Abstract Background Global connectivity and environmental change pose continuous threats to dengue invasions from worldwide to China. However, the intrinsic relationship on introduction and outbreak risks of dengue driven by the landscape features are still unknown. This study aimed to map the patterns on source-sink relation of dengue cases and assess the driving forces for dengue invasions in China. Methods We identified the local and imported cases (2006–2020) and assembled the datasets on environmental conditions. The vector auto-regression model was applied to detect the cross-relations of source-sink patterns. We selected the major environmental drivers via the Boruta algorithm to assess the driving forces in dengue outbreak dynamics by applying generalized additive models. We reconstructed the internal connections among imported cases, local cases, and external environmental drivers using the structural equation modeling. Results From 2006 to 2020, 81,652 local dengue cases and 12,701 imported dengue cases in China were reported. The hotspots of dengue introductions and outbreaks were in southeast and southwest China, originating from South and Southeast Asia. Oversea-imported dengue cases, as the Granger-cause, were the initial driver of the dengue dynamic; the suitable local bio-socioecological environment is the fundamental factor for dengue epidemics. The Bio8 [odds ratio ( OR) = 2.11, 95% confidence interval ( CI) : 1.67–2.68], Bio9 ( OR = 291.62, 95% CI : 125.63–676.89), Bio15 ( OR = 4.15, 95% CI : 3.30–5.24), normalized difference vegetation index in March ( OR = 1.27, 95% CI : 1.06–1.51) and July ( OR = 1.04, 95% CI : 1.00–1.07), and the imported cases are the major drivers of dengue local transmissions ( OR = 4.79, 95% CI : 4.34–5.28). The intermediary effect of an index on population and economic development to local cases via the path of imported cases was detected in the dengue dynamic system. Conclusions Dengue outbreaks in China are triggered by introductions of imported cases and boosted by landscape features and connectivity. Our research will contribute to developing nature-based solutions for dengue surveillance, mitigation, and control from a socio-ecological perspective based on invasion ecology theories to control and prevent future dengue invasion and localization. Graphical Abstract 

/pdf/the-patterns-and-driving-forces-of-dengue-invasions-in-china-3g8reo5x.pdf

The patterns and driving forces of dengue invasions in China

Drought propagation is a complex process involving various components of water cycle. Clarifying the propagation pathways and mechanisms among multiple types of droughts is essential. However, the current drought propagation analysis mainly focuses on the relationship between two types of droughts, which highlights the urgence in studying the propagation among multiple types of droughts. To this end, this study will first develop a dynamic threshold framework to identify the propagation pathways among meteorological, hydrological, agricultural and groundwater droughts, and further investigate the risk probability, trigger threshold and their controlling factors in the long-chain drought propagation. The propagation pathways among multi-type droughts were identified as meteorological-hydrological-agricultural-groundwater drought. In the long-chain drought propagation, the spatial heterogeneity of risk probability and trigger threshold in China is significant. Among them, the risk probability triggering the next stage decreases progressively in south China, and the drought propagation is blocked. A significant upward trend exhibited in the trigger thresholds in east China, indicating that drought resistance is weakening. Temperature, aridity index and soil evaporation flux are the main drivers affecting the dynamics of trigger thresholds. This study contributes to the completeness and systematization of the propagation process of drought in the water cycle. It not only offers new insights into the process of drought propagation, but also provides scientific guidance for establishing drought early warning systems and reducing drought hazards. 

Long-chain propagation pathways from meteorological to hydrological, agricultural and groundwater drought and their dynamics in China

