Study of spatial distribution characteristics of river eco-environmental values based on emergy-GeoDa method

Prediction of change in suitable habitats of Senna obtusifolia and Senna tora under climate change

Senna obtusifolia (L.) Irwin & Barneby and Senna tora (L.) Roxb represent important medicinal resources in traditional Chinese medicine for more than two millennia. Sustainable resource utilization and preservation strategies for Senna species necessitate a thorough understanding of the climatic factors governing their distribution patterns. Therefore, this study aimed to identify the key climate variables shaping the current and potential future global distribution of both Senna species. To achieve this, the MaxEnt ecological niche model was employed, integrating species occurrence data with relevant environmental variables. The results indicated that Bio13 and Bio14 were the most critical variables affecting distribution of S. tora, while Bio6 and Bio14 were crucial for S. obtusifolia. The moderate and high suitability habitats of S. obtusifolia and S. tora consist of ca. 189.69 × 104 km2 and 129.07 × 104 km2, respectively, under current situation. Moreover, the global distribution of both species under various climate scenarios revealed that the suitable habitats of both Senna species will reach the maximum during the 2081-2100 period under the SSP585 scenario. Projections across all four climate scenarios indicate a general northward migration in the core distribution of both Senna species. Intriguingly, the observed high degree of ecological niche overlap between the two species aligns with their close phylogenetic relationship. These findings provide valuable insights into the potential future distribution and ecological niche of Senna species, informing sustainable utilization and preservation strategies for Senna resources.

Characterizing the water resource-environment-ecology system harmony in Chinese cities using integrated datasets: A Beautiful China perspective assessment

Integrated management and synergistic improvement of the water system is a topic of widespread concern. This study innovatively integrates three functions of quality assessment, synergy evaluation, and driving influence determination to establish a systematic framework assessing water system harmony. A case study of 336 Chinese cities is further performed by combining multi-scale and multi-source datasets. The results show China's water system quality has improved from 2015 to 2022. Development in the water resource, environment, and ecology subsystems have been differentiated, with 0.05 %, 4.33 %, and -1.64 % changes, respectively. The degradation of water ecology and the weak synergy with the other two subsystems have limited China's water system harmony. Water environment improvement played a contributive role in improving the water system quality. The contribution structure of water resources, environment, and ecology has shifted towards equilibrium in recent years. We found and highlighted the north-south differentiation of water system harmony in Chinese cities. The Beijing-Tianjin-Hebei and its surroundings, the Yangtze River Delta, and the middle reaches of the Yangtze River are identified as priority regions for water system harmony improvement. The primary contribution of this study is to propose an assessing concept of water resource-environment-ecology system harmony, establish well-structured assessment methods, and integrate the multiple data sources. The novel methods and findings, including the indicator system, application of data mining and decomposing methods, and the city-level water system harmony map, deconstruct and quantify the complex and diverse water system, supporting clearer and more efficient water management policymaking.

Dynamic evaluation and prediction of the ecological environment quality of the urban agglomeration on the northern slope of Tianshan Mountains

In order to timely determine the dynamic changes of the ecological environment quality and future development laws of the urban agglomeration on the northern slope of the Tianshan Mountains, combined with the actual situation of the urban agglomeration, 11 indicators were selected from the three aspects of natural ecology, social ecology, and economic ecology. To reduce the dimensions of the indicators, principal component analysis, coefficient of variation, and analytic hierarchy process were used based on RS and GIS technology methods, and the ecological environmental quality (EQI) from 2000 to 2018 was dynamically evaluated. Further, the CA-Markov model was introduced to simulate the development status in 2026 for predictive purposes. The main results are as follows: the overall ecological environment of the area exhibited a gradually improving distribution change from southwest to northeast; the proportion of ecological environment classification exhibited a gradually decreasing change pattern; the spatial differentiation of ecological environment quality exhibited a significant spatial positive correlation; from the influencing factors, an observation can be made that natural ecological factors were highly significant; the prediction accuracy verification revealed that the CA-Markov model was suitable for the prediction of the ecological environment quality in the region and had high accuracy; and the comprehensive regional ecological environment quality indexes were 5.7392, 6.1856, and 6.4366, respectively, while the forecasted value for 2026 was predicted to be 6.6285, indicating that the overall ecological environment quality of the region will improve and develop well. The present research results reveal the law of dynamic changes and future development of the ecological environment quality in the region, which can be used as a theoretical reference for the formulation of ecological environmental protection measures.

