Identifying influencing factors and characterizing key issues in urban sustainable development capacity through machine learning

In response to the United Nations Sustainable Development Goals and China’s“Dual Carbon”Goals(DCGs means the goals of“Carbon Peak and carbon neutrality”),this paper from the perspective of the construction of China’s Innovation Demonstration Zones for Sustainable Development Agenda(IDZSDAs),combines carbon emission-related metrics to construct a comprehensive assessment system for Urban Sustainable Development Capacity(USDC).After obtaining USDC assessment results through the assessment system,an approach combining Least Absolute Shrinkage and Selection Operator(LASSO)regression and Random Forest(RF)based on machine learning is proposed for identifying influencing factors and characterizing key issues.Combining Coupling Coordination Degree(CCD)analysis,the study further summarizes the systemic patterns and future directions of urban sustainable development.A case study on the IDZSDAs from 2015 to 2022 reveals that:(1)the combined identification method based on machine learning and CCD models effectively quantifies influencing factors and key issues in the urban sustainable development process;(2)the correspondence between influencing factors and key subsystems identified by the LASSO-RF combination model is generally consistent with the development situations in various cities;and(3)the machine learning-based combined recognition method is scalable and dynamic.It enables decision-makers to accurately identify influencing factors and characterize key issues based on actual urban development needs.

Distributions of typical contaminant species in urban short-term storm runoff and their fates during rain events:A case of Xiamen City

The pollutants in urban storm runoff, which lead to an non-point source contamination of water environment around cities, are of great concems. The distributions of typical contaminants and the variations of their species in short term storm runoff from different land surfaces in Xiamen City were investigated. The concentrations of various contaminants, including organic matter, nutrients （i.e., N and P） and heavy metals, were significantly higher in parking lot and road runoff than those in roof and lawn runoff. The early runoff samples from traffic road and parking lot contained much high total nitrogen （TN 6-19 mg/L） and total phosphorus （TP 1-3 mg/L）. A large proportion （around 60%） of TN existed as total dissolved nitrogen （TDN） species in most runoff. The percentage of TDN and the percentage of total dissolved phosphorus remained relatively stable during the rain events and did not decrease as dramatically as TN and TP. In addition, only parking lot and road runoff were contaminated by heavy metals, and both Pb （25-120 μg/L） and Zn （0.1-1.2 mg/L） were major heavy metals contaminating both runoff. Soluble Pb and Zn were predominantly existed as labile complex species （50%-99%）, which may be adsorbed onto the surfaces of suspended particles and could be easily released out when pH decreased. This would have the great impact to the environment.

Multi-omics analysis reveals the genetic and environmental factors in shaping the gut resistome of a keystone rodent species

Understanding the emergence and spread of antibiotic resistance genes(ARGs)in wildlife is critical for the health of humans and animals from a“One Health”perspective.The gut microbiota serve as a reservoir for ARGs;however,it remains poorly understood how environmental and host genetic factors influence ARGs by affecting the gut microbiota.To elucidate this,we analyzed whole-genome resequencing data from 79 individuals of Brandt’s vole in two geographic locations with different antibiotics usage,together with metabolomic data and shotgun sequencing data.A high diversity of ARGs(851 subtypes)was observed in vole’s gut,with a large variation in ARG composition between individuals from Xilingol and Hulunbuir in China.The diversity and composition of ARGs were strongly correlated with variations in gut microbiota community structure.Genome-wide association studies revealed that 803 loci were significantly associated(P<5.05×10^(−9))with 31 bacterial species,and bipartite networks identified 906 bacterial species-ARGs associations.Structural equation modeling analysis showed that host genetic factors,air temperature,and presence of pollutants(Bisphenol A)significantly affected gut microbiota community structure,which eventually regulated the diversity of ARGs.The present study advances our understanding of the complex host-environment interactions that underlie the spread of ARGs in the natural environments.