Restoring degraded ecosystems in drylands is challenging because of low precipitation and high evapotranspiration. Water availability determines the existence and spatiotemporal distribution patterns of key endangered species struggling to survive in the severely damaged desert riparian ecosystem of the lower Tarim River (LTR) in NW China. Ecological water flow restoration measures with high costs and uncertainties have been implemented since 2000. The key task for scientists is to assess the success and drawbacks of this restoration project and propose specific recommendations for stakeholders to optimize the ecological benefits of the project in a cost-effective manner. In this study, Landsat time-series data from 1990 to 2020 were used to extract vegetation index values from river corridors along the LTR and explore the spatiotemporal patterns of desert riparian forest (DRF) vegetation. Based on land use and surface water data, we extracted the interannual spatial distribution range of vegetation and surface water, and selected several sample plots to demonstrate the influence of surface water and groundwater on vegetation change trends. The study results showed the following. 1) From 1990 to 1999, the vegetation slowly degraded; from 2000 to 2012, the extent of vegetation restoration was approximately 1 km from the river; and from 2013 to 2020, the extent of vegetation restoration at the Yingsu and Karday sections increased to 4.5–6.0 km, while that at the Arghan and Yiganbujima sections remained within 1 km from the river. 2) The vegetation growth rate increased substantially and was spatially heterogeneous when the groundwater level reached 4.0–5.0 m and was influenced by surface water divergence; the average vegetation expansion rates per square km for P1–P4 were 0.017 km2/a, 0.011 km2/a, 0.005 km2/a, and 0.002 km2/a, respectively. 3) Flooding by surface water was the main driver of vegetation expansion when groundwater was stable and elevations in surface vegetation area were often accompanied by the spreading of surface water. Surface water was significantly correlated with vegetation cover and normalized difference vegetation index (NDVI) (Water pixels–Vegetation cover [P1: R2 = 0.57, P < 0.001; P2: R2 = 0.45, P < 0.01]; Water pixels–NDVI [P1: R2 = 0.22, P < 0.05; P2: R2 = 0.40, P < 0.01]). The increase in surface vegetation has alleviated the desertification process in the LTR, and the survival of the poplar has been mitigated. The results of this paper can help decision makers to formulate reasonable ecological water conveyance strategies and realize sustainable management of DRF ecosystems in arid zones. 

Impact of water supply on the restoration of the severely damaged riparian plants along the Tarim River in Xinjiang, Northwest China

Exposure to air pollutants of fine particulate matter (PM2.5) is a major threat to human health. Research on PM2.5 exposure has been on the rise in recent years, but there has been a lack of systematic literature analysis in this field. To address this research gap, we conducted a bibliometric analysis of the existing publications on PM2.5 exposure over the past three decades and analyzed the current state and historical trends of research using the open-access tool, KNIME. Our results show that the number of publications on PM2.5 exposure has been increasing at an accelerating rate over the last 30 years. The authors of the publications are primarily from developed nations, such as countries in North America, Europe, East Asia, and Oceania. Published research is mainly from the fields of Environmental Sciences and Ecology, Environmental Sciences, and Public, Environmental and Occupational Health. The main research hotspots are exposure, air pollution, and PM2.5. Research is trending toward the intersection and integration of multiple subjects. Our results highlight the rapid growth of PM2.5-related research and provide insights into the structure, impact, and trends of this interdisciplinary field.

https://www.mdpi.com/2071-1050/15/13/10509/pdf?version=1688451558

A Review of Global PM2.5 Exposure Research Trends from 1992 to 2022

Groundwater resources in arid regions play a vital role in meeting water demands; however, they are facing rapid depletion due to unsustainable exploitation practices, exacerbated by climate change. Floods can present a unique opportunity for restoring groundwater levels and mitigating saltwater intrusion into aquifers. The use of properly managed floodwater for aquifer recharge offers a dual advantage by maximizing the potential of floods as a valuable water resource, while minimizing their negative impacts. In this work, we applied a GIS-based Multi-Criteria Decision-Making (MCDM) method, namely the Analytic Hierarchy Process (AHP), to delineate flood susceptible zones and groundwater recharge zones in Qatar, considering several influential topographical, hydrological, environmental, and anthropological criteria. The maps of flood susceptibility and groundwater recharge potential were validated using recent flooding events and existing recharge wells data, respectively. Sensitivity analysis was conducted on both variables to further assess their accuracy. The overlay analysis of the two validated maps suggests that approximately 64% of the Qatar peninsula presents medium to excellent suitability for aquifer recharge using floodwater. The areas best suited for floodwater-based recharge intervention are the northern and coastal regions of the peninsula, while the urban areas and southwestern area are less suitable. This study provides decision-makers with spatially explicit information on areas in Qatar that can be targeted for aquifer recharge projects using floodwater as well as recommendations on technical, economic, and regulatory considerations that require additional investigation. The approach employed can be effectively applied in similar flood-prone arid regions and is adaptable to diverse contexts. 