A global spatial analysis of factors associated with case and mortality rates for coronavirus disease 2019 during the first year of the pandemic

BACKGROUND

A increasing number of studies have revealed associations between country-level determinants and coronavirus disease 2019 (COVID-19) outcomes. This ecological study was conducted to analyze country-level parameters related to COVID-19 infections and deaths during the first year of the pandemic.

METHODS

The examined predictors comprised demographics, economic factors, disease prevalence and healthcare system status, and the relevant data were obtained from public databases. The index dates were set to 15 July 2020 (Time 1) and 15 December 2020 (Time 2). The adjusted spatial autoregression models used a first-order queen contiguity spatial weight for the main analysis and a second-order queen contiguity spatial weight for a sensitivity analysis to examine the predictors associated with COVID-19 case and mortality rates.

RESULTS

Obesity was significantly and positively associated with COVID-19 case and mortality rates in both the main and sensitivity analyses. The sensitivity analysis revealed that a country's gross domestic product, population density, life expectancy and proportion of the population older than 65 y are positively associated with COVID-19 case and mortality rates.

CONCLUSIONS

With the increasing global prevalence of obesity, the relationship between obesity and COVID-19 disease at the country level must be clarified and continually monitored.

Effects of human activity intensity on habitat quality based on nighttime light remote sensing: A case study of Northern Shaanxi, China

Habitat quality is a crucial expression of the value of ecosystem services. Habitat quality issues caused by human activities are troubling dilemmas worldwide, and there is an urgent need to assess the impact of the large-scale human activity intensity on habitat quality. In this study, Northern Shaanxi, China, is used as an example to demonstrate how the impact on habitat quality can be explored by simulating the intensity of human activities using nighttime light remote sensing data from 2000 to 2020. Defense Meteorological Satellite Program-Operational Linescan System (DMSP-OLS) data, Visible Infrared Imaging Radiometer Suite-Day-Night Band (VIIRS-DNB) data, and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model were used in this study. The results showed that from 2000 to 2020, human activity intensity in Northern Shaanxi increased by 361.4 %, and the habitat quality decreased by 2.3 %. Habitat quality was more spatially clustered and spatially dependent than habitat degradation. Human activity intensity and habitat quality were significantly correlated. Habitat quality in Yulin city decreased significantly compared with that in Yan'an city. The differences in human activity types and economic structures of Yulin and Yan'an were an important factor for this phenomenon. The assessment of the impact of human activity intensity on habitat quality using nighttime light data is feasible and can be applied in other larger regions worldwide.

Assessment of eco-economic effects of urban water system connectivity project

As one of the large ecological infrastructures, the urban water system connectivity (UWSC) project is an important part of urban ecosystem construction. It is helpful for the scientific planning and construction of the project to systematically evaluate the effects. However, due to the complex and various effects of UWSC project, there is no complete effect system and quantitative method. Against this backdrop, the composition and mechanism of positive and negative effects of ecological economics of UWSC project were deeply analyzed to improve the composition system of eco-economic effects in this study. At the same time, the emergy theory was used to put forward the quantification method of eco-economic effect system. Taking the UWSC project in Xuchang as an example, its ecological, social, and economic effects were evaluated. The result showed that the average eco-economic effect of the project is 49.97 million dollars/year. Economic effect and ecological effect are significant, accounting for 82.49% and 15.89% of total effect, respectively. This study can provide reference for comprehensive and unified assessment of eco-economic effects of UWSC project.

Management implications of spatial-temporal variations of net anthropogenic nitrogen inputs (NANI) in the Yellow River Basin

It is an important content of environment management to accurately identify the time change and spatial distribution of net anthropogenic nitrogen inputs (NANI) in the river basin. In order to develop a unified management and diverse control strategy that fits the characteristics of the basin, this study establishes the NANI-S model combining the NANI model with the spatial autocorrelation analysis method, which is a quantification-analysis-control process, and takes the 70 prefecture-cities in the Yellow River Basin (YRB) as the study area. The result shows that (1) the NANI of YRB increased first and then decreased with an average NANI value of 6787.59 kg/(km²·a), showing that the overall N pollution situation of the YRB shows a trend of improvement in nitrogen (N) fertilizer input as the main source, and the average contribution rate was 47.45%. (2) There were obvious spatial differences in the NANI in the YRB because the global Moran's I fluctuated between 0.67 and 0.78. Cities with high NANI clustered in the middle and lower reaches, while low NANI clustered in the upper reaches. (3) Improving fertilizer utilization rate and industrial and domestic sewage treatment capacity was the key point of N control. Based on the results, practical policy recommendations for water pollution management were constructed, which provides a scientific basis for pollution prevention and high-quality development in the basin. In addition, this analysis method can also be applied to other basin N management studies.

