Jiangsu Province In Eastern China Research Articles

Assessing landscape fragmentation and ecological connectivity to support regional spatial planning: A case study of Jiangsu province, China

Urbanization in China has led to land-use changes resulting in landscape fragmentation, natural habitats loss and ecological connectivity decline. Aiming to support sustainable landscape planning, we proposed an integrated method for ecological structure assessment and optimization including morphological spatial pattern analysis (MSPA), minimal cumulative resistance (MCR) model and circuit theory to assess landscape fragmentation and ecological connectivity change at regional scale. A modified connectivity index is also proposed by employing the index of relative quality of ecological patches and corridors. We applied the combined methods to Jiangsu province in eastern China for multi-temporal landscape analysis and optimization. The results showed that the combined analysis revealed both fragmentation trend of ecological patches and ecological connectivity reduction with regard to all the species as a whole in the study area from 2000 to 2018. While, the trend has been slowed down to a certain extent lately, which is related to a series of ecological protection policies implemented in the study area, including ecological redlines policy, national park construction and returning marginal farmland into forest or grassland. Furthermore, suggestions for improving the ecological network in the study area were proposed. We proposed to improve the ecological network by fostering twenty-five potential ecological sources, maintaining twenty-five pinch points, restoring eleven dredging corridors and planning fifty-three stepping stones. Overall, we argue that the combined method can reveal both structural connectivity and functional connectivity, and the time series analysis can provide dynamics situation for better understanding and planning landscape process. It can also provide planners with a valuable strategic tool that advances the practical utility of landscape ecology techniques for spatial planning, and the combined application of the method helps to reduce some of the limitations of each individual method.

An Empirical Test of the Influence of Rural Leadership on the Willingness to Participate in Public Affairs from the Perspective of Leadership Identification

The participation of villagers in rural public affairs is vital for the sustainable development of rural communities and the improvement of villagers’ quality of life. Various factors, including individual characteristics, village environment, social forces, and national policies, influence villagers’ willingness to participate. However, empirical research on the determinants of villagers’ participation in public affairs often overlooks the role of grassroots leadership. To address this gap, this study proposes a theoretical model examining the relationship between transformational leadership and villagers’ willingness to participate in public affairs. Using a sample of 438 villagers from Jiangsu Province in eastern China, structural equation modeling and regression are employed to analyze the data. The findings indicate that moral modeling, leadership charm, and personalized care directly impact villagers’ willingness to participate in public affairs or indirectly influence it through leadership identification, which acts as a mediator. Furthermore, shared vision enhances the positive relationship between leadership identification and villagers’ awareness of public affairs participation. These findings provide valuable insights for village cadres seeking to promote active participation in public affairs among villagers. Specifically, gaining recognition through virtuous conduct, capabilities, and strong cadre–villager relationships serves as a foundation for influencing villagers’ willingness to participate in public affairs, while shared vision plays a strategic role in mobilizing villagers based on their identification with leaders.

Dynamical Analyses of a Supercell Tornado in Eastern China Based on a Real-Data Simulation

Tornadoes are extremely destructive natural disasters, and East China has become a high-incidence area for tornadoes in China in recent years. On 7 July 2013, an EF2-intensity tornado occurred in Gaoyou County, Jiangsu Province in eastern China, within a supercell storm near a Meiyu frontal system. To investigate the dynamical process of the tornado, a numerical simulation was performed using four one-way nested grids within the Advanced Regional Prediction System (ARPS). Data from a nearby operational S-band Doppler radar are assimilated using a 4D ensemble Kalman filter (4DEnKF) at 5 min intervals. Forecasts are run with a nested 50 m grid, capturing the tornado embedded within the supercell storm with a reasonable agreement with observations. The tornadogenesis processes within the simulation results are analyzed in detail, including the three-dimensional evolution of the tornado vortex. It is found that a cold surge within the rear flank downdraft region plays a key role in instigating tornadogenesis when the leading edge of the cold surge approaches a near-ground convergence center located underneath the main updraft, and the enhancement of the convergence center caused by the descending of the low-level mesocyclone is the direct cause of the rapid increase in tornado vorticity. Backward trajectories are calculated based on model output, and the origins of the parcels feeding the intensifying tornado vortex are identified. It is found that parcels from the mid-level of the rear flank downdraft region follow the cold surge, descending to the ground under the influence of the downdraft in the cold surge, and then entering the convergence center, merging into the core of the tornado and being lifted up. Vertical profiles of the mass and vorticity fluxes into the core of the tornado vortex are examined, and it is found that the near-ground airflow contributes significantly to the growth of the tornado vorticity, with the contribution increasing as it gets closer to the ground.

