Global relevance of Argentinean rainfed crops in a climatic variability context: A water footprint assessment in Buenos Aires province

Argentina has a relevant international role as a producer of agricultural commodities. Buenos Aires is the province with the largest cultivated area of cereals and oilseeds of the country. Rainfed crops depend exclusively on green water, meaning a comparative advantage for Buenos Aires province. The green virtual water content in the crops produced in Buenos Aires has implications for water allocation at international level. A great amount of countries depends on the Argentinean rainfed agriculture. Therefore, it is important to understand the effects of climate variations on Argentinean crop production at local level and the role of rainfed crops in regional and international trade. We analysed the temporal and territorial variations of crops green water demand in a climatic variability context and their influence on the water footprint. The green water footprint of the main crops of Buenos Aires was assessed, including soybeans, maize, sunflower, wheat and barley, in different climatic conditions: for the period 2008-2018, which include a dry year, a humid year and an ordinary year. A dataset about the green water footprint at municipality level was provided, and the results were presented on maps for each crop and for the different climatic conditions. The relevance of green water of main crops in the world water-dependent supply chains was shown. This comprehensive green water footprint assessment provides a useful database for researchers, companies and policy makers in Argentina and beyond.

Spatiotemporal dynamics of dissolved organic matter and disinfection by-products formation potential of Shengzhong Lake in southwest China

The quality and quantity of dissolved organic matter (DOM) in lakes as well as its environmental effects associated with the unintended disinfection by-products (DBPs) have received continuous attention. This work investigated the spatiotemporal dynamics of DOM in Shengzhong Lake in southwest China and the formed DBPs during the chlorine disinfection process. The results showed that lake water in summer had significantly higher dissolved oxygen and dissolved organic carbon than that in winter. In contrast, DOM in winter demonstrated an obviously higher aromaticity and molecular weight than that in summer. Four fluorescence components, i.e., terrestrial humic-like substances (C1), protein-like substances (C2), and microbial humic-like substances (C3 and C4), were identified, and their relative abundance followed in the order of C3 > C4 > C2 > C1 in winter and C4 > C3 > C1 > C2 in summer. The formation potential of trihalomethanes and haloacetic acids in winter was higher and lower than that in summer, which was mainly ascribed to the content of aromatic and hydrophobic substances. Compared to the significant seasonal dynamic, the spatial variation of DOM and the formed DBPs was not obvious. This work sheds light on the spatial-temporal distribution of DOM and the potentially formed DBPs in Shengzhong Lake, and will be helpful for understanding the biogeochemical cycle of carbon and assessing the drinking water safety.

Modeling the effect of grazing on carbon and water use efficiencies in grasslands on the Qinghai-Tibet Plateau

BACKGROUND

Carbon and water use efficiencies (CUE and WUE, respectively) are vital indicators of the adaptability of plants to environmental conditions. However, the effects of grazing and climate change on the spatiotemporal changes in CUE and WUE in Qinghai-Tibet Plateau grasslands (QTPG) are still unclear.

RESULTS

Using the enhanced Biome-BGCMuSo model in combination with observed data, we estimated and analyzed the spatiotemporal variations in CUE and WUE and their responses to grazing in QTPG from 1979 to 2018. The mean annual CUE was 0.7066 in QTPG from 1979 to 2018 under the actual climate scenario. In general, the grassland CUE was low in the southeast and high in the northwest. Grazing generally decreased CUE in QTPG from 1979 to 2018, and there was an increasing trend in the difference in CUE between the grazing and nongrazing scenarios. The difference in CUE was generally greater in the northwest than in the southeast. The mean annual WUE was 0.5591 g C/kg H2O in QTPG from 1979 to 2018 under the actual climate scenario. After 2000, the grassland WUE exhibited a fluctuating upward trend. In general, the grassland WUE was greater in the southeast than in the northwest. Grazing generally decreased WUE in QTPG from 1979 to 2018, and there was an increasing trend in the difference in WUE between the grazing and nongrazing scenarios. The difference in WUE was generally greater in the northwest than in the southeast.

CONCLUSIONS

The findings of this study suggested that the spatiotemporal changes in CUE and WUE in QTPG were closely related to changes in the natural environment and grazing management.

Landsat observations of total suspended solids concentrations in the Pearl River Estuary, China, over the past 36 years

Information on long-term trends in total suspended solids (TSS) is critical for assessing aquatic ecosystems. However, the long-term patterns of TSS concentration (CTSS) and its latent drivers have not been well investigated. In this study, we developed and validated three semi-analysis algorithms for deriving CTSS using Landsat images. Subsequently, the long-term trends in CTSS in the Pearl River Estuary (PRE) from 1987 to 2022 and the driving factors were clarified. The developed algorithms yielded excellent performance in estimating CTSS, with mean absolute percentage errors <25% and root mean square errors of <13 mg/L. Long-term Landsat observations showed an overall decreasing trend and significant spatiotemporal dynamics of the CTSS in the PRE from 1987 to 2022. The analysis of driving factors suggested that industrial sewage, cropland, forests and grasslands, and built-up land were the four potential driving forces that explained 87.81% of the long-term variation in CTSS. This study not only provides 36-year recorded datasets of CTSS in estuary water, but also offers new insights into the complex mechanisms that regulate CTSS spatiotemporal dynamics for water resource management.

Urbanization and weather dynamics co-dominated the spatial-temporal variation in pCO2 and CO2 fluxes in small montanic rivers draining diverse landscapes

Rivers have been widely reported as important CO2 emitters to the atmosphere. Rapid urbanization has a profound impact on the carbon biogeochemical cycle of rivers, leading to enhanced riverine CO2 evasions. However, it is still unclear whether the spatial-temporal patterns of CO2 emissions in the rivers draining diverse landscapes dominated by urbanization were stable, especially in mountainous areas. This study carried out a two-year investigation of water environmental hydrochemistry in three small mountainous rivers draining urban, suburban and rural landscapes in southwestern China, and CO2 partial pressure (pCO2) and fluxes (fCO2) in surface water were measured using headspace equilibrium method and classical thin boundary layer model. The average pCO2 and fCO2 in the highly urbanized river were of 4783.6 μatm and 700.0 mmol m-2 d-1, conspicuously higher than those in the rural river (1525.9 μatm and 123.2 mmol m-2 d-1), and the suburban river presented a moderate level (3114.2 μatm and 261.2 mmol m-2 d-1). It provided even clearer evidence that watershed urbanization could remarkably enhance riverine CO2 emissions. More importantly, the three rivers presented different longitudinal variations in pCO2, implying diversified spatial patterns of riverine CO2 emissions as a result of urbanization. The urban land can explain 49.6-69.1% of the total spatial variation in pCO2 at the reach scale, indicating that urban land distribution indirectly dominated the longitudinal pattern of riverine pCO2 and fCO2. pCO2 and fCO2 in the three rivers showed similar temporal variability with higher warm-rainy seasons and lower dry seasons, which are significantly controlled by weather dynamics, including monthly temperature and precipitation, but seem to be impervious to watershed urbanization. High temperature-stimulated microorganisms metabolism and riched-CO2 runoff input lead much higher pCO2 in warm-rainy seasons. However, it showed more sensitivity of pCO2 to monthly weather dynamics in urbanized rivers than that in rural rivers, and warm-rainy seasons showed hot moments of CO2 evasion for urban rivers. TOC, DOC, TN, pH and DO were the main controls on pCO2 in the urban and suburban rivers, while only pH and DO were connected with pCO2 in the rural rivers. This indicated differential controls and regulatory processes of pCO2 in the rivers draining diverse landscapes. Furthermore, it suggested that pCO2 calculated by the pH-total alkalinity method would obviously overestimate pCO2 in urban polluted rivers due to the inevitable influence of non-carbonate alkalinity, and thus, a relatively conservative headspace method should be recommended. We highlighted that urbanization and weather dynamics co-dominated the multiformity and uncertainty in spatial-temporal patterns of riverine CO2 evasions, which should be considered when modeling CO2 dynamics in urbanized rivers.

Determining the spatiotemporal variation, sources, and ecological processes of antibiotic resistance genes in a typical lake of the middle reaches of the Yangtze River

Antibiotic resistance genes (ARGs) are emerging environmental pollutants, influenced by complex regulatory factors. River-lake systems act as natural reservoirs for ARGs and provide an ideal model for studying their regulatory mechanisms. This study employed high-throughput quantitative PCR, high-throughput sequencing, correlation analyses, and model predictions to investigate the dynamics of ARGs and their influencing factors in Liangzi Lake, located in the mid-reaches of the Yangtze River. The research specifically centered on three environmental components: lake water, sediment, and river water. Results indicated that the ARGs from eight major antibiotic classes, displaying distinct seasonal distribution patterns. In comparison to the sediment, the water phase demonstrated a higher diversity of ARGs, with the highest level of ARGs sharing observed between lake and river waters (approximately 83.7 %). Furthermore, seasonal variations significantly influenced the distributions of both ARGs and bacterial communities. The diversity of ARGs was highest during the summer and autumn, and specific bacterial species exhibited robust correlations with ARGs (including matA/mel, aac (6')-Ib-03, and blaROB). It is worth noting that environmental attributes and bacterial diversity had the most substantial impact on the dynamic changes in ARGs. Lastly, source tracking analysis pinpointed that sediment as the primary source of ARGs in lake water, constituting 45 % to 48 % of the total ARGs. Our study provides a comprehensive analysis of ARGs and their influencing factors in the river-lake system of the middle reaches of the Yangtze River, with Liangzi Lake as a representative case.