A New Carbon and Oxygen Balance Model Based on Ecological Service of Urban Vegetation

The application of human induced oxygen consumption and carbon emission theory in urban region was summed up and on this base a new model of urban carbon and oxygen balance (UCOB) was constructed by calculating the carbon and oxygen fluxes. The purpose was to highlight the role of vegetation in urban ecosystems and evaluate the effects of various human activities on urban annual oxygen consumption and carbon emission. Hopefully,the model would be helpful in theory to keep the regional balance of carbon and oxygen,and provide guidance and support for urban vegetation planning in the future. To test the UCOB model,the Jimei District of Xiamen City,Fujian Province,China,a very typical urban region,was selected as a case study. The results turn out that Jimei′s vegetation service in oxygen emission and carbon sequestration could not meet the demand of the urban population,and more than 31.49 times of vegetation area should be added to meet the whole oxygen consumption in Jimei while 9.60 times of vegetation area are needed to meet the carbon sequestration targets. The results show that the new UCOB model is of a great potential to be applied to quantitative planning of urban vegetation and regional eco-compensation mechanisms.

Responses of Soil Bacterial Diversity to Fertilization are Driven by Local Environmental Context Across China

Soil microbial diversity is extremely vulnerable to fertilization,which is one of the main anthropogenic activities associated with global changes.Yet we know little about how and why soil microbial diversity responds to fertilization across contrasting local ecological contexts.This knowledge is fundamental for predicting changes in soil microbial diversity in response to ongoing global changes.We analyzed soils from ten 20-year field fertilization(organic and/or inorganic)experiments across China and found that the national-scale responses of soil bacterial diversity to fertilization are dependent on ecological context.In acidic soils from regions with high precipitation and soil fertility,inorganic fertilization can result in further acidification,resulting in negative impacts on soil bacterial diversity.In comparison,organic fer-tilization causes a smaller disturbance to soil bacterial diversity.Despite the overall role of environmental contexts in driving soil microbial diversity,a small group of bacterial taxa were found to respond to fer-tilization in a consistent way across contrasting regions throughout China.Taxa such as Nitrosospira and Nitrososphaera,which benefit from nitrogen fertilizer addition,as well as Chitinophagaceae,Bacilli,and phototrophic bacteria,which respond positively to organic fertilization,could be used as bioindicators for soil fertility in response to fertilization at the national scale.Overall,our work provides new insights into the importance of local environmental context in determining the responses of soil microbial diver-sity to fertilization,and identifies regions with acidic soils wherein soil microbial diversity is more vul-nerable to fertilization at the national scale.

Distributive Characteristics of Metallic Nano-particles in China's Urban Water Bodies and their Ecological Risks

Engineering nano-materials & their impact on human health or environmental security constitute a newly emerging R&D hot spot and a key problem now urgently waiting for its solution in supporting the sustainability of China's nano-science and related technology development. At present, water bodies in Chinese cities have been seriously polluted by metallic nano-particles (MNPs) while related monitoring data are found woefully lacking throughout the country. Based on the above understanding, this article gives a round-up explanation on distributive characteristics of MNPs in the river mouths or water bodies of Chinese cities, their ecological hazards as well as our research in this regard, providing some inspiring ideas and data for control over this scourge. In addition, our exploration probes the discharge traits of MNPs themselves and the mechanism underlying its impact on water pollution.

Assessment of Greenland surface melt algorithms based on DMSP and SMOS data

Satellite-borne microwave radiometers provide essential measurements to study the surface melt state of ice sheets. Therefore, selecting suitable microwave radiometer data is critical to characterize the spatial distribution of surface melt. In this study, we investigated the Greenland Ice Sheet and evaluated the usefulness, as climate indicators, of data acquired by microwave radiometers onboard the F17 satellite of the United States of America Defense Meteorological Satellite Program(DMSP) and the Soil Moisture and Ocean Salinity(SMOS) satellite of the European Space Agency. First, surface melt was simulated using the DMSP dataset as input for a brightness temperature threshold algorithm, the Microwave Emission Model of Layered Snowpacks(MEMLS2), and the SMOS dataset as input for the L-band Specific MEMLS(LS-MEMLS). For accuracy evaluation, the simulation results were then compared with surface melt estimates derived from air temperature measurements at Automatic Weather Stations and from ice surface temperature measurements from the Moderate Resolution Imaging Spectroradiometer(MODIS) satellite-borne instrument. Our results show that global(over Greenland) MEMLS2 simulation performance(overall accuracy 83%) was higher than that of LS-MEMLS(overall accuracy 78%). However, in southeastern Greenland, MEMLS2 omission error was markedly higher than that of LS-MEMLS, whereas LS-MEMLS could detect longer-lasting surface melt than MEMLS2. This analysis showed that DMSP-based surface melt simulations are more accurate than SMOS-based simulations, thereby providing a data selection reference for surface melt studies of the Greenland Ice Sheet.

