Determining the main contributing factors to nutrient concentration in rivers in arid northwest China using partial least squares structural equation modeling.

Understanding the main driving factors of oasis river nutrients in arid areas is important to identify the sources of water pollution and protect water resources. Twenty-seven sub-watersheds were selected in the lower oasis irrigated agricultural reaches of the Kaidu River watershed in arid Northwest China, divided into the site, riparian, and catchment buffer zones. Data on four sets of explanatory variables (topographic, soil, meteorological elements, and land use types) were collected. The relationships between explanatory variables and response variables (total phosphorus, TP and total nitrogen, TN) were analyzed by redundancy analysis (RDA). Partial least squares structural equation modeling (PLS-SEM) was used to quantify the relationship between explanatory as well as response variables and fit the path relationship among factors. The results showed that there were significant differences in the TP and TN concentrations at each sampling point. The catchment buffer exhibited the best explanatory power of the relationship between explanatory and response variables based on PLS-SEM. The effects of various land use types, meteorological elements (ME), soil, and topography in the catchment buffer were responsible for 54.3% of TP changes and for 68.5% of TN changes. Land use types, ME and soil were the main factors driving TP and TN changes, accounting for 95.56% and 94.84% of the total effects, respectively. The study provides a reference for river nutrients management in arid oases with irrigated agriculture and a scientific and targeted basis to mitigate water pollution and eutrophication of rivers in arid lands.

Unveiling the complex networks of urban tree diversity research: A global perspective.

Ecosystem services offered by urban forests must be proactively managed to remain diverse and sustainable. Recent research findings deserve a systematic synthesis to elucidate inherent knowledge structures and dynamics. This study focused on the urban tree diversity theme from 2000 to 2022. Web of Science Core Collection database provided bibliometric details on academic publications. The data-driven quantitative analysis explored research quantities, emphasis, trends, patterns, linkages, and impacts by countries, institutions, authors, journals, and citations. Publications and research topics have expanded continually, with accelerated growth in recent years. Research activities, outputs and interactions demonstrated conspicuous spatial clustering. A few countries, institutions and researchers generated a notable proportion of publications. Their scholarly contributions were visualized in knowledge graphs as complex networks of nodes and inter-node links. Keyword analysis generated a network to indicate research hotspots and frontiers to steer and prioritize future studies. Recent findings affirmed that cities can harbor substantial tree diversity due to enhanced habitat heterogeneity and successful species adaptation. Aligning tree traits with environmental conditions and management objectives can improve benefits. Urbanization can filter tree traits to shape community assemblages through stressors: habitat degradation, fragmentation and loss, in conjunction with pollution, climate change, and introduced species. Diversity preservation strategies include protecting remnant natural vegetation, connecting green spaces, and restoring complex canopy geometry and biomass structure. The emerging frontiers are marked by modeling future species distributions, leveraging technologies like remote sensing, linking ecology with human values, and committing to community-based stewardship. Management can be upgraded by interdisciplinary perspectives integrating ecological science and social engagement. The findings highlight the need for biodiversity enrichment anchored by native species, trait-matched assemblages, adaptive policies, and community participation to create livable-green cities. This review synthesizes key advances in urban tree ecology and biodiversity research to inform the planning and stewardship of resilient urban forests.

Distribution pattern of large old Ginkgo biloba in China under climate change scenarios.

Large old Ginkgo biloba trees (LOGTs), with profound ecological and cultural significance in China, face increasing threats from climate change and human activities. We employed the BIOCLIM and DOMAIN species distribution models to predict their spatial patterns under the present climate and doubled-CO2 climate change scenario in 2100. We collected 604 validated LOGT occurrence records and data on 19 bioclimate factors for the analysis. Our study yielded a LOGT geographic distribution pattern covering a wide latitudinal belt extending from south subtropical to temperate zones in central and eastern China, concentrating in low elevations and coastal regions. The principal component analysis identified the dominant bioclimatic factors shaping their distribution, namely annual precipitation and low winter temperatures. BIOCLIM and DOMAIN generated predicted suitable habitats that match the present distribution range well. However, under the future climate scenario, the models indicated habitat retentions mainly in the core distribution areas and habitat losses mainly in the southern edge of the present range and scattered pockets elsewhere. Some retained habitats, including excellent ones, will suffer from fragmentation. The predicted new habitats may permit some range expansion and migration but are beset by small patch size and large interpatch distance, bringing fragmentation and gene flow restrictions. The anticipated projected range decline highlights considerable threats climate change poses to the long-term survival of the precious natural-cum-cultural resource. Understanding the distribution patterns and underlying drivers and distillation of practical conservation measures can foster sustainable management vis-a-vis the looming global change.