Effect of Public Space on Collective Action for Rural Waste Management and the Mediating Effects of Social Capital

Public spaces enhance social interactions and contacts, yet few scholars have linked public spaces to the governance of commons for rural waste management. We thus explore the direct and mediated effects of public spaces on collective action for rural waste management. The research was conducted in the Jiangsu Province of Eastern China by interviewing 290 farmers from 9 different counties. The individual dataset was collected from the measurement of public space, social capital and collective action for rural waste management. Public space characteristics include scale, entering frequency and accessibility. A structural equation modelling approach was employed to analyse the path and relationship of these variables. The results show that public space has a direct and positive effect on collective action for rural waste management, which could be attributed to the specific dimensions of scale, entering frequency and accessibility. We also find that social capital positively mediates the relationship between public spaces and collective action. This study highlighted the importance of public space use to rural environmental governance. Social capital is recommended to promote the collective action for rural waste management. The results contribute to the literature on public space research and imply that public space should be considered by policymakers to enhance environmental development and rural revitalisation.

Measuring green development level at a regional scale: framework, model, and application.

In this study, we propose and construct a novel model that measures regional green development level based on the "three-circle" conceptual framework for green development. Using Jiangsu Province in eastern China as a case study, the spatial-temporal characteristics and dynamics of the green development level from 2000 to 2020 were evaluated using a multi-source dataset at the grid-cell level. Our results show that (1) the analytical hierarchy process-based model proposed herein has higher reliability in terms of the development level measurement than principal component analysis and the entropy weight method. In addition, the average score of green development in the study area was approximately 0.53. Spatially, the green development level in the eastern coastal areas of the study area was found to be generally higher than in other regions, while that in southwestern regions is relatively low. In terms of sub-regions, the green development level scores of the study area have been ranked as follows: middle Jiangsu > southern Jiangsu > northern Jiangsu. (2) It was observed that the gravity center of the green development level can be divided into three stages during the study, with a whole had shifted to the north. (3) For most cities in Jiangsu, the green development level initially increased at first, then declined, and then increased again. (4) In the future, the green development level of Jiangsu Province should pay more attention to promoting regional coordinated development and relationships between society and the environment under rapid economic development.

Multilevel Analysis of the Nutritional and Health Status among Children and Adolescents in Eastern China.

We aimed to identify multiple nutritional health problems and the relevant factors among children and adolescents aged 7–17 years. This study was part of the China Nutrition and Health Surveillance of Children and Lactating Mothers in 2016–2017, conducted in Jiangsu Province in eastern China. After sampling, 3025 school-age children and adolescents were enrolled into this study. Demographic information collections and anthropometric measurements were conducted by trained local Center for Disease Control and Prevention (CDC) staff. Venous blood in the amount of 6 mL was drawn from each participant in the morning and used for testing biochemical and nutritional indicators. Multivariate logistic regression analysis and Poisson regression analysis were used for overnutrition- and undernutrition-related disorders to test relevant personal, parental, and household factors. The prevalence of wasting, overweight, and obesity was 5.5%, 14.8%, and 12.7%, respectively. Metabolic syndrome (MetS) was prevalent among 5.1% of participants. Among the study participants, 29.5% had hyperuricemia. The overall prevalence of high low-density lipoprotein (LDL) and high total cholesterol (TC) of all participants was 4.8% and 7.4%, respectively. 0.9% of the participants had vitamin A deficiency (VAD) and 14.6% had marginal vitamin A deficiency; 25.1% had vitamin D deficiency (VDD) and 54.5% had inadequate vitamin D levels. Anemia was present in 4.0% of all participants. The prevalence of zinc deficiency was 4.8%. Demographic characteristics, behavioral characteristics, parents’ characteristics, and family characteristics were associated with these multiple malnutrition disorders. The double burdens of malnutrition, which includes overnutrition- and undernutrition-related diseases, were prevalent among the school-age children and adolescents in Jiangsu Province in eastern China. There were various factors related to different nutritional problems. Thus, health education focusing on behavior intervention and nutrition education are necessary in containing nutritional problems among children.