Terrestrial invertebrate hosts of human pathogens in urban ecosystems

Terrestrial invertebrates in urban ecosystems are extremely species-rich,have many important roles in material flow and energy circulation,and are host to many human pathogens that pose threats to human health.These invertebrates are widely distributed in urban areas,including both out-and in-door environments.Consequently,humans are frequently in contact with them,which provides many opportunities for them to pose human health risks.However,comprehensive knowledge on human pathogen transfer via invertebrates is lacking,with research to date primarily focused on dipterans(e.g.,mosquitoes,flies).Here,we take a broad taxonomic approach and review terrestrial invertebrate hosts(incl.mosquitoes,flies,termites,cockroaches,mites,ticks,earthworms,collembola,fleas,snails,and beetles)of human pathogens,with a focus on transmission pathways.We also discuss how urbanization and global warming are likely to influence the communities of invertebrate hosts and have flow-on risks to human health.Finally,we identify current research gaps and provide perspectives on future directions.

A commentary review on the use of normalized diff erence vegetation index(NDVI)in the era of popular remote sensing

The Normalized Diff erence Vegetation Index(NDVI),one of the earliest remote sensing analytical products used to simplify the complexities of multi-spectral imagery,is now the most popular index used for vegetation assessment.This popularity and widespread use relate to how an NDVI can be calculated with any multispectral sensor with a visible and a near-IR band.Increasingly low costs and weights of multispectral sensors mean they can be mounted on satellite,aerial,and increasingly—Unmanned Aerial Systems(UAS).While studies have found that the NDVI is effective for expressing vegetation status andquantified vegetation attributes,its widespread use and popularity,especially in UAS applications,carry inherent risks of misuse with end users who received little to no remote sensing education.This article summarizes the progress of NDVI acquisition,highlights the areas of NDVI application,and addresses the critical problems and considerations in using NDVI.Detailed discussion mainly covers three aspects:atmospheric eff ect,saturation phenomenon,and sensor factors.The use of NDVI can be highly eff ective as long as its limitations and capabilities are understood.This consideration is particularly important to the UAS user community.

Spatial-temporal Characteristics of Land Subsidence Corresponding to Dynamic Groundwater Funnel in Beijing Municipality,China

Due to long-term over-exploitation of groundwater in Beijing Municipality, regional groundwater funnels have formed and land subsidence has been induced. By combining a groundwater monitoring network, GPS monitor- ing network data, radar satellite SAR data, GIS and other new technologies, a coupled process model based on the dy- namic variation of groundwater and the deformation response of land subsidence has been established. The dynamic variation of groundwater fimnels and the land subsidence response process were analyzed systematically in Beijing. Study results indicate that current groundwater funnel areas are distributed mainly in the southwest of Shunyi District, the northeast of Chaoyang District and the northwest of Tongzhou District, with an average decline rate of groundwa- ter level of 2.66 rn/yr and a maximum of 3.82 m/yr in the center of the funnels. Seasonal and interannual differences exist in the response model of land subsidence to groundwater funnels with uneven spatial and temporal distribution, where the maximum land subsidence rate was about --41.08 mm/yr and the area with a subsidence rate greater than 30 mm/yr was about 1637.29 km2. Although a consistency was revealed to exist between a groundwater funnel and the spatial distribution characteristics of the corresponding land subsidence funnel, this consistency was not perfect. The results showed that the response model of land subsidence to the dynamic variation of groundwater was more revealing when combining conventional technologies with InSAR, GIS, GPS, providing a new strategy for environmental and hydrogeological research and a scientific basis for regional land subsidence control.