Spatio-temporal evolution of landscape patterns in an oasis city.

Studying the spatial-temporal evolution of oasis urban landscape patterns can provide a unique reference for future sustainable development. This study aimed to characterize the spatio-temporal evolution of landscape patterns in the past 20 years. The remote sensing and spatial analysis techniques included land transfer matrix, orientation evolution combined with landscape index, natural driving factor, and mass center migration model. The results showed that (1) two decades of urbanization brought prominent LULC changes. An increase of 464.8 km2 in the building area denoted the dominant change. (2) Changes in building, bare land, and green space occurred mainly in the northwest orientation. The patch Aggregation Index (AI) increased continually during building expansion. Meanwhile, the Landscape Division Index (DIVISION) experienced a progressive and complementary decline. (3) Increase in building land was associated with topography (DEM) and vegetation cover (NDVI). A lower elevation induced a larger building increment. Around NDVI average value for bare land (0.137) and farmland (0.477), building land had the largest expansion, verifying its principal land sources. (4) The center of gravity of building land overall migrated towards the north, and green space and bare land towards the south due to building encroachment. The findings could inform future sustainable urban development.

Assessing Spatial Accessibility of Community Hospitals for the Elderly in Beijing, China.

Accessibility of health services signifies the quality and equitability of universal health provision. The hierarchical medical system recently implemented in China offers the policy instruments to improve medical services to the elderly in an aging society. As the critical primary care gateway, accessibility to community hospitals has significant impacts on people's health. However, current research has paid little attention to spatial accessibility within walking distance of community hospitals, especially for the elderly. This study selected four districts with different urbanization levels in the rapidly developing Beijing metropolis. The spatial interaction model was applied to measure the accessibility of community hospitals for the elderly at the community level. An attractiveness index was computed based on key hospital traits. The results showed that: (1) community hospitals could cover 82.66% of elderly residents, and 77.63% of the communities were within walking distance. The served elderly proportion was relatively high in central urban areas and low in the suburbs. (2) The attractiveness indices of hospitals varied notably between districts, with higher values in more urbanized areas. (3) The spatial accessibility for the elderly of hospitals differed significantly between the four districts, with a descending gradient from central to suburban and rural areas, as indicated by the Gini coefficients and Lorenz curves. (4) The accessibility index was strongly related to the served elderly population and the hospital-residence distance. The findings provide policy directions to the government, including providing more primary-care resources to suburban and rural areas, building new community hospitals in identified provision gaps, upgrading some clinics to hospitals in rural areas, and planning hospitals according to the projected trend of the elderly population in terms of quantity and distribution. The considerable provision disparity between core urban, suburban and rural areas can be addressed by refined spatial health planning informed by research.

Controlled and driving mechanism of the SPM variation of shallow Brackish Lakes in arid regions.

Suspended particulate matter (SPM) in the brackish Ebinur Lake of arid northwest China profoundly affect its water quality and watershed habitat quality. However, the actual driving mechanisms of the Lake's SPM changes remain unclear. Therefore, the purpose of this study is to explore the controlling factors driving the variability of SPM in the Ebinur Lake. This study constructed month-by-month SPM maps of Ebinur Lake based on time-series remote-sensing imageries and SPM inversion model. Thirty-four factors that might influence SPM changes were extracted, and the Partial Least Squares Structural Equation Modeling (PLS-SEM), suitable for complex relationships and factor interactions, was applied to identify the relative influence of each factor quantitatively. The results showed: (1) a clear increasing trend of SPM concentration in Ebinur Lake from 2011 to 2020; (2) that SPM changes were influenced by external and internal factors, explaining 48.2 % and 46.9 % of the changes, respectively; (3) that, to the external factors, meteorological factors exerted the greatest influence on SPM (relative contribution of 38.9 %); that, to the internal factors, water salinity imposed the greatest influence on SPM (relative contribution of 43.3 %); (4) that, among the meteorological factors, the measured variable Alashankou wind speed expressed the most significant positive effect on SPM (weighting coefficient of 0.894), and sulfate generated the strongest positive effect on SPM (weighting coefficient of 0.791) among the water salinity factors. Hence, the quantitative identification of drivers of SPM changes in Ebinur Lake could provide a new perspective to investigate the driving mechanisms of lake water quality in arid areas and inform their sustainable restoration and management.