Associations between Serum Vitamin A and Metabolic Risk Factors among Eastern Chinese Children and Adolescents.

Vitamin A, a fat-soluble essential vitamin, is implicated in a large range of physiological processes. Up to now, the associations between vitamin A and metabolic syndrome (MetS) or other metabolic risk factors are controversial in children and adolescents. Thus, we aimed to dig into the relationship of vitamin A with MetS and many other metabolic risk factors. This was a cross-sectional study derived from the China National Nutrition and Health Surveillance of Children and Lactating Mothers. A total of 3025 school-aged (7–17 years) children and adolescents were selected by applying multistage stratified cluster random sampling methods in the Jiangsu Province of eastern China. Through enquiry survey, anthropometric measurement and laboratory examination, relevant information and blood biochemical indexes of the participants were collected in this study. MetS was identified according to the modified criteria of the National Cholesterol Education Program–Adult Treatment Panel III (NCEP-ATP III). Multivariate logistic analysis and the generalized additive model (GAM) were used to analyze the relationship between vitamin A and various metabolic risk factors. The overweight, obesity and MetS prevalence of children and adolescents in this study was 14.0%, 11.9% and 5.1%, respectively. The risk of prevalent MetS, general obesity, high low-density lipoprotein (LDL), high total cholesterol (TC) and hyperuricemia increased with vitamin A in a dose-dependent way. Logistic regression analysis showed that serum vitamin A Z scores were positively associated with MetS and central obesity, elevated blood pressure (BP) and elevated triglyceride (TG). Sex stratification analysis showed that both in male and female participants, the risk of prevalent MetS, general obesity, high LDL, high TC and hyperuricemia still increased with vitamin A levels. MetS was at a high prevalence level in children and adolescents in Jiangsu that were 7–17 years old. Vitamin A was positively associated with obesity, MetS, dyslipidemia and hyperuricemia. More public health measures and new visions should focus on the effects of retinol on children and adolescents.

Diversity Assessment of an Endemic Carpinus oblongifolia (Betulaceae) Using Specific-Locus Amplified Fragment Sequencing and Implications for Conservation

Carpinus oblongifolia is an endemic species and the extant wild populations show a fragmentation distribution in the Baohua Mountain of Jiangsu Province in eastern China. Understanding of genetic diversity plays an important role in C. oblongifolia survival and sustainable development. The wild C. oblongifolia population was artificially divided into four subpopulations according to the microhabitats, and another two subpopulations were constructed by progeny seedlings cultivated with the mature seeds. Then, the leaf buds of 80 individuals from six subpopulations were sampled to develop single nucleotide polymorphisms (SNPs) using specific-locus amplified fragment sequencing (SLAF-seq). Based on these SNPs, we aimed to characterize the genetic diversity and population structure of C. oblongifolia and provide an illumination and reference for effective management of such a small endemic population. The level of genetic diversity was low at the species level, and the progeny subpopulations had a relatively higher genetic diversity than the wild subpopulations. This may be attributed to a high gene flow and an excess heterozygosity to reduce the threat of genetic drift-based hazards. Moreover, the progeny subpopulations had the ability to form new clusters and a great contribution to the genetic structure variation of C. oblongifolia. These results will assist with the development of conservation and management strategies, such as properly evacuating competitive trees to provide more chance for pollen and seed flow in situ conservation, and establishing sufficient seedling plantlets under laboratory conditions for reintroduction to enlarge the effective population size.

Linking food production and environmental outcomes: An application of a modified relative risk model to prioritize land-management practices

