The study characterized the temporal and spatial variability in greenhouse gas (GHG) fluxes (CO2, CH4, and N2O) between December 2020 and November 2021 and their regulating drivers in the subtropical wetland of the Indian Himalayan foothill. Five distinct habitats (M1-sloppy surface at swamp forest, M2-plain surface at swamp forest, M3-swamp surface with small grasses, M4-marshy land with dense macrophytes, and M5-marshy land with sparse macrophytes) were studied. We conducted in situ measurements of GHG fluxes, microclimate (AT, ST, and SMC(v/v)), and soil properties (pH, EC, N, P, K, and SOC) in triplicates in all the habitat types. Across the habitats, CO2, CH4, and N2O fluxes ranged from 125 to 536 mg m-2 h-1, 0.32 to 28.4 mg m-2 h-1, and 0.16 to 3.14 mg m-2 h-1, respectively. The habitats (M3 and M5) exhibited higher GHG fluxes than the others. The CH4 flux followed the summer > autumn > spring > winter hierarchy. However, CO2 and N2O fluxes followed the summer > spring > autumn > winter. CO2 fluxes were primarily governed by ST and SOC. However, CH4 and N2O fluxes were mainly regulated by ST and SMC(v/v) across the habitats. In the case of N2O fluxes, soil P and EC also played a crucial role across the habitats. AT was a universal driver controlling all GHG fluxes across the habitats. The results emphasize that long-term GHG flux monitoring in sub-tropical Himalayan Wetlands has become imperative to accurately predict the near-future GHG fluxes and their changing nature with the ongoing climate change.

Although many studies have discussed the impact of Europe\'s air quality, very limited research focused on the detailed phenomenology of ambient trace elements (TEs) in PM10 in urban atmosphere. This study compiled long-term (2013-2022) measurements of speciation of ambient urban PM10 from 55 sites of 7 countries (Switzerland, Spain, France, Greece, Italy, Portugal, UK), aiming to elucidate the phenomenology of 20 TEs in PM10 in urban Europe. The monitoring sites comprised urban background (UB, n = 26), traffic (TR, n = 10), industrial (IN, n = 5), suburban background (SUB, n = 7), and rural background (RB, n = 7) types. The sampling campaigns were conducted using standardized protocols to ensure data comparability. In each country, PM10 samples were collected over a fixed period using high-volume air samplers. The analysis encompassed the spatio-temporal distribution of TEs, and relationships between TEs at each site. Results indicated an annual average for the sum of 20 TEs of 90 ± 65 ng/m3, with TR and IN sites exhibiting the highest concentrations (130 ± 66 and 131 ± 80 ng/m3, respectively). Seasonal variability in TEs concentrations, influenced by emission sources and meteorology, revealed significant differences (p < 0.05) across all monitoring sites. Estimation of TE concentrations highlighted distinct ratios between non-carcinogenic and carcinogenic metals, with Zn (40 ± 49 ng/m3), Ti (21 ± 29 ng/m3), and Cu (23 ± 35 ng/m3) dominating non-carcinogenic TEs, while Cr (5 ± 7 ng/m3), and Ni (2 ± 6 ng/m3) were prominent among carcinogenic ones. Correlations between TEs across diverse locations and seasons varied, in agreement with differences in emission sources and meteorological conditions. This study provides valuable insights into TEs in pan-European urban atmosphere, contributing to a comprehensive dataset for future environmental protection policies.