Spatial-temporal Distribution and Influencing Factors of Helicobacter pylori Infection in Chinese Mainland, 2001-2020: A Systematic Review and Meta-Analysis

BACKGROUND

The spatial-temporal distribution of Helicobacter pylori infection in China is poorly understood. We aimed to study the spatial-temporal distribution of H. pylori infection in Chinese mainland and to explore its influencing factors.

MATERIALS AND METHODS

We searched the relevant literature from 2001 to 2021 and applied meta-analysis to obtain the pooled prevalence estimates of all studies and subgroups. Then, we used the pooled prevalence as the dependent variable for the following analysis, including time series analysis, statistical mapping, spatial autocorrelation analysis, and influencing factor analysis based on generalized additive model and panel data model.

RESULTS

A total of 726 articles and 3,407,392 people were included. The pooled prevalence was 43.7% (95% confidence interval: 42.7%-44.8%). The prevalence decreased in the past 20 years, with high in the eastern and western regions and low in the central region. Qinghai Tibet Plateau and Guizhou Plateau were the high incidence areas of this disease. The intake of vegetable oil, aquatic products, meat, milk, per capita gross domestic product, and annual average humidity were significantly correlated with H. pylori.

CONCLUSIONS

The prevalence of H. pylori is decreasing in Chinese mainland, but still high in underdeveloped areas. Appropriate strategies for the prevention need greater attention.

Modeling of the Potential Geographical Distribution of Three Fritillaria Species Under Climate Change

Fritillaria species, a well-known Chinese traditional medicine for more than 2,000 years, have become rare resources due to excessive harvesting. In order to balance the economical requirement and ecological protection of Fritillaria species, it is necessary to determine (1) the important environmental variables that were responsible for the spatial distribution, (2) distribution change in response to climate change in the future, (3) ecological niche overlap between various Fritillaria species, and (4) the correlation between spatial distribution and phylogenies as well. In this study, the areas with potential ecological suitability for Fritillaria cirrhosa, Fritillaria unibracteata, and Fritillaria przewalskii were predicted using MaxEnt based on the current occurrence records and bioclimatic variables. The result indicated that precipitation and elevation were the most important environmental variables for the three species. Moreover, the current suitable habitats of F. cirrhosa, F. unibracteata, and F. przewalskii encompassed 681,951, 481,607, and 349,199 km2, respectively. Under the scenario of the highest concentration of greenhouse gas emission (SSP585), the whole suitable habitats of F. cirrhosa and F. przewalskii reach the maximum from 2021 to 2100, while those of F. unibracteata reach the maximum from 2021 to 2100 under the scenario of moderate emission (SSP370) from 2021 to 2100. The MaxEnt data were also used to predict the ecological niche overlap, and thus high overlap occurring among three Fritillaria species was observed. The niche overlap of three Fritillaria species was related to the phylogenetic analysis despite the non-significance (P > 0.05), indicating that spatial distribution was one of the factors that contributed to the speciation diversification. Additionally, we predicted species-specific habitats to decrease habitat competition. Overall, the information obtained in this study provided new insight into the potential distribution and ecological niche of three species for the conservation and management in the future.

Urban Vitality Evaluation and Spatial Correlation Research: A Case Study from Shanghai, China

Urban vitality is the primary driver of urban development. However, assessing urban vitality has always been a challenge. This paper builds on the research framework of sustainable development evaluation and selects evaluation indicators from the three systems of urban operation: economy, society, and environment. The deviation maximization (DM) method is used to evaluate urban vitality. Shanghai is then used as a case study for evaluation, and the comprehensive index of urban vitality is calculated for the city from 2010 to 2019. The evaluation results indicate that the urban vitality of Shanghai experienced a significant upward trend over ten years (2010–2019), which shows that the urban competitiveness of Shanghai is constantly strengthening. Next, the study focuses on the administrative region of Shanghai, to calculate the regional vitality level of Shanghai from 2010 to 2019 and to explore its spatial distribution characteristics. Then, a spatial autocorrelation analysis is used to explore the mechanism that affects the spatial distribution of urban vitality. The results demonstrate that the urban vitality in Shanghai shows a significant positive correlation in space. Moreover, there is a “High–High” gathering area, which includes Huangpu, Xuhui, Hongkou, and Changning in central area of Shanghai. This research provides a theoretical reference to support effective decision-making with respect to high-quality urban development.