CONTEXTSustainable land-use systems require clear decision-making protocols across institutions and departments. However, food production and ecological conservation are often regarded as separate or even incompatible policy goals, resulting in sustainability challenges and unclear land-management practices. More recently, with the introduction of Sustainable Development Goals (SDGs), there has been growing interests in minimizing the possible trade-offs between the two policy goals through appropriate governance. OBJECTIVEThe objective of this study was to develop a systematic framework for assessing current land-management practices and specifying future priorities. METHODSThe systematic framework included three modules and considered agroecosystems covering each administrative unit as the research objects. In the risk assessment module, we modified traditional relative risk model (RRM) to assess the risk that current management practices may affect food production and non-provisioning ecosystem services in existing agroecosystems, respectively. The framework also included a module to identify potentially available cropland (PAC) based on a combination of agricultural suitability and environmental costs for future reclamation. Finally, priorities for future land-management practices were specified based on the trade-offs between cropland expansion, ecological restoration and productive restoration. Jiangsu Province in eastern China was taken as a case study to verify the applicability of our framework. RESULTS AND CONCLUSIONSUsing Jiangsu Province as a case study, we have verified the applicability of our framework in prioritizing future land-management practices at a county level. The framework can offer a prioritization mechanism for formulating targeted strategies under alternative scenarios to correspond with varying management goals. The RRM can separate adverse effects from multiple stressors on food production and environmental outcomes rather than confounding the two interactive functions, while the risk scores and ranks generated for each sub-region, stressor and endpoint can pave the way for detailed and targeted governances. In addition, the identification of PAC can highlight areas for future cropland expansion. SIGNIFICANCEThe proposed framework can provide important insights and tools for avoiding institutional conflicts regarding land-management governance. Due to the simplicity and comparability, it can not only be applicable to our particular site, but also be used for different locations or downscaled to a landscape level.

Social Network Structure as a Moderator of the Relationship between Psychological Capital and Job Satisfaction: Evidence from China

Although networking is reported to be a job search strategy in the literature, research on the interaction between social networking and other personal resources and its effect on job satisfaction is scarce. In the perspective of social networks, the present study explored whether the social network structure, which consists of network size and tie strength, moderates the relationship between psychological capital and job satisfaction. By using a two-wave longitudinal design, we collected the quantitative data (survey of 344 undergraduate students who were about to graduate soon) from 19 universities in Beijing city, Shandong Province, and Jiangsu Province in Eastern China. Factor analysis and hierarchical regression analysis were adopted to analyze the data of the survey. We found that psychological capital has a positive impact on job seekers’ job satisfaction. Furthermore, smaller networks and weaker ties in social networks both render the positive effect of psychological capital on job satisfaction even stronger.

An assessment of Planet satellite imagery for county-wide mapping of rice planting areas in Jiangsu Province, China with one-class classification approaches

ABSTRACT There is a growing demand of the spatial distribution of major crops at the field level in recent years for the precision management of farmlands in developing countries. However, most previous studies used low or medium resolution images (e.g. Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat) to map the planting areas of rice in various regions of China. As a new source of satellite imagery, the 3 m Planet satellite imagery with daily revisit frequency has rarely been used for mapping crop types. In particular, it is still unclear how well the Planet imagery would perform in mapping the rice planting areas in the Lower Reaches of the Yangtze River Plain of China where image acquisition is strongly limited by rainy and cloudy weather conditions. To overcome the spectral confusion between rice and non-rice vegetation types, this study proposed one-class classification approaches with Planet imagery from the early and late seasons of rice crops over three counties (Guanyun, Rugao and Wujiang) across Jiangsu Province in eastern China. Apart from the traditional use of mono-temporal imagery from the late season (Strategy I), we developed two strategies to make use of the bi-temporal imagery from the early and late seasons, with one being direct classification using stacked images (Strategy II) and the other being stepwise classification (Strategy III). All classifications were performed with the popular machine learning classifier one-class support vector machine (OCSVM) and evaluated from the aspects of classification accuracy and area estimation accuracy. The results showed Strategy I could achieve an overall classification accuracy of 83.02% and kappa coefficient (ƙ) of 0.65. The overall accuracy (OA) can be significantly improved by Strategy II (OA = 84.44% and ƙ = 0.69) and further by Strategy III (OA = 90.42% and ƙ = 0.81). In terms of area estimation, the estimates from Strategy III were consistent with the government reported statistical data with a relative error (RE) within 10% at the county level. At the town level, the correspondence between Planet-derived rice planting areas and the Landsat-8 derived reference data was significantly improved with Strategy III as compared to the other two for Guanyun and Wujiang. The stepwise classification approach (Strategy III) developed with Planet imagery has great values in monitoring rice paddies over the regions with fragmentized distribution of rice fields.

Characterization of Human Origin Salmonella Serovar 1,4,[5],12:i:- in Eastern China, 2014 to 2018.