Spatio-temporal distribution characteristics and influencing factors of protoporphyrin IX in the estuarine-coastal ecosystems

Protoporphyrin IX (PPIX), a key precursor for the synthesis of chlorophyll and heme, is fundamental to photosynthetic eukaryotic cells and participates in light absorption, energy transduction, and numerous other cellular metabolic activities. Along with the application of genetic and biochemical techniques over the past few years, our understanding of the formation of PPIX has been largely advanced, especially regarding possible metabolic pathways. However, the ecological role and function of PPIX in natural ecosystems remains unclear. We have previously established a method for quantifying PPIX in marine ecosystems. Here, our results provide evidence that PPIX is not only subtly linked to nutrient uptake but also triggers phytoplankton productivity. PPIX and its derivatives are dynamic spatiotemporally in direct response to increased nutrient availability. Using 16 S rRNA gene amplicon sequencing, PPIX was revealed to interact strongly with many microorganisms, indicating that PPIX serves as a critical metabolite in maintaining microbial metabolism and community development. In summary, we observed that PPIX is linearly related to nutrient availability and microbial diversity. The levels of microbial PPIX reflect ecological health, and the availability of PPIX and nutrients jointly affect microbial community composition.

Does urban growth mean the loss of greenness? A multi-temporal analysis for Chinese cities

Urban growth is recognized as the conversion of vegetated surface to built-up surface. However, there is still no consensus about the urbanization-induced dynamic of vegetation greenness in view of existing literatures. In this study, we aimed to empirically investigate whether urban growth mean the loss of vegetation greenness. We selected 340 Chinese cities as the study areas, relied on consistent multi-temporal remotely sensed data and adopted linear regression analysis, annual growth area, Tail-Sen slope and Mann-Kendall models. Results show that although vegetation greening generally lagged behind urban growth in the monitoring period, a tendency of their consistent speeding up can be observed over time. By categorizing four forms and four trends of vegetation greenness dynamics related to urban growth, we revealed the diversity of Chinese cities. The former focused on the velocity of urban growth and vegetation greenness dynamics within newly urbanized area in three phases, i.e., 2003-2008, 2008-2013 and 2013-2018. The latter focused on the interannual trends of vegetation greenness dynamics among the previously existing and newly urbanized areas. The key finding is that, in over 85 % of the cities, we measured an increase of vegetation greenness along with urban growth. In addition, our detailed results allow quantifying the impact of urbanization in Chinese cities on vegetation protection and sustainable development.

Disentangling the Ecological Processes and Driving Forces Shaping the Seasonal Pattern of Halobacteriovorax Communities in a Subtropical Estuary

Halobacteriovorax are predatory bacteria that have a significant ecological role in marine environments. However, understanding of dynamics of populations, driving forces, and community composition of Halobacteriovorax groups in natural marine environments is still limited. Here, we used high-throughput sequencing to study the underlying mechanisms governing the diversity and assembly of the Halobacteriovorax community at spatiotemporal scales in a subtropical estuary. Phylogenetic analysis showed that 10 of 15 known Halobacteriovorax clusters were found in the studied estuary. Halobacteriovorax α-diversity and β-diversity exhibited significant seasonal variation. Variation partitioning analysis showed that the effect of nutrients was greater than that of other measured water properties on Halobacteriovorax community distribution. The results of Spearman's and Mantel's tests indicated that the trophic pollutants dissolved inorganic phosphorus (DIP) and NH4+-N in the estuary were the key factors that significantly affected Halobacteriovorax species and community diversity. In addition, this work indicated that the biological stoichiometry (especially N/P) of nutrients exerted a significant influence on the Halobacteriovorax community. Furthermore, we found that both deterministic and stochastic processes contributed to the turnover of Halobacteriovorax communities, and environmental filtering dominated the assembly of estuarine Halobacteriovorax communities. Overall, we provide new insights into the mechanisms in the generation and maintenance of the Halobacteriovorax community in marine environments.

Spatial-temporal dynamics of land use carbon emissions and drivers in 20 urban agglomerations in China from 1990 to 2019

Urban agglomerations (UAs) are the largest carbon emitters; thus, the emissions must be controlled to achieve carbon peak and carbon neutrality. We use long time series land-use and energy consumption data to estimate the carbon emissions in UAs. The standard deviational ellipse (SDE) and spatial autocorrelation analysis are used to reveal the spatiotemporal evolution of carbon emissions, and the geodetector, geographically and temporally weighted regression (GTWR), and boosted regression trees (BRTs) are used to analyze the driving factors. The results show the following: (1) Construction land and forest land are the main carbon sources and sinks, accounting for 93% and 94% of the total carbon sources and sinks, respectively. (2) The total carbon emissions of different UAs differ substantially, showing a spatial pattern of high emissions in the east and north and low emissions in the west and south. The carbon emissions of all UAs increase over time, with faster growth in UAs with lower carbon emissions. (3) The center of gravity of carbon emissions shifts to the south (except for North China, where it shifts to the west), and carbon emissions in UAs show a positive spatial correlation, with a predominantly high-high and low-low spatial aggregation pattern. (4) Population, GDP, and the annual number of cabs are the main factors influencing carbon emissions in most UAs, whereas other factors show significant differences. Most exhibit an increasing trend over time in their impact on carbon emissions. In general, China still faces substantial challenges in achieving the dual carbon goal. The carbon control measures of different UAs should be targeted in terms of energy utilization, green and low-carbon production, and consumption modes to achieve the low-carbon and green development goals of the United Nations' sustainable cities and beautiful China's urban construction as soon as possible.

Exploring spatiotemporal dynamics of flower visitor association pattern on two Avicennia mangroves: a network approach

Plant-flower visitor interaction is one of the most important relationships regarding the co-existence of the floral and faunal communities. The implication of network approaches is an efficient way to understand the impact of community structure on ecosystem functionality. To understand the association pattern of flower visitors, we performed this study on Avicennia officinalis and Avicennia marina mangroves from the islands of Indian Sundarban over three consecutive years. We found that visiting time and sites (islands) influenced the abundance of visitors. The bipartite networks showed a significant generalized structure for both site-visitor and visiting time-visitor networks where the strength and specialization of visitor species showed a highly and moderately significant positive correlation between both networks respectively. All the site-wise visiting time-visitor networks and year-wise site-visitor networks were significantly modular in structure. For both the plants, most of the visitors showed a generalized association pattern among islands and also among visiting times. Additionally, the study of the foraging behavior of dominant visitors showed Apis dorsata and Apis mellifera as the potential visitors for these plants. Our results showed that flower visitor networks are spatiotemporally dynamic. The interactions of visitors with flowers at different times influence their contribution to the network for becoming a generalist or peripheral species in the context of their visiting time, which may subsequently change over islands. This approach will help to devise more precise plant species-specific conservation strategies by understanding the contribution of visitors through the spatiotemporal context.

Spatio-temporal dynamics and human-land synergistic relationship of urban expansion in Chinese megacities

Megacities play important roles in countries' politics, economy, culture, etc. Exploring the law of urban expansion of megacities has important reference for sustainable urbanization. Here, the spatiotemporal dynamics of urban expansion were quantified analyzed in 21 Chinese megacities from 2000 to 2020 with quantitative measurement indicators and explored the human-land synergistic relationship used the decoupling model. Results are as follows: (1) China's megacities experienced significant expansion, and urban expansion characterized as rapid initially but slowed down thereafter. (2) Urban expansion in megacities was characterized as having significant spatial differences, and rapidly expanding megacity centers moved from eastern to midwestern China. (3) Urban spatial expansion of megacities was mainly an enclave type in 2000-2010 and marginal type in 2010-2020. (4) The main type of human-land synergistic relationship in megacities were weak decoupling, there is a significant increase in expansive coupling and expansive negative decoupling in 2010-2020; (5) Lastly, human-land synergy relationship in most megacities was uncoordinated based on the per capita urban land area and decoupling type. The findings of this study can deepen the understanding of the characteristics and quality of urbanization evolution, and provides reference for high-quality development planning and decision-making in megacities.

Spatiotemporal dynamics, traceability analysis, and exposure risks of antibiotic resistance genes in PM2.5 in Handan, China

Fine particulate matter (PM2.5) seriously affects environmental air quality and human health, and antibiotic resistance genes (ARGs) in PM2.5 posed a great challenge to clinical medicine. The year of 2013-2017 was an important 5-year period for the implementation of Air Pollution Prevention and Control Action Plan (APPCAP) in China. Here, we took Handan, a PM2.5 polluted city in northern China, as the research object and analyzed ARGs in PM2.5 in winter (January) from 2013 to 2017. The results showed that the abundance of ARGs was the highest in 2013 (3.7 × 10-2 copies/16S rRNA), and ARGs were positively correlated with air quality index (AQI) (r = 0.328, P < 0.05) and PM2.5 concentration (r = 0.377, P = 0.020 < 0.05) in the 5-year period. The ARGs carried by PM2.5 in four functional regions of sewage treatment plant, steel works, university, and park showed that sul1 and qepA had higher abundance in each functional region, and the total ARG abundance in sewage treatment plant (1.3 × 10-1 copies/16S rRNA) was the highest, while lowest in park (2.0 × 10-3 copies/16S rRNA). Potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) model were used to trace the pollutants at the sampling points, which indicated that the surrounding cities contributed more than quarter to the sampling points. Therefore, regional transportation reduces the spatial distribution difference of ARGs in PM2.5. The exposure dose of ARGs in different functional regions illustrated that the total inhaled dose of ARGs in sewage treatment plant (1.7 × 105 copies/d) was the highest, while lowest in park (3.2 × 104 copies/d). This study is of great significance for assessing the distribution and sources of ARGs under the clean air initiative in China.