Urbanization, agriculture, and climate change affect water quality and water hyacinth growth in lakes. This study examines the spatiotemporal variability of lake surface water temperature, turbidity, and chlorophyll-a (Chl-a) and their association with water hyacinth biomass in Lake Tana. MODIS Land/ Lake surface water temperature (LSWT), Sentinel 2 MSI Imagery, and in-situ water quality data were used. Validation results revealed strong positive correlations between MODIS LSWT and on-site measured water temperature (R = 0.90), in-situ turbidity and normalized difference turbidity index (NDTI) (R = 0.92), and in-situ Chl-a and normalized difference chlorophyll index (NDCI) (R = 0.84). LSWT trends varied across the lake, with increasing trends in the northeastern, northwestern, and southwestern regions and decreasing trends in the western, southern, and central areas (2001-2022). The spatial average LSWT trend decreased significantly in pre-rainy (0.01 ℃/year), rainy (0.02 ℃/year), and post-rainy seasons (0.01℃/year) but increased non-significantly in the dry season (0.00 ℃/year) (2001-2022, P < 0.05). Spatial average turbidity decreased significantly in all seasons, except in the pre-rainy season (2016-2022). Likewise, spatial average Chl-a decreased significantly in pre-rainy and rainy seasons, whereas it showed a non-significant increasing trend in the dry and post-rainy seasons (2016-2022). Water hyacinth biomass was positively correlated with LSWT (R = 0.18) but negatively with turbidity (R = -0.33) and Chl-a (R = -0.35). High spatiotemporal variability was observed in LSWT, turbidity, and Chl-a, along with overall decreasing trends. The findings suggest integrated management strategies to balance water hyacinth eradication and its role in water purification. The results will be vital in decision support systems and preparing strategic plans for sustainable water resource management, environmental protection, and pollution prevention.

Temporal lobe epilepsy (TLE) stands as the predominant adult focal epilepsy syndrome, characterized by dysfunctional intrinsic brain dynamics. However, the precise mechanisms underlying seizures in these patients remain elusive. Our study encompassed 116 TLE patients compared with 51 healthy controls. Employing microstate analysis, we assessed brain dynamic disparities between TLE patients and healthy controls, as well as between drug-resistant epilepsy (DRE) and drug-sensitive epilepsy (DSE) patients. We constructed dynamic functional connectivity networks based on microstates and quantified their spatial and temporal variability. Utilizing these brain network features, we developed machine learning models to discriminate between TLE patients and healthy controls, and between DRE and DSE patients. Temporal dynamics in TLE patients exhibited significant acceleration compared to healthy controls, along with heightened synchronization and instability in brain networks. Moreover, DRE patients displayed notably lower spatial variability in certain parts of microstate B, E and F dynamic functional connectivity networks, while temporal variability in certain parts of microstate E and G dynamic functional connectivity networks was markedly higher in DRE patients compared to DSE patients. The machine learning model based on these spatiotemporal metrics effectively differentiated TLE patients from healthy controls and discerned DRE from DSE patients. The accelerated microstate dynamics and disrupted microstate sequences observed in TLE patients mirror highly unstable intrinsic brain dynamics, potentially underlying abnormal discharges. Additionally, the presence of highly synchronized and unstable activities in brain networks of DRE patients signifies the establishment of stable epileptogenic networks, contributing to the poor responsiveness to antiseizure medications. The model based on spatiotemporal metrics demonstrated robust predictive performance, accurately distinguishing both TLE patients from healthy controls and DRE patients from DSE patients.

The water quality evolution of surface and groundwater caused by mining activities and mine drainage is a grave public concern worldwide. To explore the effect of mine drainage on sulfate evolution, a multi-aquifer system in a typical coal mine in Northwest China was investigated using multi-isotopes (δ34SSO4, δ18OSO4, δD, and δ18Owater) and Positive Matrix Factorization (PMF) model. Before mining, the Jurassic aquifer was dominated by gypsum dissolution, accompanied by cation exchange and bacterial sulfate reduction, and the phreatic aquifers and surface water were dominated by carbonate dissolution. Significant increase in sulfate in phreatic aquifers due to mine drainage during the early stages of coal mining. However, in contrast to common mining activities that result in sulfate contamination from pyrite oxidation, mine drainage in this mining area resulted in accelerated groundwater flow and enhanced hydraulic connections between the phreatic and confined aquifers. Dilution caused by the altered groundwater flow system controlled the evolution of sulphate, leading to different degrees of sulfate decrease in all aquifers and surface water. As the hydrogeochemical characteristic of Jurassic aquifer evolved toward phreatic aquifer, this factor should be considered to avoid misjudgment in determining the source of mine water intrusion. The study reveals the hydrogeochemical evolution induced by mine drainage, which could benefit to the management of groundwater resources in mining areas.