The prevalence of Salmonella serovar 1,4,[5],12:i:- among diarrhea patients has increased considerably in many countries around the world, including China. However, the characterization of this serovar of human origin has been less reported from China. We characterized 76 isolates of Salmonella 1,4,[5],12:i:- gained from diarrhea patients from 2014 to 2018 in the Jiangsu Province of eastern China. These isolates fell into a single-sequence type (ST34) determined by multilocus sequence typing (MLST), and into 44 pulsed-field gel electrophoresis band patterns, with 1 pattern (JSSMM015) comprising 12 isolates (15.9%). By means of PCR-based assays, the seven prophage located virulence genes were detected in our Salmonella 1,4,[5],12:i:- isolates with a high rate of gipA, gtgB, sspH1, sspH2, sodC1, and gtgE (93.4-97.4%), and with a moderate rate of sopE (42.1%). In contrast, none of the five plasmid-borne virulence genes (spvC, pefA, mig5, rck, and srgA) was identified. We tested the isolates' susceptibility to 18 antibiotics of 9 categories using the VITEK 2 system. A high proportion (89.5%) of the isolates were multidrug resistant (MDR) strains with full resistance to cefazolin, cefotetan, amikacin, gentamycin, and tobramycin, followed by resistance to ampicillin (88.2%) and ampicillin/sulbactam (80.3%). The resistance to piperacillin/tazobactam, ceftazidime, cefepime, and levofloxacin was scarce (2.6-9.2%). Notably, an isolate from 2018 was resistant to carbapenems. blaTEM-1B and aac(6')-Ib-cr were the most common drug resistance genes presented in cephalosporin- and fluoroquinolone-resistant strains. All Salmonella 1,4,[5],12:i:- isolates were capable of forming biofilm, with 13.2% of them having strong ability. However, no association was indicated between the scale of biofilm formation ability and MDR. Our results indicate that the combination of these characteristics may together provide a selective and competitive advantage to those Salmonella 1,4,[5],12:i:- isolates, contributing to their increasing prevalence observed worldwide.

Regional Forecasting of Fine Particulate Matter Concentrations: A Novel Hybrid Model Based on Principal Component Regression and EOF

AbstractWhen many cities need quantitative forecasts of air quality to adjust industrial production plans and urbanization development, how to build an efficient forecast model remain a challenge. Methodology for quantitative prediction of air quality can no longer rely on single‐site observations, and thus approaches that require fewer input data and are more efficient and more reliable need to be explored. This paper proposes the principles and steps of a new model using the empirical orthogonal function (EOF) and principal component regression (PCR), which is a hybrid EOF‐PCR approach that decomposes the panel data of PM2.5 and predictors into spatial structures (EOFs) and time expansion coefficients (ECs) by EOF analysis, establishes the PCR of the ECs of PM2.5, and simulates the PM2.5 concentrations in each city by projecting the fitted ECs through EOFs. The very heart of the new model is the PCR modeling and projection. The results are presented for PM2.5 concentrations over Jiangsu Province in eastern China. The results show that this EOF‐PCR model, which is based on EC1s with a cumulative variance contribution rate above 90%, has an average prediction accuracy of 65%. The model performs best in spring and autumn, better in summer and worst in winter. Most predictors have a maximum lag of a week, and they are quite different among seasons. Considering the influence of the spatial distributions of predictors, rather than covariates at a single site, this model can reflect regional influences and effectively improve the simulation effect.

Numerical Simulation and the Underlying Mechanism of a Severe Hail‐Producing Convective System in East China

AbstractA severe convective system that produced egg‐sized hail in Jiangsu province in eastern China on April 28, 2015 was simulated using a cloud‐resolving Weather Research and Forecasting model with the spectral bin microphysics scheme. The simulation reproduced the two stages of the convective system: the linear convective system (LCS) and the bow echo system (BES) stages. During the LCS stage, the intensity of updrafts was slightly stronger than that in the BES stage, with abundant supercooled water above the −20°C layer, and graupel and hail mainly generated in this period. The microphysical budget analyses and size distribution characteristics of hail were studied within one cell that produced hail during the LCS. It was suggested that hail mainly formed through water‐graupel collision and increased in size by collecting liquid water. Hail particles with smaller diameter were located around the perimeter of the main updrafts, while larger ones were distributed at the left edge of the updrafts. Trajectories and size growth processes of hailstones within the chosen cell were calculated by a three‐dimensional hail growth model, and it was found that hail originated from the middle levels on the east side of the updrafts, and were transformed westward and downward to the lower levels. They continued to ascend along the left edge of the updrafts and experienced one or more up‐down recycles and fell down to the ground on the west side of the updrafts.