Valuation of Lake and Marsh Wetlands Ecosystem Services in China

Wetlands are highly productive natural ecosystems, providing valuable goods and services. There is growing interest in transferring ecosystem service value from the existing wetlands studied to other wetlands ecosystems at a large geographic scale. The benefit transfer method uses the known values from wetlands to predict the value of other wetland sites. This methodology requires only limited time and resources. The present study calculated the value of the ecological services provided by lake and marsh wetlands in China in terms of biodiversity indices, water quality indices and economic indices. Basic data on wetlands were obtained through remote sensing images. The results show that: 1) The total ecosystem service value of the lake and marsh wetlands in 2008 was calculated to be 8.1841 × 1010 United States Dollars(USD), with the marsh and lake wetlands contributing 5.6329 × 1010 and 2.5512 × 1010 USD, respectively. Values of marsh ecosystem service were concentrated in Heilongjiang Province(2.5516 × 1010 USD), Qinghai Province(1.2014 × 1010 USD), and Inner Mongolia Autonomous Region(1.1884 × 1010 USD). The value of the lakes were concentrated in Tibet Autonomous Region(6.223 × 109 USD), Heilongjiang(5.810 × 109 USD), and Qinghai(5.500 × 109 USD). 2) Waste treatment and climate regulation services contributed to 26.29% and 24.74% respectively, of the total ecosystem service value of the marsh wetlands. Hydrological regulation and waste treatment contributed to 41.39% and 32.75%, respectively, of the total ecosystem service value of the lake wetlands. 3) The total ecological service value of the lake and marsh wetlands was 54.64% of the total service value of natural grassland ecosystems and 30.34% of the total service value of forests ecosystems in China.

Quantitative Simulation on Soil Moisture Contents of Two Typical Vegetation Communities in Sanjiang Plain,China

Different types of vegetation occupy different geomorphology and water gradient environments in the San- jiang Plain, indicating that the soil moisture dynamics and water balance patterns of the different vegetation communi- ties might differ from each other. In this paper, a lowland system, perpendicular to the Nongjiang River in the Honghe National Nature Reserve （HNNR）, was selected as the study area. The area was occupied by the non-wetland plant forest and the typical wetland plant meadow. The Microsoft Windows-based finite element analysis software package for simulating water, heat, and solute transport in variably saturated porous media （HYDRUS）, which can quantita- tively simulate water, heat, and/or solute movement in variably-saturated porous media, was used to simulate soil moisture dynamics in the root zone （20-40 cm） of those two plant communities during the growing season in 2005. The simulation results for soil moisture were in a good agreement with measured data, with the coefficient of determi- nation （R2） of 0.44-0.69 and root mean square error （RMSE） ranging between 0.0291 cm3/cm3 and 0.0457 cm3/cm3, and index of agreement （d） being from I）.612 to 0.968. During the study period, the volumetric soil moisture content of meadow increased with the depth and its coefficient of variation decreased with the depth （from 20 cm to 40 cm）, while under the forest the soil moisture content at different depths varied irregularly. The calculated result of water budget showed that the water budget deficit of the meadow was higher than that of the forest, suggesting that the meadow is more likely to suffer from water stress than the forest. The quantitative simulation by HYDRUS in this study did not take surface runoff and plant growth processes into account. Improved root water uptake and surface runoff models will be needed for higher accuracy in further researches.

Scale Issues of Wetland Classification and Mapping Using Remote Sensing Images: A Case of Honghe National Nature Reserve in Sanjiang Plain, Northeast China

Wetland research has become a hot spot linking multiple disciplines presently. Wetland classification and mapping is the basis for wetland research. It is difficult to generate wetland data sets using traditional methods because of the low accessibility of wetlands, hence remote sensing data have become one of the primary data sources in wetland research. This paper presents a case study conducted at the core area of Honghe National Nature Reserve in the Sanjiang Plain, Northeast China. In this study, three images generated by airship, from Thematic Mapper and from SPOT 5 were selected to produce wetland maps at three different wetland landscape levels. After assessing classification accuracies of the three maps, we compared the different wetland mapping results of 11 plant communities to the airship image, 6 plant ecotypes to the TM image and 9 landscape classifications to the SPOT 5 image. We discussed the different characteristics of the hierarchical ecosystem classifications based on the spatial scales of the different images. The results indicate that spatial scales of remote sensing data have an important link to the hierarchies of wetland plant ecosystems displayed on the wetland landscape maps. The richness of wetland landscape information derived from an image closely relates to its spatial resolution. This study can enrich the ecological classification methods and mapping techniques dealing with the spatial scales of different remote sensing images. With a better understanding of classification accuracies in mapping wetlands by using different scales of remote sensing data, we can make an appropriate approach for dealing with the scale issue of remote sensing images.