Uncovering the spatiotemporal features of ecosystem services (ESs) and their intricate interrelations in large lake basins can facilitate the development of scientific management measures for various ESs. Previous studies have focused less on watershed units and their historical dynamics, and the ecosystem service (ES) driving mechanisms remain unclear. Here, we focused on Hunan Province-the main coverage area of the Dongting Lake Basin (China\'s second largest freshwater lake), investigated the spatiotemporal characteristics of seven typical ESs and their interactions, identified the ecosystem service bundle (ESB) historical spatial patterns and revealed the socio-ecological driving mechanisms of these ES changes. Results showed that: (1) the spatial distribution of most ESs remained stable in the basin. Food production (FP), water yield (WY), soil conservation (SC) and net primary productivity (NPP) improved over time, whereas nitrogen retention (NR), habitat quality (HQ) and outdoor recreation (OR) declined; (2) tradeoffs were observed between food production and most ESs, whereas synergistic relationships between all ESs except food production. The tradeoff relationship between food production and water yield increased significantly over time, while the synergistic relationship between water yield and nitrogen retention decreased significantly; (3) five ecosystem service bundles were identified. And the transformation of soil conservation area into integrated ecological regulation area mainly occurred from 2000 to 2020, resulting in an increase in the function of ecological regulation services; (4) natural conditions such as precipitation, topography and vegetation, as well as socio-economic factors such as Gross Domestic Product (GDP) and population, were key factors affecting ESs. The interactions among most of these drivers can further elucidate the ES changes. Our results emphasize the need for a watershed-based assessment and a historical dynamic perspective in the sustainable management of ESs.

This study investigated the spatiotemporal distribution of the phytoplankton in the coral habitat of Dongshan Bay (China), along with critical factors affecting the distribution, during June, August, and December 2022. Phytoplankton abundance in Dongshan Bay exhibited considerably temporal variation, peaking in June 2022, gradually decreasing thereafter, and reaching its lowest point in December 2022. The abundance of bottom-layer phytoplankton consistently exceeded that of the surface layer throughout all seasons. The average phytoplankton abundance in the coral habitat of Dongshan Bay was lower than that in non-coral habitat areas. Fluctuations in the Zhangjiang River and coastal upwelling influenced the diversity and community structure of the phytoplankton. Critical factors causing spatiotemporal variability in phytoplankton community structure included nutrient concentrations and seawater temperature. Nutrients played key roles in influencing various phytoplankton groups. Dominant diatom species, such as Thalassionema nitzschioides and Thalassiosira diporocyclus, were positively correlated with ammonia nitrogen, seawater salinity, coral cover, and the number of coral species present. In winter, Calanus sinicus exhibited a negative correlation with harmful algal bloom species. Additionally, it was found that both in the coral habitat and surrounding open sea, currents, nutrients, and zooplankton may play crucial roles in determining the spatiotemporal variability in the phytoplankton community structure.

Climate refugia are areas where species can persist through climate change with little to no movement. Among the factors associated with climate refugia are high spatial heterogeneity, such that there is only a short distance between current and future optimal climates, as well as biotic or abiotic environmental factors that buffer against variability in time. However, these types of climate refugia may be declining due to anthropogenic homogenization of environments and degradation of environmental buffers. To quantify the potential for restoration of refugia-like environmental conditions to increase population persistence under climate change, we simulated a population\'s capacity to track their temperature over space and time given different levels of spatial and temporal variability in temperature. To determine how species traits affected the efficacy of restoring heterogeneity, we explored an array of values for species\' dispersal ability, thermal tolerance, and fecundity. We found that species were more likely to persist in environments with higher spatial heterogeneity and lower environmental stochasticity. When simulating a management action that increased the spatial heterogeneity of a previously homogenized environment, species were more likely to persist through climate change, and population sizes were generally higher, but there was little effect with mild temperature change. The benefits of heterogeneity restoration were greatest for species with limited dispersal ability. In contrast, species with longer dispersal but lower fecundity were more likely to benefit from a reduction in environmental stochasticity than an increase in spatial heterogeneity. Our results suggest that restoring environments to refugia-like conditions could promote species\' persistence under the influence of climate change in addition to conservation strategies such as assisted migration, corridors, and increased protection.