Anomalous Atmospheric Circulation Associated with the Extremely Persistent Dense Fog Events over Eastern China in the Late Autumn of 2018

Under a declining trend of fog days in China, the duration of fog events since the 1990s reached a significant peak in the late autumn of 2018 over Eastern China. The average anomalous fog days were 4.74 d in November 2018 over Jiangsu Province in Eastern China, with a 1.73 standard deviation departure from climatology. Those fogs can thus be identified as a significantly abnormal climatic event with long duration, strong intensity, and extensive coverage. Based on the daily evolutions and correlations of atmospheric parameters, the dense fogs are revealed to be well configured by favorable metrological conditions such as weak dynamic progress, strong inversion in the lower troposphere and saturated air near the surface. If not disturbed, the intensification or duration of these conditions will further promote and maintain the development of fogs. The anomalous atmospheric background associated with those favorable meteorological conditions is revealed by composing the standardized anomalies of circulation fields during the fog days. Over the fog areas, vortex activities or cold air invasion is effectively hampered and the atmosphere inclines to be stable, due to the anomalous circulation pattern composed of the broadened jet stream, weakened jet core over Eastern China, undermined East Asian trough, declined East Asian winter monsoon, and enhanced anomalous southerly flows that transport abnormal warm and wet air to Eastern China. The vapor supplement is intensified by both sustained anomalous northward wind at the lower troposphere and anomalous westward wind in the near-surface. Overall, the numbers of standardized anomalies of 1000–200-hPa height, temperature, wind, and moisture fields during these fog days all significantly depart from climatology for that locale and time of the season, further demonstrating that the persistent dense fogs over Eastern China in the late autumn of 2018 is an unusual weather event with extreme synoptic-scale departures from normal.

Does the Organ-Based N Dilution Curve Improve the Predictions of N Status in Winter Wheat?

Accurately summarizing Nitrogen (N) content as a prelude to optimal N fertilizer application is complicated during the vegetative growth period of all the crop species studied. The critical nitrogen (N) concentration (Nc) dilution curve is a stable diagnostic indicator, which performs plant critical N concentration trends as crop grows. This study developed efficient technologies for different organ-based (plant dry matters (PDM), leaf DM (LDM), stem DM (SDM), and leaf area index (LAI)) estimation of Nc curves to enrich the practical applications of precision N management strategies. Four winter wheat cultivars were planted with 10 different N treatments in Jiangsu province of eastern China. Results showed the SDM-based curve had a better performance than the PDM-based curve in N nutrition index (NNI) estimation, accumulated N deficit (AND) calculation, and N requirement (NR) determination. The regression coefficients ‘a’ and ‘b’ varied among the four critical N dilution models: Nc = 3.61 × LDM–0.19, R2 = 0.77; Nc = 2.50 × SDM–0.44, R2 = 0.89; Nc = 4.16 × PDM–0.41, R2 = 0.87; and Nc = 3.82 × LAI–0.36, R2 = 0.81. In later growth periods, the SDM-based curve was found to be a feasible indicator for calculating NNI, AND, and NR, relative to curves based on the other indicators. Meanwhile, the lower LAI-based curve coefficient variation values stated that leaf-related indicators were also a good choice for developing the N curve with high efficiency as compared to other biomass-based approaches. The SDM-based curve was the more reliable predictor of relative yield because of its low relative root mean square error in most of the growth stages. The curves developed in this study will provide diverse choices of indicators for establishing an integrated procedure of diagnosing wheat N status, and improving the accuracy and efficiency of wheat N fertilizer management.

Remarkably low genetic diversity and shallow population structure detected of the spiny eel (Sinobdella sinensis) in Eastern China.