Research on Risk and Resilience Evaluation of Urban Underground Public Space.

High urban density, land scarcity, rapid population growth, and traffic congestion have restricted urban development. In response, selected multiple functions have increasingly been integrated into the underground public space (UPS) to maximize the 3D utilization of precious urban space. The accelerated intensity of UPS use has alerted safety concerns. UPS with enclosed and confined natures, complex building structures, locations usually in cramped areas, and limited emergency exits are potentially more prone to heavy casualties and losses in natural or human-made disasters. As research on UPS safety is limited and focused on single risks, we attempted to fill the knowledge gap by developing an integrated risk analysis of UPS to understand risk resilience and improve risk management. From the perspective of the UPS system, four latent factors were identified: natural environment, economic environment, facilities and equipment, and physical structure. Seventeen resilience indicators subsumed under the factors were selected based on resilience concepts. A questionnaire was designed to gather opinions on the relative importance rating of the resilience indicators. SPSS and AMOS software were enlisted to build a structural equation model (SEM), validate the data and model, and calculate the path coefficients and index weights to test four hypotheses. The SEM model results were employed to develop a holistic resilience enhancement strategy under a four-phase framework: before, during, after, and long-term, and under four latent factors. The resilience enhancements can optimize UPS disaster prevention, rescue and evacuation, mitigation, and response management.

Effects of climate-change scenarios on the distribution patterns of Castanea henryi.

Castanea henryi, with edible nuts and timber value, is a key tree species playing essential roles in China's subtropical forest ecosystems. However, natural and human perturbations have nearly depleted its wild populations. The study identified the dominant environmental variables enabling and limiting its distribution and predicted its suitable habitats and distribution. The 212 occurrence records covering the whole distribution range of C. henryi in China and nine main bioclimatic variables were selected for detailed analysis. We applied the maximum entropy model (MaxEnt) and QGIS to predict potentially suitable habitats under the current and four future climate-change scenarios. The limiting factors for distribution were accessed by Jackknife, percent contribution, and permutation importance. We found that the current distribution areas were concentrated in the typical subtropical zone, mainly Central and South China provinces. The modeling results indicated temperature as the critical determinant of distribution patterns, including mean temperature of the coldest quarter, isothermality, and mean diurnal range. Winter low temperature imposed an effective constraint on its spread. Moisture served as a secondary factor in species distribution, involving precipitation seasonality and annual precipitation. Under future climate-change scenarios, excellent habitats would expand and shift northwards, whereas range contraction would occur on the southern edge. Extreme climate change could bring notable range shrinkage. This study provided a basis for protecting the species' germplasm resources. The findings could guide the management, cultivation, and conservation of C. henryi, assisted by a proposed three-domain operation framework: preservation areas, loss areas, and new areas, each to be implemented using tailor-made strategies.

Effects of Self-Rated Health Status on Residents' Social-Benefit Perceptions of Urban Green Space.

Urban green spaces (UGS) provide many social benefits and improves residents' wellbeing. Studying residents' perceptions of UGS's social benefits and driving factors could promote public health and environmental justice. A questionnaire survey of 432 Beijing residents and statistical tests assessed the impacts of residents' living environments and self-rated health status on UGS perceptions. The results showed: (1) perceptions of UGS' physical health benefits were subdued, with an inclination towards other social benefits. Respondents more highly perceived accelerating patient recovery and reducing morbidity and mortality rates. Perceptions of bearing larger-head babies with higher weight were relatively low. For other social benefits, perceptions of improving the environment and life quality were higher, but reducing anger outbursts and resolving conflicts were lower. (2) Childhood living environments did not affect perceptions of social benefits, but current living environments did. Suburb residents understood reducing pain-relief medication demands and bearing larger-head babies better than city residents. City residents understood UGS' investments considerable and sustained returns better than village residents. City residents agreed with accelerating patient recovery higher than village ones. (3) Respondents with "poor" self-rated health status had better perceptions of other social benefits. Those with "excellent" ratings did not fully understand UGS' physical health benefits. "Poor" ratings understood improving a city's image and making cities livable and sustainable better than "good" or "fair" ratings. "Excellent" ratings had less understanding of larger-head babies than "good" or "fair" ratings. The study could enhance appreciation of UGS' social benefits to facilitate planning and management to meet residents' expectations.