Seasonal comparison of bacterial communities in rhizosphere of alpine cushion plants in the Himalayan Hengduan Mountains

Positive associations between alpine cushion plants and other species have been extensively studied.However,almost all studies have focused on the associations between macrofauna.Studies that have investigated positive associations between alpine cushion plants and rhizospheric microbes have been limited to the vegetation growing season.Here,we asked whether the positive effects that alpine cushion plants confer on rhizospheric microbe communities vary with seasons.We assessed seasonal variations in the bacterial diversity and composition in rhizosphere of two alpine cushion plants and surrounding bare ground by employing a high throughput sequencing method targeting the V3 region of bacterial 16 S rRNA genes.Soil properties of the rhizosphere and the bare ground were also examined.We found that cushion rhizospheres harbored significantly more C,N,S,ammonia nitrogen,and soil moisture than the bare ground.Soil properties in cushion rhizospheres were not notably different,except for soil pH.Bacterial diversities within the same microhabitats did not vary significantly with seasons.We concluded that alpine cushion plants had positive effects on the rhizospheric bacterial communities,even though the strength of the effect varied in different cushion species.Cushion species and the soil sulfur content were probably the major factors driving the spatial distribution and structure of soil bacterial communities in the alpine communities dominated by cushion plants.

Monitoring Intra-annual Spatiotemporal Changes in Urban Heat Islands in 1449 Cities in China Based on Remote Sensing

This study aimed to accurately study the intra-annual spatiotemporal variation in the surface urban heat island intensities(SUHIIs) in 1449 cities in China.First, China was divided into five environmental regions.Then, the SUHIIs were accurately calculated based on the modified definitions of the city extents and their corresponding nearby rural areas.Finally, we explored the spatiotemporal variation of the mean, maximum, and minimum values, and ranges of SUHIIs from several aspects.The results showed that larger annual mean daytime SUHIIs occurred in hot-humid South China and cold-humid northeastern China, and the smallest occurred in arid and semiarid west China.The seasonal order of the SUHIIs was summer > spring > autumn > winter in all the temperate regions except west China.The SUHIIs were obviously larger during the rainy season than the dry season in the tropical region.Nevertheless, significant differences were not observed between the two seasons within the rainy or dry periods.During the daytime, the maximum SUHIIs mostly occurred in summer in each region, while the minimum occurred in winter.A few cold island phenomena existed during the nighttime.The maximum SUHIIs were generally significantly positively correlated with the minimum SUHIIs during the daytime, nighttime and all-day in all environmental regions throughout the year and the four seasons.Moreover, significant correlation scarcely existed between the daytime and nighttime ranges of the SUHIIs.In addition, the daytime SUHIIs were also insignificantly correlated with the nighttime SUHIIs in half of the cases.

Research on the effects of command-and-control and market-oriented policy tools on China's energy conservation and emissions reduction innovation

The impact of environmental regulation on technology innovation is a hot spot in current research where a large number of empirical studies are based on Porter Hypothesis(PH). However, there are still controversies in academia about the establishment of "weak" and "narrow" versions of PH. Based on the panel data of application for patent of energy conservation and emission reduction(ECER) technology of Chinese city scale during 2008-2014, comprehensive energy price, pollutant emission, etc., mixed regression model and systematic generalized method of moments method were adopted, respectively,to study the impact of market-oriented and command-and-control policy tool on China's ECER technology innovation. The results show that the environmental regulation hindered the technological innovation in the immediate phase; however, it turned out to be positive in the first-lag phase. Hence, the establishment of "weak" PH is time-bounded. The command-and-control policy tool played a more positive role in promoting technological innovation in the first-lag phase than market-oriented policy tool. Therefore, "narrow" PH is not tenable. The reason is that the main participants of China's ECER technology innovation are state-owned companies and public institutions. Regionally speaking, the impact which command-and-control policy tool has on technological innovation at sight was nonsignificant in the eastern, the central, and the western regions of China whilst market-oriented policy tool had a negative effect. And market-oriented policy tool in the central region had strongest negative effect, which would diminish in the eastern region and become weakest in the western region. This was related to regional energy consumption level and the market economic vitality.