Climate-sensitive ice-covered reservoirs are critical components of methane (CH4) release. However, the mechanisms that influence CH4 dynamics during ice-covered periods remain poorly studied. To investigate the effects of bubbles on CH4 dynamics, we conducted intensive field and incubation experiments in an ice-covered reservoir (ice growth, stability, and melt period) in Northeast China. We found that the mean dissolved CH4 concentrations in the ice (625.9 ± 2419.7 nmol L-1) and underlying water (1218.9 ± 2678.9 nmol L-1) were high, making them atmosphere CH4 sources. The visible bubble bands (bubble area) in the riverine zone and the vertical profile of the CH4 concentration in the ice reflect the distribution of trapped bubbles. The mean CH4 concentration in the ice of the bubble area (1674.8 ± 3926.8 nmol L-1) was 2 orders of magnitude higher than that of no-bubble area (53.7 ± 9.2 nmol L-1). Moreover, a large amount of CH4 accumulated under the ice in the bubble area. These findings suggest that bubbles determine the CH4 storage in ice and CH4 accumulation in the underlying water. Ice growth increases CH4 storage in ice and the underlying water because of the entrapment and re-dissolution of CH4 bubbles. However, ice melting releases the CH4 accumulated in the ice and underlying water. A comparison of the field and incubation experiments indicated that the deep-water environment of the reservoir had a CH4 burial effect. Stepwise regression analysis revealed that higher sediment organic matter content, median particle size, and porosity increased the production and release of CH4 bubbles, trapping more CH4 bubbles in ice. Overall, this study improves the mechanistic understanding of CH4 dynamics and predictability of CH4 emissions during ice-covered periods.

Oil exploitation may pose adverse effects on marine ecosystems, but its impacts on surface carbonate dynamics remain unknown. In a carbonate system with low air-sea ∆pCO2, such as the South China Sea (SCS), human activities may affect the pCO2 distribution patterns and potentially alter CO2 sink or source at the surface. This study investigates the surface carbonate system in two oil fields, namely the Wenchang Oil Feld and Enping Oil Feld, located on the northwestern SCS (NWSCS) shelf. In Enping Oil Field, although there is a slight increase in surface pCO2 due to probable total alkalinity (TA) consumption from CaCO3 precipitation, strong biological production makes the plume water a strong CO2 sink. Similarly, the biological processes dominated the pCO2 variability in Wenchang Oil Feld, exhibiting high values in its central area. In NWSCS, the influence of shelf water was observed during both cruises. And the pCO2 drawdown caused by the decreased sea surface temperature (SST) and CO2 outgassing outweighed their increases via enhanced vertical mixing, leading to a pCO2 drawdown from September to October within this water mass. More importantly, there were no significant disparities observed in carbonate parameters at stations along transects with and without wells, and the observed parameter values in this study fell within the range reported previously on the nSCS shelf with similar controlling processes. Thus the impact of oil exploitation on carbonate dynamics is negligible, and the characteristics of the carbonate system in oil field are primarily governed by natural processes such as the mixing of plume water and basin water, CaCO3 precipitation and the changes in SST. The provided data establish a crucial baseline for detecting future alterations in carbonate chemistry within oil fields, and the rapid fluctuations in sea surface pCO2 highlight the need for higher spatiotemporal resolution observation.