In the right place, at the right time: the integration of bacteria into the Plankton Ecology Group model

BACKGROUND

Planktonic microbial communities have critical impacts on the pelagic food web and water quality status in freshwater ecosystems, yet no general model of bacterial community assembly linked to higher trophic levels and hydrodynamics has been assessed. In this study, we utilized a 2-year survey of planktonic communities from bacteria to zooplankton in three freshwater reservoirs to investigate their spatiotemporal dynamics.

RESULTS

We observed site-specific occurrence and microdiversification of bacteria in lacustrine and riverine environments, as well as in deep hypolimnia. Moreover, we determined recurrent bacterial seasonal patterns driven by both biotic and abiotic conditions, which could be integrated into the well-known Plankton Ecology Group (PEG) model describing primarily the seasonalities of larger plankton groups. Importantly, bacteria with different ecological potentials showed finely coordinated successions affiliated with four seasonal phases, including the spring bloom dominated by fast-growing opportunists, the clear-water phase associated with oligotrophic ultramicrobacteria, the summer phase characterized by phytoplankton bloom-associated bacteria, and the fall/winter phase driven by decay-specialists.

CONCLUSIONS

Our findings elucidate the major principles driving the spatiotemporal microbial community distribution in freshwater ecosystems. We suggest an extension to the original PEG model by integrating new findings on recurrent bacterial seasonal trends. Video Abstract.

Identifying the water quality variation characteristics and their main driving factors from 2008 to 2020 in the Yellow River Basin, China

Understanding of the water quality dynamics and their main influence factors is crucial for sustainable water environment management especially in the sensitive ecosystem area. Here, the spatiotemporal dynamic of water quality in the Yellow River Basin from 2008 to 2020 and its relationship with physical geography, human activities, and meteorology were studied by using Pearson correlation test, and a generalized linear model. The results showed that water quality was significantly improved since 2008, which was reflected from the decreasing trend of the permanganate index (COD_Mn) and ammonia nitrogen (NH₃-N), and increasing trend of the dissolved oxygen (DO). However, the total nitrogen (TN) remained severely polluted with average annual concentration inferior to level V. Spatially speaking, the water quality in the upper and lower reaches was better than that of the middle reaches. The whole basin was severely contaminated by TN with 2.62 ± 1.52, 3.91 ± 1.71, and 2.91 ± 1.20 mg L^-1 from upper, middle, and lower reaches, respectively. Thus, TN should be paid much attention in the water quality management of the Yellow River Basin. The water quality improvement could be attributed to the reduction of pollution discharges and ecological restoration. Further analysis found the variation of water consumption and increase of forest and wetland area contributed 39.90% and 47.49% for COD_Mn and 58.92% and 30.87% for NH₃-N, respectively. Meteorological variables and total water resources contributed slightly. This study is expected to provide in-depth insights for the water quality dynamics and their response to human activities and natural factors in the Yellow River Basin, which could provide theoretical references for water quality protection and management.

From prairie to crop: Spatiotemporal dynamics of surface soil organic carbon stocks over 167 years in Illinois, U.S.A

Quantifying spatiotemporal dynamics of soil organic carbon (SOC) stocks is needed to understand the impact of land use change and can help target carbon sequestration efforts. In the recently and radically transformed landscapes of the state of Illinois, U.S.A., we evaluated surface SOC stocks under land use change using a space-for-time substitution method over 167 years. Additionally, we determined SOC stocks for the A horizon vs 0-30 cm depth to evaluate pedogenically-informed vs more commonly used fixed depth approaches. Legacy soil datasets from 1980 to 2012 were combined with environmental covariates using a random forest algorithm. To more accurately estimate pre-agricultural land use SOC stocks (i.e., pre-1845), SOC observations collected from soils under native prairie and forest were extracted from peer-reviewed publications. The model was validated on 25 % of the total 627 test data (R_A-hor²: 0.59 and R_0-30²: 0.56; RMSE_A-hor: 20.5 and RMSE_0-30:19.3 Mg/ha) independent of the 75 % of data for calibration (R²: 0.91; RMSE_A-hor:10.1 and RMSE_0-30:9.6 Mg/ha). SOC stocks were largest under prairie (A horizon: 156.1 Mg/ha; 0-30 cm: 152.4 Mg/ha) and lowest under pasture (A horizon: 33.2, 0-30 cm: 44.6 Mg/ha). SOC stocks varied less by soil order than by land use. Between 1845 and 2012, surface SOC stocks decreased for most of Illinois, with greatest losses in central (-16.3 Mg/ha) and east-central Illinois (-47.0 Mg/ha) where approximately 80 % of prairie was converted to cropland. A slight increase in surface SOC stocks occurred in the unglaciated northwest region and the less recently glaciated south region, as well as in alluvial corridors. This study (i) highlights how estimating spatiotemporal dynamics of surface SOC stocks over centennial timescales can benefit from including measures of SOC under native land use not usually contained in legacy pedon datasets, and (ii) illustrates the potential of identifying localized hotspots of historical SOC loss and thus deficits that can be prioritized for carbon sequestration efforts.

Spatiotemporal dynamics analysis of aquaculture zones and its impact on green tide disaster in Haizhou Bay, China

With the rapid marine economic development, the problem of the marine ecological environment has become progressively prominent. Mariculture monitoring plays an essential role in sustaining ecological stability, rational planning, and green economic development of sea areas. Using the Landsat image, the raft-mariculture area information of Haizhou Bay and its adjacent southern waters were extracted by the object-oriented classification method based on remote sensing techniques. Landscape pattern index and principal component analysis were used to analyze the spatiotemporal expansion and structural changes of mariculture areas, and to quantify the effects of natural, socio-economic factors on the spatiotemporal variations of mariculture areas. This study discusses the correlation between the mariculture area and the outbreak scale of Enteromorpha Enteromorpha green tide. Results show that the object-oriented classification method has the highest accuracy, with total classification accuracy and Kappa coefficient of more than 90% and 0.79, respectively. The total area, patch density, and landscape shape index of mariculture areas in Haizhou Bay increase yearly, which demonstrates that the heterogeneity and fragmentation increase with the expansion of the mariculture area. The landscape pattern changes in the mariculture area are predominantly impacted by annual mean sea surface temperature (SST), annual average wind speed, social development level, and population density, etc. The larger the area of raft-aquaculture, the wider the outbreak scale of the Enteromorpha prolifera disaster. Study results can provide scientific references for the further development of mariculture in Haizhou Bay and marine environmental protection.

Spatiotemporal dynamics and functional characteristics of the composition of the main fungal taxa in the root microhabitat of Calanthe sieboldii (Orchidaceae)

BACKGROUND

Endophytic fungi play a critical ecological role in the growth and development of orchids, but little is known about the spatial and temporal dynamics of fungal diversity or the ecological functions of fungi during orchid growth and reproduction. Calanthe sieboldii Decne. is listed in the Chinese National Key Protected Wild Plants as a class I protected wild plant. To understand the community characteristics of root and soil fungi of the orchid during its reproductive seasons, we investigated the community composition, spatial and temporal dynamics, and functional characteristics of the orchid microhabitat fungi by using diversity and ecological functional analyses.

RESULTS

We discovered that there were three, seven, and four dominant fungal families in the orchid's roots, rhizoplane soil, and rhizosphere soil, respectively. Tulasnellaceae, Aspergillaceae, and Tricholomataceae were the dominant fungi in this endangered orchid's microhabitats. The closer the fungal community was to the orchid, the more stable and the less likely the community composition to change significantly over time. The fungal communities of this orchid's roots and rhizoplane soil varied seasonally, while those of the rhizosphere soil varied interannually. Saprophytic fungi were the most abundant in the orchid's fungal community, and the closer the distance to the orchid, the more symbiotic fungi were present.

CONCLUSIONS

The fungi in different parts of the root microhabitat of C. sieboldii showed different spatiotemporal dynamic patterns. The fungal community near the orchid roots was relatively stable and displayed seasonal variation, while the community further away from the roots showed greater variation. In addition, compared with the soil fungi, the dominant endophytic fungi were more stable, and these may be key fungi influencing orchid growth and development. Our study on the spatiotemporal dynamics and functions of fungi provides a basis for the comprehensive understanding and utilization of orchid endophytic fungi.

