and soil organic matter (SOM) contents, and therein the hydrophobic acid matter and the hydrophobic basic matter content had a positive contribution to SWR, and the hydrophilic basic matter and the hydrophilic acidic matter had a negative contribution on SWR. In addition, SWR was found to be negatively related to the soil particle size (r = -0.672). A slight SWR was also observed in the majority of the studied area, particularly in the topsoil and fine soils, especially during the monsoon period; hence, SWR must be also considered to reduce the risk of occurrence of soil erosion and degradation in grasslands.

Optimizing phosphorus fertigation management zones using electromagnetic induction, soil properties, and crop yield data under semi-arid conditions.

The impact of climate change on water resource availability and soil quality is more and more emphasized under the Mediterranean basin, mostly characterized by drought and extreme weather conditions. The present study aims to investigate how electromagnetic induction technique and soil mapping combined with crop yield data can be used to optimize phosphorus (P) use efficiency by chickpea crop under drip fertigation system. The study was carried out on a 2.5-ha agricultural plot and the agronomic experiments in two growing cycles of chickpea crop. Soil spatial variability was first assessed by the measurement of soil apparent electrical conductivity (ECa) using the CMD Mini-Explorer sensor, and then, soil physicochemical properties were evaluated based on an oriented soil sampling scheme to explore other soil spatial variabilities influencing chickpea yield and quality. Data from the first agronomic experiment were used in geostatistical, multiple linear regression (MLR), and fuzzy c-means unsupervised classification algorithms to properly identify P drip fertigation management zones (MZs). Results from the Person's correlation analysis revealed that chickpea grain yield was more influenced by soil ECa (r = - 0.56), pH (r = - 0.84), ECe (r = - 0.6), P content (r = 0.72), and calcium (Ca) content (r = - 0.83). The proposed MLR-based model to predict chickpea grain yield showed good performances with a normalized root mean square error (NRMSE) of 0.11% and a coefficient of determination (R2) equal to 0.69. The identified MZs were verified by the one-way variance analysis for the studied soil and plant attributes, revealing that the first MZ1 presents a high grain yield, high soil P content, and low ECa. The low fertility MZ2 located in the south part of the studied site presented a low chickpea grain yield due to the low P content and the high ECa. Moreover, the application of P-variable rate fertigation regimes in the second field experiment significantly improved P use efficiency, chickpea grain yield, seed quality, and farmer income by 18%, 12%, 9%, and 136 $/ha, respectively, as compared to the conventional drip fertigation practices. The approach proposed in this study can greatly contribute to optimizing agro-input use efficiency under drip fertigation system, thereby improving farmers' incomes, preserving the ecosystem, and ensuring sustainable cropping systems in the Mediterranean climate.