Identifying suitable zones for integrated aquifer recharge and flood control in arid Qatar using GIS-based multi-criteria decision-making

As one of the earliest remote sensing indices, the Normalized Difference Vegetation Index (NDVI) has been employed extensively for vegetation research. However, despite an abundance of NDVI review articles, these studies are predominantly limited to either one subject area or one area, with systematic NDVI reviews being relatively rare. Bibliometrics is a useful method of analyzing scientific literature that has been widely used in many disciplines; however, it has not yet been applied to comprehensively analyze NDVI research. Therefore, we used bibliometrics and scientific mapping methods to analyze citation data retrieved from the Web of Science during 1985–2021 with NDVI as the topic. According to the analysis results, the amount of NDVI research increased exponentially during the study period, and the related research fields became increasingly varied. Moreover, a greater number of satellite and aerial remote sensing platforms resulted in more diverse NDVI data sources. In future, machine learning methods and cloud computing platforms led by Google Earth Engine will substantially improve the accuracy and production efficiency of NDVI data products for more effective global research.

/pdf/bibliometric-analysis-of-global-ndvi-research-trends-from-2kakj0fh.pdf

Bibliometric Analysis of Global NDVI Research Trends from 1985 to 2021

: Normalized Difference Vegetation Index (NDVI) is one of the most commonly used remote sensing indexes for vegetation research. Long-term NDVI data is of great significance on the study of vegetation change. This dataset contains the monthly maximum synthesized NDVI data in China from 1982 to 2020. It is mainly based on the NOAA CDR AVHRR NDVI product using the rgee package in R to call Google Earth Engine for monthly maximum synthesis and cropping. This dataset can reflect the spatio-temporal changes of China's NDVI from 1982 to 2020

A 5 km resolution dataset of monthly NDVI product of China (1982–2020)

Soil moisture is a key factor in ecosystems that profoundly affects carbon, nitrogen, and water cycles on land surfaces, vegetation growth, and climate change. Consequently, numerous scholars have researched and authored scientific literature on soil moisture and related topics. Using the Web of Science database, we conducted a bibliometric analysis of 60,581 papers published in the field of soil moisture between 2000 and 2022. The findings revealed the following trends. (1) The number of publications on soil moisture has consistently increased in the 21st century at an increasing rate. For instance, although the annual increase was only 94 publications in 2005, it surged to 321 publications in 2020. (2) The United States (US), China, and developed European countries emerged as primary research institutions and authors. The US occupies a leading position in soil moisture research, boasting the highest number of publications and total citations in the field, whereas China ranks second in both publications and total citations. (3) Regarding international collaboration, the US has established close partnerships with numerous international research institutions. However, China’s international cooperation in this field requires improvement. (4) The Journal of Hydrology holds the top position in terms of both the total number of published articles and citations. Research on water resources ranked first in terms of its H-index. (5) Keyword analysis highlighted several current research hotspots, including the coupled covariance effect of soil moisture and land surface environmental factors in the context of climate change, soil moisture utilization rate, crop yield, influence mechanism of soil moisture on soil ecosystem structure, and development of high-precision soil moisture data products. In conclusion, this study provides a systematic review of the research hotspots and trends in soil moisture studies in the 21st century. The objective is to offer a comprehensive reference to aid in understanding the evolutionary patterns of soil moisture research in multiple dimensions. 

Analysis of Hotspots and Trends in Soil Moisture Research since the 21st Century

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Bibliometric Analysis of Global NDVI Research Trends from 1985 to 2021

A 5 km resolution dataset of monthly NDVI product of China (1982–2020)

Analysis of Hotspots and Trends in Soil Moisture Research since the 21st Century