Spatiotemporal dynamics and anthropologically dominated drivers of chlorophyll-a, TN and TP concentrations in the Pearl River Estuary based on retrieval algorithm and random forest regression

Estimation of large-scale and high-precision water quality parameters is critical in explaining the spatiotemporal dynamics and the driving factors of water quality variability, especially in areas with environmental complexity (e.g., crisscrossing waterways, high flood risk in rainy season and seawater invasion). Thus, in this study, a retrieval algorithm was developed to predict chlorophyll-a (Chl-a), total nitrogen (TN) and total phosphorus (TP) concentrations in the Pearl River Estuary (PRE) based on a large amount of in situ measurements and Landsat 8 remote sensing images. Random Forest (RF) machine learning was conducted to identify the relationship between environmental indicators (pH, turbidity, conductivity, total dissolved solids and water temperature), Chl-a, TN and TP. The results showed that the NIR/R Binomial algorithm for Chl-a estimation presented appreciable reliability with R² of 0.7429, root mean square error (RMSE) of 1.2089 and mean absolute percent error (MAPE) of 15.33%. The water quality variation in the PRE showed a characteristic of overall improvement and regional deterioration with average concentrations of 7.28 μg/L, 1.15 mg/L and 0.12 mg/L for Chl-a, TN, and TP respectively. Turbidity and pH were identified as the most important indicators to explain Chl-a (52.86%, 39.91%), TN (52.38%, 40.57%) and TP (55.23%, 40.03%) variation. Agricultural pollution was the main pollution source due to the intensive application of fertilizer and increased field size. Besides, land use patterns (e.g., increasing farmland but decreasing forest) greatly influenced water quality from 2010 to 2020. Moreover, light limitation caused by high turbidity reduced the algae productivity and further lowered the Chl-a concentration. The driving factors for regional water quality variations were anthropologically dominated and supplemented by climate change. This study improved the monitoring accuracy of regional water environment and provided quantitative early warning of water pollution events for environmental practitioners, so as to achieve long-term monitoring, precise pollution management and efficient water resources management.

Spatiotemporal dynamics of ecological security in a typical conservation region of southern China based on catastrophe theory and GIS

Ecological security assessment can effectively reflect the ecological status of a region and reveal its level of sustainable development. In this paper, an ecological security-oriented evaluation system was constructed, and the ecological security level of the Dongjiangyuan region from 2000 to 2020 was evaluated based on catastrophe theory and GIS. The results were as follows: (1) As shown in the land use and cover maps, by 2020, the forestland area had decreased the most, and the artificial surface area had increased the most. (2) The ecological security index of the Dongjiangyuan region showed a low trend in the artificial surface area and its surrounding areas. The quite low values of the ecological security index in 2000 and 2010 were improved in 2020 due to the increase in ecological services capacity. The increased vegetation cover from 2000 to 2020 promoted the improved ecological service capacity. (3) The rapid urbanization process in the Dongjiangyuan region resulted in a lower ecological sensitivity index value. Notably, the ecological sensitivity index of the study area had a slightly decreasing trend. (4) The spatial autocorrelation showed that the proportion of hot and cold spots from 2000 to 2020 decreased by 2.96% and 6.91%, respectively. This study can provide a scientific basis and decision-making guidance for ecological management in the Dongjiangyuan region in the future.

Seeking sustainable pathway of crop production by optimizing planting structures and management practices from the perspective of water footprint

Water shortage threatens sustainable agriculture and food security globally. The Huanghuaihai Plain plays a critical role in ensuring China's food security, but at the expense of groundwater quantity and quality. Approaches that integrate crop production and environmental goals offer promise for achieving more sustainable water management in agriculture, yet little work has been done to link potential solutions with planting structure and resource management. The spatiotemporal variation of water footprint, water scarcity footprint, and green water occupancy rate for seven major crops, and the sustainability index and reduction potential of ten targeted reduction scenarios across 486 counties were quantitatively assessed in the Huanghuaihai Plain during 1985-2015. Total and gray water footprints dramatically increased by 59.5 % and 446.8 % from 1985 to 2015, respectively. The water scarcity footprint increased from 43.3 × 10⁹ to 49.9 × 10⁹ m³ and green water occupancy rate decreased from 37.8 % to 36.1 %. Among the single measures, reducing nitrogen input or its leaching would have the optimal reduction potential in WF_total (reduced by 5.5-11.0 %), while adjusting planting structure would have the best sustainable performance. More importantly, the areas with the greatest reduction potential in blue water footprint by deficit irrigation and adjusting planting structure were located in the southeastern and middle parts of the plain, respectively, suggesting that differentiated strategies are required for regional water sustainability. The findings provide not only integrated approaches to inform targeted water management decision making in the Huanghuaihai Plain, but also best practices that may be applicable to other regions facing similar resource concerns.

Trophic structure and origin of resources of soil macrofauna in the salt marsh of the Wadden Sea: a stable isotope (15N, 13C) study

Salt marshes exist along the gradient of the marine mudflat to the terrestrial dunes, with a gradient of shore height and associated plant zonation. The lower salt marsh (LSM) extends from the mean high tidal level to 35 cm above that level and is followed by the upper salt marsh (USM). Despite changes in the amount of allochthonous marine input and in abiotic conditions, little is known about changes in the trophic structure and used of basal resources by the soil macrofauna along marine-terrestrial boundaries. Natural variations in carbon stable isotope ratios (δ13C signatures) allow insight into basal resources of consumers such as marine algae, terrestrial C3 and C4 photosynthesising plants. Furthermore, variations in nitrogen stable isotope ratios (δ15N signatures) allow insight into the trophic position of consumers. We investigated spatial and temporal changes in stable isotope signatures in salt marsh soil macrofauna of the island of Spiekeroog, German Wadden Sea. The range of δ15N signatures indicated no changes in food chain length across salt marsh zones with consumers in both zones comprising primary decomposers, secondary decomposers and first order predators. However, the trophic position of individual species changed between zones, but in particular with season. Contrasting δ15N signatures, the range in δ13C signatures in the LSM was twice that in the USM indicating a wider range of resources consumed. Bayesian mixing models indicated predominant autochthonous resource use in both the LSM and USM, with the use of marine allochthonous resources never exceeding 29.6%. However, the models also indicate an increase in the use of marine resources in certain species in the LSM with no use in the USM. Overall, the results indicate that the resource use of salt marsh macrofauna varies more in space than in time, with the food web being generally based on autochthonous rather than allochthonous resources. However, there also is trophic plasticity in certain species across both temporal and spatial scales including variations in the use of allochthonous resources. Generally, however, marine input contributes little to the nutrition of salt marsh soil macroinvertebrates.

Spatiotemporal dynamics of grassland aboveground biomass and its driving factors in North China over the past 20 years

Although remote sensing has enabled rapid monitoring of grassland aboveground biomass (AGB) at a regional scale, it is still a difficult challenge to construct an accurate estimation model of grassland AGB in a vast region to support the AGB dynamics analysis over a long time series. In this study, extensive grassland AGB measurements (collected in North China during the grassland growing season of 2000-2019), MODIS data, and environmental factors (climate, topography and soil) were employed to construct the grassland AGB models using four machine learning algorithms (random forest, support vector machine, artificial neural network and extreme learning machine) combined with four variable selections. The spatial distributions of annual grassland AGB from 2000 to 2019 were simulated based on the optimal AGB model. The temporal change and future trend of AGB series from 2000 to 2019 were comprehensively analyzed by the slope model and Hurst exponent. The influences of natural and anthropogenic factors on grassland AGB dynamics were explored quantitatively using the Geodetector model. The results showed that (1) the random forest model constructed from the variables selected by the successive projections algorithm is the optimal grassland AGB model. (2) The 20-year average grassland AGB in North China showed an overall spatial distribution of being low in the central and western parts and high in the southeastern part. (3) The annual maximum grassland AGB in most regions (82.71%) showed an increasing trend during 2000-2019; and most of the grasslands with a decreasing trend of AGB were located in regions with low AGB values and arid climates. (4) The future trend of grassland AGB after the study period may be optimistic, as reflected by more grassland AGB was predicted to increase rather than decrease (70.38% vs. 29.62%). (5) The main driving factors of spatiotemporal dynamics of grassland AGB were precipitation, soil type, and livestock density; the interactive influence of two drivers on AGB showed mutual enhancement.

Assessment of spatiotemporal dynamics of land and vegetation cover change detection in Maze National Park, Southwest Ethiopia

Biodiversity conservation areas include National Parks which are integral parts of protected areas. In parks, the dynamics of land and vegetation covers are significantly affected by anthropogenic activities and natural factors. These resources are exposed to challenges due to unwise practices. Assessing and monitoring the status of park's natural resources enables us to understand the extent of land and vegetation resources. Few studies have been conducted in Maze National Park (MzNP) but none of them quantified the land and vegetation cover dynamics. The purpose of this study is, therefore, to quantify the extents spatiotemporal dynamics of land and vegetation cover of MzNP using GIS and RS technology considering three decades Landsat images acquired from USGS. GPS and GCPs were collected for the analysis of land cover classification and accuracy assessment, respectively. The trend analysis result revealed that scattered tree and grass land cover area have increased from 19.8% in 1987 to 51.6% in 2019. The area of sparse vegetation cover increased from 19.7% in 2000 to 78.4% in 2019. Highly dense and dense vegetation cover decreased remarkably. Accuracy assessment was 98% and computed Kappa coefficient was 0.97. The results suggested that the extent of MzNP's vegetation cover change was basically due to anthropogenic pressure. This study could be used to alarm responsible bodies to restructure and implement better environmental protection strategies for restoration of the rapidly deteriorating vegetation resource of MzNP.

The spatiotemporal dynamics of lung cancer: 30-year trends of epidemiology across 204 countries and territories

BACKGROUND

It has been established that lung cancer is the leading cause of all cancer deaths. This study sought to analyze the epidemiological trends of lung cancer over the past 30 years worldwide.