Landscape and vegetation traits of urban green space can predict local surface temperature.

Societal and technological advances have triggered demands to improve urban environmental quality. Urban green space (UGS) can provide effective cooling service and thermal comfort to alleviate warming impacts. We investigated the relative influence of a comprehensive spectrum of UGS landscape and vegetation factors on surface temperature in arid Urumqi city in northwest China. Built-up area range was extracted from Luojia 1-01 (LJ1-01) satellite data, and within this range, the landscape metric information and vegetation index information of UGS were obtained based on PlanetScope data, and a total of 439 sampling grids (1 km × 1 km) were generated. The urban surface temperature of built-up areas was extracted from Landsat8-TIRS images. The 12 landscape metrics and 14 vegetation indexes were assigned as independent variables, and surface temperature the dependent variable. Support Vector Machine (SVM), Gradient Boost Regression Tree (GBRT) and Random Forest (RF) were enlisted to establish numerical models to predict surface temperature. The results showed that: (1) It was feasible to predict local surface temperature using a combination of landscape metrics and vegetation indexes. Among the three models, RF demonstrated the best accuracy. (2) Collectively, all the factors play a role in the surface-temperature prediction. The most influential factor was Difference Vegetation Index (DVI), followed by Green Normalized Difference Vegetation Index (GNDVI), Class Area (CA) and AREA. This study developed remote sensing techniques to extract a basket of UGS factors to predict the surface temperature at local urban sites. The methods could be applied to other cities to evaluate the cooling impacts of green infrastructures. The findings could provide a scientific basis for ecological spatial planning of UGS to optimize cooling benefits in the arid region.

Positive relationships among aboveground biomass, tree species diversity, and urban greening management in tropical coastal city of Haikou.

Within urban green spaces, tree species diversity is believed to correlate with aboveground biomass, though there is some disagreement within the literature on the strength and directionality of the relationship. Therefore, we assessed the relationship between the biodiversity of woody species and the aboveground biomass of woody plant species in the tropical, coastal city of Haikou in southern China. To accomplish this, we obtained comprehensive tree and site data through field sampling of 190 urban functional units (UFUs, or work units) corresponding to six types of land uses governmental-institutional, industrial-commercial, park-recreational, residential, transport infrastructure, and undeveloped area. Based on our field data, we investigated the relationship between tree species diversity and aboveground biomass using multiple regression, which revealed significant relationships across all five types of land uses. Aboveground biomass in green spaces was also correlated with anthropogenic factors, especially time since urban development, or site age, annual maintenance frequency by human caretakers, and human population density. Among these factors, maintenance is the strongest predictor of aboveground biomass in urban green space. Therefore, this study highlights the critical role of maintenance of urban green space in promoting both aboveground biomass and woody biodiversity in urban ecosystems and, consequently, on urban ecosystem services. Our findings contribute to a deeper understanding of the ecosystem services provided by communities of woody plant species in urban areas.

Integrating solutions to adapt cities for climate change.

Record climate extremes are reducing urban liveability, compounding inequality, and threatening infrastructure. Adaptation measures that integrate technological, nature-based, and social solutions can provide multiple co-benefits to address complex socioecological issues in cities while increasing resilience to potential impacts. However, there remain many challenges to developing and implementing integrated solutions. In this Viewpoint, we consider the value of integrating across the three solution sets, the challenges and potential enablers for integrating solution sets, and present examples of challenges and adopted solutions in three cities with different urban contexts and climates (Freiburg, Germany; Durban, South Africa; and Singapore). We conclude with a discussion of research directions and provide a road map to identify the actions that enable successful implementation of integrated climate solutions. We highlight the need for more systematic research that targets enabling environments for integration; achieving integrated solutions in different contexts to avoid maladaptation; simultaneously improving liveability, sustainability, and equality; and replicating via transfer and scale-up of local solutions. Cities in systematically disadvantaged countries (sometimes referred to as the Global South) are central to future urban development and must be prioritised. Helping decision makers and communities understand the potential opportunities associated with integrated solutions for climate change will encourage urgent and deliberate strides towards adapting cities to the dynamic climate reality.