The spiny eel (Sinobdella sinensis) is a small subtropical fish endemic to China, Vietnam, and Laos. It has disappeared in many rivers and lakes due to anthropogenic stressors. The aim of this study was to investigate the genetic diversity and population structure and to provide pertinent information of the evolutionary history and conservation of S. sinensis. Mitochondrial DNA (mtDNA) cytochrome c oxidase I (COI) sequences of 144 individuals from five lakes in the Jiangsu Province of Eastern China were sequenced. A total of 17 haplotypes were defined by 20 variable nucleotide sites. Remarkably low haplotype and nucleotide diversity was observed in all sampled populations. The AMOVA analyses revealed that 96.44% of the genetic variation occurred within the populations. Significant genetic differentiation was detected among populations (P < 0.05), but no large-scale regional differences were detected. Analysis of neutral evolution and mismatch distribution suggests population expansion. Low genetic diversity and shallow population structure based on COI sequences were also confirmed. The wild resource of S. sinensis in Eastern China has sharply declined. Low genetic diversity and shallow population structure based on COI sequences were confirmed. Fishing management and resource conservation of this species should be taken urgently.

Dynamic optimization of input production factors for urban industrial water supply and demand management

To help minimize urban industrial water consumption and realize the goal of a water-saving society, this paper develops a method for the dynamic optimization of the input production factors in an urban industrial water supply model. A negative exponential curve describes the urban industrial water consumption per Yuan of urban industrial value added, the latter being described by a Gompertz curve. The product of the two describes the urban industrial water demand. The production function of urban industrial water supply is expressed by the fixed substitution proportional production function. Taking investment and labor input as control variables, the system goal is to balance of industrial water supply and demand. The time-varying model can not only solve the stable state problem for infinite time horizon, but also the transient problem for finite time horizon. Taking Jiangsu province in eastern China as an example, the applicability of the method was investigated under different parameter combinations. The simulation results show its effectiveness in these cases. In the earlier period, meeting balance requirements is easier using the straight-line capital depreciation method. In the later period, the fixed rate on declining balance method allows to meet the requirements more easily. In general, it is easier to achieve the goal by choosing a smaller and feasible weight matrix coefficient of the control variables.

Adaptability evaluation of ORYZA (v3) for single‐cropped rice under different establishment techniques in eastern China

AbstractThe ORYZA (v3) rice model is the most exhaustive representation of the available knowledge on rice (Oryza sativa L.) growth and development and has become an integrated rice modelling tool suitable for different scenarios according to the demands of users. A 3‐yr field experiment was conducted under potential production conditions for single‐cropped rice during 2011–2013 in Jiangsu Province in eastern China. The simulation performance of ORYZA (v3) with respect to the growth and development of different rice varieties under different establishment methods was evaluated and validated. The adaptability and stability of the model and its effect on the production of the same or similar rice varieties in different districts and years were verified using calibrated parameters. The results revealed that ORYZA (v3) performed well in simulating the dynamics of crop biomass and leaf area index for both calibration and validation datasets in 2011–2013, as is reflected by the high adjusted linear correlation coefficient (r2), low normalized root mean square error (NRMSE) value, and lack of notable differences between simulated and observed data with 99% confidence. The NRMSE value of the final yield ranged from 4.30 to 8.99% for both Indica and Japonica rice throughout the growing seasons. The performance of transplanted Indica rice varieties was better than that of most Japonica rice varieties. Overall, our evaluation suggested the suitability of ORYZA (v3) for simulating rice growth and development of different single‐cropped varieties under different establishment techniques in eastern China.

Combining habitat area and fragmentation change for ecological disturbance assessment in Jiangsu Province, China.

Understanding where and how human land use causes ecological consequences is essential for habitat conservation. However, the assessment of the ecological disturbance caused by human land use is usually shaped by the area change in ecological land. The comprehensive evaluation of ecological disturbance based on the losses and gains of ecological patches is neglected. This paper analyzed the land use change between agricultural land, construction land, and ecological land from 1995 to 2015 in Jiangsu Province of eastern China. The ecological disturbance was quantificationally evaluated by a proposed index that considered both the changes of habitat area and fragmentation caused by the losses and gains of ecological landscape patches. The findings showed that there was a slight increase in area of ecological land in Jiangsu Province; however, ecological fragmentation was becoming severe with the growth of human land use, which, in turn, resulted in increased ecological disturbance. The losses and gains in the area and fragmentation of ecological land were comprehensively reflected using the proposed ecological disturbance index. Negative ecological disturbance was more likely to be observed at the edge of the city centers, ecologically sensitive areas, and counties with low area ratios of ecological land. Ecological governance policies should be formulated and implemented based on quantity, quality, and spatial relationships between human land use and ecological disturbance.