METHODS

Estimates, including the global, regional, national prevalence, incidence, and years lived with disability (YLDs) of lung cancer from 1990 to 2019, were extracted from the Global Burden of Disease Study 2019 to assess the spatiotemporal dynamics in cases and age-standardized rates (ASR). The estimated annual percentage change (EAPC) was calculated to evaluate the variation in ASR. Besides, estimates of age-sex specific prevalence, decomposition analysis for incident cases, and correlation analysis of the EAPC were conducted in our study.

RESULTS

Globally, the ASR of lung cancer prevalence, incidence and YLDs in 2019 were 38.84/100,000 persons, 27.66/100,000 persons, and 6.62/100,000 persons, respectively. Over the past 30 years, the ASR of incidence (EAPC = -0.09) decreased, although that of prevalence (EAPC = 0.51) and YLDs (EAPC = 0.03) increased. The global prevalence counts was greater in males than females at all age groups and increased with age, peaking in the 65-69 age group for both sexes. The increase in incidence was mainly attributed to population aging. For YLDs, EAPC was negatively correlated with the human development index (p = 0.0008) and ASR (p < 0.0001) in 1990 across nation-level units.

CONCLUSIONS

Lung cancer remains a major public health issue globally, warranting the implementation of scientific and effective measures in different countries and territories to control it.

Impacts of Human Activities and Climate Change on Water Storage Changes in Shandong Province, China

The over-exploitation of water resources causes water resource depletion, which threatens water security, human life, and social and economic development. Only by clarifying the spatial pattern, changing trends, and influencing factors of water storage can we promote the rational development of water resources and relieve the pressure on water resources. However, there is still a lack of research on these aspects. In this study, the water-scarce area in Shandong Province, China, was selected to quantify the spatial and temporal changes in the terrestrial water storage (TWS) and groundwater storage (GWS) over the past 30 years. Nighttime light data were used to characterize the urbanization level (UL) and explore the effects of human activities (i.e., UL) and climate change (temperature and precipitation) on the TWS and GWS. The results show that 1) from 1990 to 2018, the overall TWS exhibited a significant decreasing trend (- 0.084 cm yr^-1). The change trend of the GWS was consistent with that of the TWS (- 0.516 m³ yr^-1). Spatially, there was significant spatial heterogeneity in the trend of the TWS and GWS. At the grid and prefectural scales, the TWS mainly exhibited a downward trend in the central and western regions, and an upward trend in the eastern region of Shandong Province. For the GWS, all cities exhibited a decreasing trend at the prefectural scale, whereas 92% of the regions exhibited a decreasing trend with less spatial heterogeneity at the grid scale. 2) Precipitation was the mean factor controlling the total amount of TWS and GWS in Shandong Province. Precipitation and temperature positively affected water storage, and the UL negatively affected it. At the prefectural scale, except for a few cities which were greatly influenced by the UL, the dominant factor of the TWS and GWS was precipitation in the other cities. At the grid scale, for the TWS, precipitation was the predominant factor in 51.82% of the entire region, followed by the UL (44.14%) and temperature (4.04%). For the GWS, precipitation was the predominant factor in 55.73% of the area, and the other 44.27% of the area was mainly influenced by the UL. Overall, precipitation and the UL were the key factors affecting the TWS and GWS. The results of this study provide a theoretical and decision-making basis for the optimal allocation and sustainable use of regional water resources.

Profile and dynamics of infectious diseases: a population-based observational study using multi-source big data

Background

The current surveillance system only focuses on notifiable infectious diseases in China. The arrival of the big-data era provides us a chance to elaborate on the full spectrum of infectious diseases.

Methods

In this population-based observational study, we used multiple health-related data extracted from the Shandong Multi-Center Healthcare Big Data Platform from January 2013 to June 2017 to estimate the incidence density and describe the epidemiological characteristics and dynamics of various infectious diseases in a population of 3,987,573 individuals in Shandong province, China.

Results

In total, 106,289 cases of 130 infectious diseases were diagnosed among the population, with an incidence density (ID) of 694.86 per 100,000 person-years. Besides 73,801 cases of 35 notifiable infectious diseases, 32,488 cases of 95 non-notifiable infectious diseases were identified. The overall ID continuously increased from 364.81 per 100,000 person-years in 2013 to 1071.80 per 100,000 person-years in 2017 (χ² test for trend, P < 0.0001). Urban areas had a significantly higher ID than rural areas, with a relative risk of 1.25 (95% CI 1.23–1.27). Adolescents aged 10–19 years had the highest ID of varicella, women aged 20–39 years had significantly higher IDs of syphilis and trichomoniasis, and people aged ≥ 60 years had significantly higher IDs of zoster and viral conjunctivitis (all P < 0.05).

Conclusions

Infectious diseases remain a substantial public health problem, and non-notifiable diseases should not be neglected. Multi-source-based big data are beneficial to better understand the profile and dynamics of infectious diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07313-6.

Spatiotemporal dynamics in microbial communities mediating biogeochemical cycling of nutrients across the Xiaowan Reservoir in Lancang River

Microbes drive biogeochemical cycles of nutrients controlling water quality in freshwater ecosystems, yet little is known regarding how spatiotemporal variation in the microbial community affects this ecosystem-level functional processes to resist perturbations. Here we examined spatiotemporal dynamics of microbial communities in paired stratified water columns and sediments collected from the Xiaowan Reservoir of Lancang-Mekong River over a year long period. Results highlighted distinctive spatiotemporal patterns of microbial communities in water columns mainly driven by sulfate, dissolved oxygen, nitrate and temperature, whilst sediment communities only showed a seasonal variation pattern governed by pH, reduced inorganic sulfur, sulfate, organic matter and total nitrogen. Microbial co-occurrence networks revealed the succession of keystone taxa in both water columns and sediments, reflecting core ecological functions in response to altered environmental conditions. Specifically, in shallow water, keystone nitrogen fixers and denitrifiers were responsible for providing nitrogen nutrients in summer, while recalcitrant substance degraders likely supplied microbially available organic matters to maintain ecosystem stability in winter. But in deep water, methane oxidation was the critical process linked to microbial-mediated cycle of carbon, nitrogen and sulfur. In addition, carbon metabolism and mercury methylation mediated by sulfate reducers, denitrifiers and nitrogen fixers were core functioning features of sediments in summer and winter, respectively. This work expands our knowledge of the importance of keystone taxa in maintaining stability of reservoir ecosystems under changing environments, providing new perspectives for water resource conservation and management.

China's industrial green total-factor energy efficiency and its influencing factors: a spatial econometric analysis

The sustainable development of China's economy is bottlenecked by resource shortage and environmental pollution. As the leading resource consumer and pollutant source, the industrial sector needs to improve its energy efficiency. This paper establishes a super epsilon-based measure (Super-EBM) model with bad outputs like environmental cost and evaluates the industrial green total-factor energy efficiencies (IGTFEEs) of 30 provinces in China during 2000-2017. Unlike previous research, the main contribution of this paper is to choose four environmental pollutants as bad outputs (industrial carbon dioxide, industrial sulfur dioxide, industrial chemical oxygen demand, industrial solid waste). By contrast, the previous studies mostly only take one environmental pollutant as bad output, i.e., the bad outputs are not fully measured. Then, the spatiotemporal dynamics and spatial correlations of the IGTFEEs were analyzed, and the influencing factors of IGTFEE were examined empirically with a spatial econometric model. Finally, this paper adopts generalized method of moments (GMM) to solve the endogenous problem, trying to assure the robustness of estimation results. The results show significant provincial differences in IGTFEE. Most eastern coastal provinces achieved satisfactory IGTFEEs, while most inland provinces had undesirable IGTFEEs. Eastern region achieved the highest IGTFEE, followed by central region; western region had the lowest IGTFEE. The IGTFEE improved over time in some provinces while worsened greatly in some provinces. The IGTFEE in most provinces need to be further improved. Global Moran's I values indicate that the provincial IGTFEEs were clustered in space, rather than randomly distributed. Local indication of spatial association (LISA) map reflects significant local spatial clustering of provincial IGTFEEs. In addition, IGTFEE is significantly promoted by industrial structure, technological innovation, human capital, opening-up, and energy structure yet significantly suppressed by ownership structure and environmental regulation. Considering the endogeneity, GMM results show that the estimation results of the model were robust. Specific policy recommendations include vigorously developing high-tech industries, deepening state-owned enterprises reform, diverting more funds to research and development, cultivating versatile talents, introducing environmentally-friendly foreign capital, accelerating the implementation of clean energy development strategy, and widening the fund channels of pollution control investment.

Spatiotemporal dynamics and influencing factors of the global material footprint

Environmental pressures have rapidly increased in various regions worldwide due to globalization. Thus, sustainable consumption and production are crucial for sustainable resource development. The material footprint (MF) of 180 countries was calculated from 1995 to 2015, and spatial autocorrelation analysis was conducted to investigate the spatiotemporal trend of the global MF. The results show that the global MF presented an upward trend from 1995 to 2015, increasing by 83%, and we find that the global per capita MF exhibits clustering, with an increasing trend during the study period. The findings indicate that resource consumption is similar in neighboring areas, especially in countries with a high MF surrounded by countries with a high MF (high-high clustering) and countries with low-low clustering. In addition, the number of countries with high clustering increased during the study period. We should take advantage of clustering, improve resource utilization, increase the technical carrying capacity, and develop energy-saving technologies. In African regions with low-low clustering, the economy of the surrounding areas should be stimulated to strengthen economic and technological clustering. In addition, advanced technology should be incorporated to improve the efficiency of using natural resources. This study can provide a reference for the spatial distribution of sustainable resource development.