Variations in the biomass of Eucalyptus plantations at a regional scale in Southern China

We quantified deviations in regional forest biomass from simple extrapolation of plot data by the biomass expansion factor method（BEF） versus estimates obtained from a local biomass model,based on large-scale empirical field inventory sampling data.The sources and relative contributions of deviations between the two models were analyzed by the boosted regression trees method.Relative to the local model,BEF overestimated accumulative biomass by 22.12%.The predominant sources of the total deviation （70.94%） were stand-structure variables.Stand age and diameter at breast height are the major factors.Compared with biotic variables,abiotic variables had a smaller overall contribution （29.06%）,with elevation and soil depth being the most important among the examined abiotic factors.Large deviations in regional forest biomass and carbon stock estimates are likely to be obtained with BEF relative to estimates based on local data.To minimize deviations,stand age and elevation should be included in regional forest-biomass estimation.

Correction to:Commentary review on the use of normalized difference vegetation index(NDVI)in the era of popular remote sensing

The article“A commentary review on the use of normalized difference vegetation index(NDVI)in the era of popular remote sensing”,written by Sha Huang·Lina Tang·Joseph P.Hupy·Yang Wang and Guofan Shao,was originally published electronically on the publisher’s internet portal on 31st May 2020 without open access.With the author(s)’decision to opt for Open Choice the copyright of the article changed on 25th July 2020 to©The Author(s)2020 and the article is forthwith distributed under a Creative Commons Attribution 4.0 International License(https://creativecommons.org/licenses/by/4.0/),which permits use,sharing,adaptation,distribution and reproduction in any medium or format,as long as you give appropriate credit to the original author(s)and the source,provide a link to the Creative Commons licence,and indicate if changes were made.

An ecosystem services zoning framework for the permafrost regions of China

The degradation of the permafrost regions, resulting from intensive anthropogenic activities and global warming, has led to the loss of ecosystem services and is threating human well-being. Nevertheless, the real ecosystem service values and their complete zoning system in the permafrost regions have received insufficient attention. Research gaps between the identification of permafrost-based ecosystem services and ecosystem management are seriously constraining the development of cryospheric science. Thus, an ecosystem service zoning framework that links ecosystem services with human welfares is proposed to solve the abovementioned challenges in the permafrost regions of China. The three tiered zoning framework for ecosystem services, consisting of zoning goals, principles, hierarchy, methodology, and nomenclature, is proposed for the permafrost regions of China. A combined method, i.e., GIS spatial tools, the location entropy analysis model, and ecosystem services assessment, was employed to distinguish ecosystem conditions, ecosystem service supply, and beneficiaries into these three-grade ecosystem service zones. Hierarchical and dynamic zoning could clarify protection priorities of ecosystems and ecosystem services in terms of regions, grades, and types. The framework could contribute to sustainable management of ecosystem services in the cryosphere.

Disentangling the factors that contribute to variation in forest biomass increments in the mid-subtropical forests of China

Mid-subtropical forests are the main vegetation type of global terrestrial biomes, and are critical for maintaining the global carbon balance. However, estimates of forest biomass increment in mid-subtropical forests remain highly uncertain. It is critically important to determine the relative importance of different biotic and abiotic factors between plants and soil, particularly with respect to their influence on plant regrowth. Consequently,it is necessary to quantitatively characterize the dynamicspatiotemporal distribution of forest carbon sinks at a regional scale. This study used a large, long-term dataset in a boosted regression tree（BRT） model to determine the major components that quantitatively control forest biomass increments in a mid-subtropical forested region（Wuyishan National Nature Reserve, China）. Long-term,stand-level data were used to derive the forest biomass increment, with the BRT model being applied to quantify the relative contributions of various biotic and abiotic variables to forest biomass increment. Our data show that total biomass（t） increased from 4.62 9 106 to 5.30 9 106 t between 1988 and 2010, and that the mean biomass increased from 80.19 ± 0.39 t ha-1（mean ± standard error） to 94.33 ± 0.41 t ha-1in the study region. The major factors that controlled biomass（in decreasing order of importance） were the stand, topography, and soil. Stand density was initially the most important stand factor, while elevation was the most important topographic factor. Soil factors were important for forest biomass increment but have a much weaker influence compared to the other two controlling factors. These results provide baseline information about the practical utility of spatial interpolationmethods for mapping forest biomass increments at regional scales.