Evolution of landscape pattern and the association with ecosystem services in the Ili-Balkhash Basin

The Ili-Balkhash Basin in Central Asia is an arid endorheic basin shared by China and Kazakhstan. Population growth, socio-economic development, ecological conservation measures, and climate change have spurred land use and land cover changes and ecosystem services variations. This study used the long-term dataset from 1992 to 2018 to detect the landscape pattern evolution and its association with ecosystem services. The landscape pattern was quantified using landscape metrics, and the GeoDetector model quantified the driving factors of landscape pattern evolution. The ecosystem service value was assessed using the benefit transfer method. The time series trend was identified by the linear regression analysis combined with the Mann-Kendall algorithm, and Pearson's correlation coefficient was used to confirm the correlation. The temporal dynamics of the landscape pattern indicated the significant conversion of bare land to grassland. Cropland and urban land expanded significantly at the expense of forestland, grassland, and bare land. Various landscape elements tended to be more uniformly distributed across the basin with more regular shape and higher aggregation. The ecosystem service value increased significantly, and its correlation with the landscape pattern varied according to land use and land cover (LULC) types. The weakened shape complexity, the strengthened aggregation degree, and the more uniform distribution of different LULC types helped elevate total ecosystem service value. The results advanced the understanding of landscape pattern evolution and provided the scientific reference for land management regarding ecosystem services. Given the watershed ecosystem's integrity, transboundary cooperation between China and Kazakhstan was suggested to reinforce watershed sustainability through integrated watershed land resource planning and the joint adaptive strategies to climate change.

Spatial heterogeneity of changes in cropland ecosystem water use efficiency and responses to drought in China

Understanding cropland ecosystem water use efficiency (eWUE) responses to drought is important for sustainable water resource management and food security. Today in China, the spatiotemporal patterns of eWUE and responses to drought across different cropland classes remain poorly quantified. In this study, we characterized the spatial temporal variability in cropland eWUE and response to drought in China from 1982 to 2017 using the satellite-retrieved evapotranspiration (ET), gross primary production (GPP), and self-calibrating Palmer Drought Severity Index (scPDSI), in conjunction with the Global Food Security-support Analysis Data product for Crop Dominance (GFSAD1KCD) data. Results indicated that (1) mean annual cropland eWUE had a spatial range from 0 to 9.94 g C kg-1 H2O, with higher values (2.06 g C kg-1 H2O) in class 4 (rainfed: wheat, rice, and soybeans dominant), whereas the lowest eWUE (1.58 g C kg-1 H2O) occurred in class 2 (irrigated mixed crop 1: wheat, rice, barley, and soybeans). (2) Annual eWUE, GPP, and ET values for croplands in China increased significantly between 1982 and 2017. Class 1 (irrigated wheat and rice) had the highest trend of 0.011 g C kg-1 H2O yr-1, and class 6 (rainfed: corn and soybeans) had the lowest of 0.0007 g C kg-1 H2O yr-1. Apart from class 4, annual GPP and ET were enhanced in most cropland classes from 1982 to 2017 (p<0.01). (3) Rainfed croplands generally had higher eWUE, GPP, and ET values than irrigated croplands. Except for rainfed cropland eWUE, all other cropland variables increased significantly (p<0.001) from 1982 to 2017. (4) Correlation analysis found that the 19.66% (15.62%) of cropland had significant negative (positive) correlations between eWUE and current-year scPDSI. The legacy effects of drought on cropland eWUE indicated that previous and current-year drought impacts on cropland eWUE were in the same direction. Our results provide insights into variability in cropland eWUE and its response to drought in China, where there is a growing demand for agricultural water resource management.

Spatiotemporal trajectories in resting-state FMRI revealed by convolutional variational autoencoder

Recent resting-state fMRI studies have shown that brain activity exhibits temporal variations in functional connectivity by using various approaches including sliding window correlation, co-activation patterns, independent component analysis, quasi-periodic patterns, and hidden Markov models. These methods often model the brain activity as a discretized hopping among several brain states that are defined by the spatial configurations of network activity. However, the discretized states are merely a simplification of what is likely to be a continuous process, where each network evolves over time following its unique path. To model these characteristic spatiotemporal trajectories, we trained a variational autoencoder using rs-fMRI data and evaluated the spatiotemporal features of the latent variables obtained from the trained networks. Our results suggest that there are a relatively small number of approximately orthogonal whole-brain spatiotemporal patterns that capture the most prominent features of rs-fMRI data, which can serve as the building blocks to construct all possible spatiotemporal dynamics in resting state fMRI. These spatiotemporal patterns provide insight into how activity flows across the brain in concordance with known network structures and functional connectivity gradients.

Neural dynamics underlying the acquisition of distinct auditory category structures

Despite the multidimensional and temporally fleeting nature of auditory signals we quickly learn to assign novel sounds to behaviorally relevant categories. The neural systems underlying the learning and representation of novel auditory categories are far from understood. Current models argue for a rigid specialization of hierarchically organized core regions that are fine-tuned to extracting and mapping relevant auditory dimensions to meaningful categories. Scaffolded within a dual-learning systems approach, we test a competing hypothesis: the spatial and temporal dynamics of emerging auditory-category representations are not driven by the underlying dimensions but are constrained by category structure and learning strategies. To test these competing models, we used functional Magnetic Resonance Imaging (fMRI) to assess representational dynamics during the feedback-based acquisition of novel non-speech auditory categories with identical dimensions but differing category structures: rule-based (RB) categories, hypothesized to involve an explicit sound-to-rule mapping network, and information integration (II) based categories, involving pre-decisional integration of dimensions via a procedural-based sound-to-reward mapping network. Adults were assigned to either the RB (n = 30, 19 females) or II (n = 30, 22 females) learning tasks. Despite similar behavioral learning accuracies, learning strategies derived from computational modeling and involvements of corticostriatal systems during feedback processing differed across tasks. Spatiotemporal multivariate representational similarity analysis revealed an emerging representation within an auditory sensory-motor pathway exclusively for the II learning task, prominently involving the superior temporal gyrus (STG), inferior frontal gyrus (IFG), and posterior precentral gyrus. In contrast, the RB learning task yielded distributed neural representations within regions involved in cognitive-control and attentional processes that emerged at different time points of learning. Our results unequivocally demonstrate that auditory learners' neural systems are highly flexible and show distinct spatial and temporal patterns that are not dimension-specific but reflect underlying category structures and learning strategies.

Spatial variations in CO2 fluxes in a subtropical coastal reservoir of Southeast China were related to urbanization and land-use types

Carbon dioxide (CO₂) emissions from aquatic ecosystems are important components of the global carbon cycle, yet the CO₂ emissions from coastal reservoirs, especially in developing countries where urbanization and rapid land use change occur, are still poorly understood. In this study, the spatiotemporal variations in CO₂ concentrations and fluxes were investigated in Wenwusha Reservoir located in the southeast coast of China. Overall, the mean CO₂ concentration and flux across the whole reservoir were 41.85 ± 2.03 µmol/L and 2.87 ± 0.29 mmol/m²/h, respectively, and the reservoir was a consistent net CO₂ source over the entire year. The land use types and urbanization levels in the reservoir catchment significantly affected the input of exogenous carbon to water. The mean CO₂ flux was much higher from waters adjacent to the urban land (5.05 ± 0.87 mmol/m²/hr) than other land use types. Sites with larger input of exogenous substance via sewage discharge and upstream runoff were often the hotspots of CO₂ emission in the reservoir. Our results suggested that urbanization process, agricultural activities, and large input of exogenous carbon could result in large spatial heterogeneity of CO₂ emissions and alter the CO₂ biogeochemical cycling in coastal reservoirs. Further studies should characterize the diurnal variations, microbial mechanisms, and impact of meteorological conditions on reservoir CO₂ emissions to expand our understanding of the carbon cycle in aquatic ecosystems.

Statistical power or more precise insights into neuro-temporal dynamics? Assessing the benefits of rapid temporal sampling in fMRI

Functional magnetic resonance imaging (fMRI), a non-invasive and widely used human neuroimaging method, is most known for its spatial precision. However, there is a growing interest in its temporal sensitivity. This is despite the temporal blurring of neuronal events by the blood oxygen level dependent (BOLD) signal, the peak of which lags neuronal firing by 4-6 seconds. Given this, the goal of this review is to answer a seemingly simple question - "What are the benefits of increased temporal sampling for fMRI?". To answer this, we have combined fMRI data collected at multiple temporal scales, from 323 to 1000 milliseconds, with a review of both historical and contemporary temporal literature. After a brief discussion of technological developments that have rekindled interest in temporal research, we next consider the potential statistical and methodological benefits. Most importantly, we explore how fast fMRI can uncover previously unobserved neuro-temporal dynamics - effects that are entirely missed when sampling at conventional 1 to 2 second rates. With the intrinsic link between space and time in fMRI, this temporal renaissance also delivers improvements in spatial precision. Far from producing only statistical gains, the array of benefits suggest that the continued temporal work is worth the effort.

Quantitative assessment of the habitat quality dynamics in Yellow River Basin, China

Habitat quality is an important indicator for measuring regional biodiversity and ecosystem service value. A change in habitat quality is the direct result of the interaction between human activities and the natural environment. In this study, the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model was used to evaluate the habitat quality of the Yellow River Basin (YRB) from 1980 to 2018. We further analyzed the quantity and spatial transfer status of habitat quality quantitatively using the Geo-informatic Tupu method. The results show that the habitat degradation degree under human disturbance showed a trend of increasing first and then decreasing, with values of 0.0196 in 1980, 0.0200 in 2000, and 0.0199 in 2018. In addition, it presents two ring structures: light-severe-high-moderate and light-moderate-high-severe in space. The overall level of habitat quality in the basin is relatively good, but there is a trend of decline, which are 0.6091, 0.6069, and 0.6049 in the three stages respectively. The spatial distribution of habitat quality showed a pattern of high in the middle and low on both sides. The habitat quality has been restored in some areas. The transition between good and medium and good and excellent in the Tupu change units of the habitat quality grade is the most intense. Both stages are mainly the transformation from high-grade to low-grade habitat quality, but there is a trend of gradual improvement. The findings could have theoretical support and policy implications for the maintenance of biodiversity and the protection of the natural environment in the Yellow River Basin.

Wastewater surveillance of SARS-CoV-2 across 40 U.S. states from February to June 2020

Wastewater-based disease surveillance is a promising approach for monitoring community outbreaks. Here we describe a nationwide campaign to monitor SARS-CoV-2 in the wastewater of 159 counties in 40 U.S. states, covering 13% of the U.S. population from February 18 to June 2, 2020. Out of 1,751 total samples analyzed, 846 samples were positive for SARS-CoV-2 RNA, with overall viral concentrations declining from April to May. Wastewater viral titers were consistent with, and appeared to precede, clinical COVID-19 surveillance indicators, including daily new cases. Wastewater surveillance had a high detection rate (>80%) of SARS-CoV-2 when the daily incidence exceeded 13 per 100,000 people. Detection rates were positively associated with wastewater treatment plant catchment size. To our knowledge, this work represents the largest-scale wastewater-based SARS-CoV-2 monitoring campaign to date, encompassing a wide diversity of wastewater treatment facilities and geographic locations. Our findings demonstrate that a national wastewater-based approach to disease surveillance may be feasible and effective.

Single-Cell Analysis of Mycobacteria Using Microfluidics and Time-Lapse Microscopy

Studies on cell-to-cell phenotypic variation in microbial populations, with individuals sharing the same genetic background, provide insights not only on bacterial behavior but also on the adaptive spectrum of the population. Phenotypic variation is an innate property of microbial populations, and this can be further amplified under stressful conditions, providing a fitness advantage. Furthermore, phenotypic variation may also precede a latter step of genetic-based diversification, resulting in the transmission of the most beneficial phenotype to the progeny. While population-wide studies provide a measure of the collective average behavior, single-cell studies, which have expanded over the last decade, delve into the behavior of smaller subpopulations that would otherwise remain concealed. In this chapter, we describe approaches to carry out spatiotemporal analysis of individual mycobacterial cells using time-lapse microscopy. Our method encompasses the fabrication of a microfluidic device; the assembly of a microfluidic system suitable for long-term imaging of mycobacteria; and the quantitative analysis of single-cell behavior under varying growth conditions. Phenotypic variation is conceivably associated to the resilience and endurance of mycobacterial cells. Therefore, shedding light on the dynamics of this phenomenon, on the transience or stability of the given phenotype, on its molecular bases and its functional consequences, offers new scope for intervention.

Probing the Functional and Structural Connectivity Underlying EEG Traveling Waves

Neural oscillations play an important role in the maintenance of brain function by regulating multi-scale neural activity. Characterizing the traveling properties of EEG is helpful for understanding the spatiotemporal dynamics of neural oscillations. However, traveling EEG based on non-invasive approach has little been investigated, and the relationship with brain intrinsic connectivity is not well known. In this study, traveling EEG of different frequency bands on the scalp in terms of the center of mass (EEG-CM) was examined. Then, two quantitative indexes describing the spatiotemporal features of EEG-CM were proposed, i.e., the traveling lateralization and velocity of EEG-CM. Further, based on simultaneous EEG-MRI approach, the relationship between traveling EEG-CM and the resting-state functional networks, as well as the microstructural connectivity of white matter was investigated. The results showed that there was similar spatial distribution of EEG-CM under different frequency bands, while the velocity of rhythmic EEG-CM increased in higher frequency bands. The lateralization of EEG-CM in low frequency bands (< 30 Hz) demonstrated negative relationship with the basal ganglia network (BGN). In addition, the velocity of the traveling EEG-CM was associated with the fractional anisotropy (FA) in corpus callosum and corona radiate. These results provided valid quantitative EEG index for understanding the spatiotemporal characteristics of the scalp EEG, and implied that the EEG dynamics were representations of functional and structural organization of cortical and subcortical structures.

Diversity of tomato-infecting begomoviruses and spatiotemporal dynamics of an endemic viral species of the Brazilian Atlantic rain forest biome

Yield losses induced by a complex of begomoviruses are observed across all major tomato-producing areas in Brazil. Tomato severe rugose virus (ToSRV) is the most widespread begomovirus in the country. Conversely, tomato common mosaic virus (ToCmMV) displays a more restricted geographical distribution to areas associated with the Atlantic Rain Forest (ARF) biome, encompassing the States of Espírito Santo-ES, Minas Gerais-MG, and Rio de Janeiro-RJ. Here, we characterized 277 tomato-infecting isolates collected in fields located within the ARF biome from 2006 to 2018. ToSRV displayed the highest prevalence (n = 157), followed by ToCmMV (n = 95) and tomato interveinal chlorosis virus (n = 14). Four other begomoviruses were also detected, but with very low incidences. ToCmMV was the predominant begomovirus in the ARF biome up to 2014-2015 with very low ToSRV incidence. Subsequently, ToSRV became the most prevalent species in ES and RJ, but ToCmMV was still predominating in the "Zona da Mata" meso-region in MG. Due to the remarkable endemic distribution of ToCmMV, we carried out phylogeographical studies of this virus using information from all 28 available isolates with complete DNA-A sequences. The closest common ancestor of ToCmMV was more likely originated around Coimbra-MG area ≈ 25 years before the formal report of this viral species. So far, all surveys indicated tomatoes as the only natural hosts of ToCmMV with outbreaks occurring mainly (but not exclusively) in highland areas. ToSRV shows a more widespread incidence across both highland and lowland areas of the ARF biome.

Reclamation shifts the evolutionary paradigms of tidal channel networks in the Yellow River Delta, China

Tidal channel networks are ubiquitous features of coastal landforms that control the input and output of intertidal water, sediment and nutrients. Nevertheless, those intertidal platforms have undergone extensive losses due to human activities such as land reclamation. Identifying how tidal channel networks respond to land reclamation is critical to our prediction of the fate of residual tidal landforms. However, the morphological changes in the channel networks in the Yellow River Delta (YRD) impacted by severe reclamation remain unclear. Here, we analyzed the spatiotemporal dynamics of channel networks on two scales (the delta scale and the zone scale) under the double stress of land reclamation and natural pressure by comparing a comprehensive suite of morphological channel characteristics, including channel segment count, channel order, length, fractal dimension, drainage density and drainage efficiency. The results show that the interannual dynamics of tidal channel networks in the delta over the last three decades have experienced two periods: a favorable period during 1984-2000 and an adverse period during 2001-2018. The spatiotemporal patterns of channel networks varied with zones. Land reclamation exerted a dominant influence on shifting the evolutionary trend of channel networks on both the delta scale and the zone scale when reclamation proportion exceeded a certain threshold. Sediment siltation could to a certain degree mitigate the impact of reclamation on tidal channel networks development. Our study highlighted the effect of reclamation on the geomorphological evolution of tidal channel networks and identified its impact threshold which could further be used to guide coastal zone restoration and management.

Comparing SNNs and RNNs on neuromorphic vision datasets: Similarities and differences

Neuromorphic data, recording frameless spike events, have attracted considerable attention for the spatiotemporal information components and the event-driven processing fashion. Spiking neural networks (SNNs) represent a family of event-driven models with spatiotemporal dynamics for neuromorphic computing, which are widely benchmarked on neuromorphic data. Interestingly, researchers in the machine learning community can argue that recurrent (artificial) neural networks (RNNs) also have the capability to extract spatiotemporal features although they are not event-driven. Thus, the question of "what will happen if we benchmark these two kinds of models together on neuromorphic data" comes out but remains unclear. In this work, we make a systematic study to compare SNNs and RNNs on neuromorphic data, taking the vision datasets as a case study. First, we identify the similarities and differences between SNNs and RNNs (including the vanilla RNNs and LSTM) from the modeling and learning perspectives. To improve comparability and fairness, we unify the supervised learning algorithm based on backpropagation through time (BPTT), the loss function exploiting the outputs at all timesteps, the network structure with stacked fully-connected or convolutional layers, and the hyper-parameters during training. Especially, given the mainstream loss function used in RNNs, we modify it inspired by the rate coding scheme to approach that of SNNs. Furthermore, we tune the temporal resolution of datasets to test model robustness and generalization. At last, a series of contrast experiments are conducted on two types of neuromorphic datasets: DVS-converted (N-MNIST) and DVS-captured (DVS Gesture). Extensive insights regarding recognition accuracy, feature extraction, temporal resolution and contrast, learning generalization, computational complexity and parameter volume are provided, which are beneficial for the model selection on different workloads and even for the invention of novel neural models in the future.

Spatiotemporal variability and key influencing factors of river fecal coliform within a typical complex watershed

Fecal coliform bacteria are a key indicator of human health risks; however, the spatiotemporal variability and key influencing factors of river fecal coliform have yet to be explored in a rural-suburban-urban watershed with multiple land uses. In this study, the fecal coliform concentrations in 21 river sections were monitored for 20 months, and 441 samples were analyzed. Multivariable regressions were used to evaluate the spatiotemporal dynamics of fecal coliform. The results showed that spatial differences were mainly dominated by urbanization level, and environmental factors could explain the temporal dynamics of fecal coliform in different urban patterns except in areas with high urbanization levels. Reducing suspended solids is a direct way to manage fecal coliform in the Beiyun River when the natural factors are difficulty to change, such as temperature and solar radiation. The export of fecal coliform from urban areas showed a quick and sensitive response to rainfall events and increased dozens of times in the short term. Landscape patterns, such as the fragmentation of impervious surfaces and the overall landscape, were identified as key factors influencing urban non-point source bacteria. The results obtained from this study will provide insight into the management of river fecal pollution.

Fire's impact on threat detection and risk perception among vervet monkeys: Implications for hominin evolution

The spatial behavior of primates is shaped by many factors including predation risk, the distribution of food sources, and access to water. In fire-prone settings, burning is a catalyst of change, altering the distribution of both plants and animals. Recent research has shown that primates alter their behavior in response to this change. Here, we study primates' perceived threat of predation in fire-modified landscapes. We focus on the predator-related behaviors of vervet monkeys (Chlorocebus pygerythrus) after controlled burning events. We compare the occurrence of vigilance and predator-deterrent behaviors, including alarm calls, scanning, and flight across different habitats and burn conditions to test the hypothesis that subjects exhibit fewer predator-specific vigilance and predator-deterrent behaviors in burned areas. The results demonstrate that predator-related behaviors occur less often in burned habitats, suggesting that predators are less common in these areas. These results provide foundations for examining hypotheses about the use of fire-altered landscapes among extinct hominins. We set these data in the context of increasing aridity, changes in burning regimes, and the emergence of pyrophilia in the human lineage.

Dynamics, differences, influencing factors of eco-efficiency in China: A spatiotemporal perspective analysis

Eco-efficiency can effectively measure the relationship between economy, resources, environment, and development. Understanding eco-efficiency is of great practical significance for decision makers tasked with addressing and delivering sustainable socioeconomic development. Based on an "undesirable output Slacks-Based Measure models," this study evaluated the eco-efficiency of 285 Chinese cities during the period 2004-2014, analyzing spatiotemporal dynamics and influencing factors using a Spatial Autocorrelation Panel Data Model. The main results are as follows: From the spatial perspective, eco-efficiency in Chinese cities generally evidenced an M-shaped trend (increasing-decreasing-increasing-decreasing), and imbalanced spatiotemporal dynamics. Furthermore, the urban eco-efficiency generally presented a distinct convergence of HH cluster and LL cluster clubs, with the latter being the most dominant. From the regional point of view, there existed a decreasing trend in the efficiencies of cities, from eastern China to central and western China. In addition, we identified significant differences in the eco-efficiency of different cities in China, and the coefficient of variation of eco-efficiency showed a general decrease. The results of our estimation of the factors affecting urban eco-efficiency showed that the economic development level, the industrial structure, import and export trade, and the information level all had significant positive influence, and local government expenditure, social retail sales of consumer goods, and infrastructure all had a negative effect on urban eco-efficiency. This paper puts forward numbers of suggestions for ways to promote social, ecological, and economic development in Chinese cities, based on our findings.

Reduced spatiotemporal brain dynamics are associated with increased depressive symptoms after a relationship breakup

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We investigated whole-brain measures of integration, hierarchy, and metastability.

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Depressive symptoms in a non-clinical sample revealed more static configurations.

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Constrained spatiotemporal dynamics correlated with increased depressive symptoms.

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Reduced global integration was associated with increased depressive symptoms.

Depressive symptoms following a stressful life event, such as a relationship breakup, are common, and constitute a potent risk factor for the onset of a major depressive episode. Resting-state neuroimaging studies have increasingly identified abnormal whole-brain communication in patients with depression, but it is currently unclear whether depressive symptoms in individuals without a clinical diagnosis have reliable neural underpinnings. We investigated to what extent the severity of depressive symptoms in a non-clinical sample was associated with imbalances in the complex dynamics of the brain during rest. To this end, a novel intrinsic ignition approach was applied to resting-state neuroimaging data from sixty-nine participants with varying degrees of depressive symptoms following a relationship breakup. Ignition-based measures of integration, hierarchy, and metastability were calculated for each participant, revealing a negative correlation between these measures and depressive ratings. We found that the severity of depressive symptoms was associated with deficits in the brain’s capacity to globally integrate and process information over time. Furthermore, we found that increased depressive symptoms were associated with reduced spatial diversity (i.e., hierarchy) and reduced temporal variability (i.e., metastability) in the functional organization of the brain. These findings suggest the merit of investigating constrained dynamical complexity as it is sensitive to the level of depressive symptoms even in a non-clinical sample.

Spatiotemporal Dynamics of Single and Paired Pulse TMS-EEG Responses

For physiological brain function a particular balance between excitation and inhibition is essential. Paired pulse transcranial magnetic stimulation (TMS) can estimate cortical excitability and the relative contribution of inhibitory and excitatory networks. Combining TMS with electroencephalography (EEG) enables additional assessment of the spatiotemporal dynamics of neuronal responses in the stimulated brain. This study aims to evaluate the spatiotemporal dynamics and stability of single and paired pulse TMS-EEG responses, and assess long intracortical inhibition (LICI) at the cortical level. Twenty-five healthy subjects were studied twice, approximately one week apart. Manual coil positioning was applied in sixteen subjects and robot-guided positioning in nine. Both motor cortices were stimulated with 50 single pulses and 50 paired pulses at each of the five interstimulus intervals (ISIs): 100, 150, 200, 250 and 300 ms. To assess stability and LICI, the intraclass correlation coefficient and cluster-based permutation analysis were used. We found great resemblance in the topographical distribution of the characteristic TMS-EEG components for single and paired pulse TMS. Stimulation of the dominant and non-dominant hemisphere resulted in a mirrored spatiotemporal dynamics. No significant effect on the TMS-EEG responses was found for either stimulated hemisphere, time or coil positioning method, indicating the stability of both single and paired pulse TMS-EEG responses. For all ISIs, LICI was characterized by significant suppression of the late N100 and P180 components in the central areas, without affecting the early P30, N45 and P60 components. These observations in healthy subjects can serve as reference values for future neuropsychiatric and pharmacological studies.

Multiscale analysis on spatiotemporal dynamics of energy consumption CO2 emissions in China: Utilizing the integrated of DMSP-OLS and NPP-VIIRS nighttime light datasets

CO₂ emissions caused by socioeconomic development and energy consumption in China have put enormous pressure on emissions reduction for Chinese government. In response to CO₂ emissions reduction in China, this study integrated the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) stable nighttime light (SNL) data and Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) composite data, and established the integrated nighttime light datasets from 1992 to 2016. The estimated CO₂ emissions model utilizing the integrated nighttime light datasets and statistical CO₂ emissions at the provincial level from 1995 to 2016 were established. Finally, spatiotemporal dynamics of CO₂ emissions were simulated from multiscale. The results clearly showed that: (1) The fitting results of regression relationship between DMSP-OLS SNL data and NPP-VIIRS composite data met the accuracy requirements. The CO₂ emissions estimated model was valid. (2) The total amount of energy consumption CO₂ emissions in China had increased from 1889.3340 Mt in 1995 to 4683.3165 Mt in 2016, with a total growth of 2.47 times. (3) The high CO₂ emissions regions were clearly agglomerated in eastern coastal China from the pixel scale, the highest CO₂ emissions provinces were concentrated in Hebei and Shandong, the high CO₂ emissions prefecture cities were concentrated in Around Bohai Gulf area, eastern coastal China and some developed cities, and the high CO₂ emissions counties were concentrated in eastern coastal China and western energy intensive counties. (4) The relatively-slow growth accounted for the highest proportion among the five growth types, and the CO₂ emissions rapid growth regions were concentrated in eastern China at provincial, prefectural and county scale. The western regions accounted for the largest area proportion in five growth types at prefectural scale. We provided policy implications based on the results, which was beneficial to propose mitigation CO₂ emissions reduction in China.

Optogenetic approaches to investigate spatiotemporal signaling during development

Embryogenesis is coordinated by signaling pathways that pattern the developing organism. Many aspects of this process are not fully understood, including how signaling molecules spread through embryonic tissues, how signaling amplitude and dynamics are decoded, and how multiple signaling pathways cooperate to pattern the body plan. Optogenetic approaches can be used to address these questions by providing precise experimental control over a variety of biological processes. Here, we review how these strategies have provided new insights into developmental signaling and discuss how they could contribute to future investigations.