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    Textual research on Xishuai grass
    Zhuqing HE, Binjie GE
    Journal of East China Normal University(Natural Science)    2023, 2023 (2): 155-160.   DOI: 10.3969/j.issn.1000-5641.2023.02.016
    Abstract325)   HTML9)    PDF (1942KB)(72)      

    Cricket fighting is a traditional Chinese game that has lasted for more than 1000 years. Before competitions, Xishuai grass (stimulant grass) is commonly used to hit a cricket’s head and antennae to prepare the insects for battle. In “Flora of China” and flora of Chinese provinces, Xishuai grass is referenced as the Chinese common name of Eleusine indica (L.) Gaertn. In “Flora of Beijing” and “Flora of Hebei”, Xishuai grass is referenced as the Chinese common name of the genus Eleusine. In this paper, however, we demonstrate that Xishuai grass should actually be Digitaria spp. Given the mistakes in the above flora references, this paper aims to clarify the correct classification for future reference.

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    A landscape simulation modeling method based on remote sensing images
    Zehua WANG, Yan GAO, Mingang CHEN
    Journal of East China Normal University(Natural Science)    2023, 2023 (2): 82-94.   DOI: 10.3969/j.issn.1000-5641.2023.02.010
    Abstract303)   HTML13)    PDF (4124KB)(109)      

    Traditional virtual terrain modeling commonly uses a procedural generation method based on manual design, which cannot be used for competent simulation modeling tasks that need to restore real environments, such as in military applications. In this paper, we proposed a landscape simulation modeling method based on remote sensing images. The core of our proposed method is a landscape blended texture generation network (LBTG-Net); this method uses a blended texture generator (BTG) to generate landscape blended textures with the supervision of a style discriminator (SD) and multi-stage classification loss. Then, we procedurally build the complete virtual environment based on the blended texture generated by LBTG-Net. Our method has two main features: (1) accurate land-cover classification ability of remote sensing image inputs; and (2) high quality landscape blended texture outputs to guarantee virtual landscape modeling quality. We used multispectral image data from the Sentinel-2 satellite as the experimental dataset. The experimental results showed that our method offered high performance under mainstream land-cover classification evaluating indicators and can accurately reproduce the environmental distribution of input remote sensing images while completing high-quality virtual terrain simulation modeling.

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    Disinfection effect of seven frequently used disinfectants on bacteriophage MS2
    Yu LI, Zhenming GE
    Journal of East China Normal University(Natural Science)    2023, 2023 (2): 161-167.   DOI: 10.3969/j.issn.1000-5641.2023.02.017
    Abstract288)   HTML13)    PDF (1485KB)(183)      

    In this study, the MS2 phages were used as an indicator microorganism to test the function of seven disinfectants with different components: hydrogen peroxide, ethanol, fermented lactic acid disinfectant, iodine disinfectant, quaternary ammonium disinfectant, chlorine-containing disinfectant, and peracetic acid disinfectant. Our results showed that the virus disinfection rate varied notably between the selected disinfectants. The iodine disinfectant exhibited the strongest disinfection effect, followed by the quaternary ammonium salt disinfectant and the peracetic acid disinfectant, while the disinfection effects of hydrogen peroxide, ethanol, and fermentation lactic acid disinfectant were inadequate. The test results provide a reference for the efficient utilization of various disinfectants to eliminate harmful microorganisms in the environment.

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    Time series database query optimization for anomaly detection
    Shuai ZHANG, Huiqi HU, Yaoqiang XU, Xuan ZHOU
    Journal of East China Normal University(Natural Science)    2023, 2023 (2): 119-131.   DOI: 10.3969/j.issn.1000-5641.2023.02.013
    Abstract283)   HTML15)    PDF (2279KB)(130)      

    With the development of the Internet of Things, a large number of sensor devices can be connected to a network. Anomaly detection of data generated by these devices is related to the stability of system services. A time series database is a database system optimized for time series data. As an important component of a monitoring system, time series databases are responsible for storing and querying continuous streams of time series data. The current time series database, however, cannot fully utilize system computing resources and cannot meet the latency requirements when coping with queries from multiple data sources. To address these drawbacks, we redesigned the query execution model of a time series database based on the well-known InfluxDB, and we proposed InfluxDB-PP (parallel processing) as a method to address the aforementioned problems. The experimental results show that InfluxDB-PP reduces query latency by about 85.7% compared to InfluxDB for real-time anomaly data query scenarios.

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    Diversity of plants in Chinese Taoist temples and the distribution pattern of Taoist tree species
    Wei CHANG, Yongchuan YANG, Cheng JIN, Xinyang WANG, Li HUANG, Lihua ZHOU, Siwei HU
    Journal of East China Normal University(Natural Science)    2023, 2023 (3): 9-19.   DOI: 10.3969/j.issn.1000-5641.2023.03.002
    Abstract249)   HTML243)    PDF (1768KB)(103)      

    In this study, we obtained tree species from 72 Taoist temples across China. We subsequently documented the tree species composition, distribution pattern, and impact factors in different regions to determine the role of Taoist temples in biodiversity protection. The results showed that: ① Among 72 Taoist temples sampled across China, we observed a total of 354 species of trees, belonging to 85 families and 208 genera; ② The tree species in the Taoist temples were mainly native species, and the mean value for the proportion of native species in each Taoist temple was 62.5%±19.8% (mean ± standard deviation). Most of the Taoist temples (77.8%), moreover, housed threatened tree species; ③ Taoist tree species originated largely from subtropical regions, with the Yangtze River Basin being the most represented, especially in the southwest and south-central regions where a relatively large proportion of ethnic minorities reside; ④ The main factors affecting the distribution of Taoist tree species were geography and climate, but their composition was indistinguishable within each climate zone. As the climatic zone moves northward, there is no religious tree species replacement phenomenon (i.e., replacing the original religious tree species by native tree species with similar morphology or cultural meaning). The above results indicate that Taoist temples are rich in plant resources, which are potential biodiversity treasures. Thus, they play an essential role in protecting and maintaining biodiversity, with the potential to serve as a reference for regional ecological restoration and urban green space construction.

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    Automatic generation of Web front-end code based on UI images
    Jin GE, Xuesong LU
    Journal of East China Normal University(Natural Science)    2023, 2023 (5): 100-109.   DOI: 10.3969/j.issn.1000-5641.2023.05.009
    Abstract237)   HTML12)    PDF (1748KB)(66)      

    User interfaces (UIs) play a vital role in the interactions between an application and its users. The current popularity of mobile Internet has led to the large-scale migration of web-based applications from desktop to mobile. Web front-end development has become more extensive and in-depth in application development. Traditional web front-end development relies on designers to give initial design drafts and then programmers to write the corresponding UI code. This method has high industry barriers and slow development, which are not conducive to rapid product iteration. The development of deep learning makes it possible to automatically generate web front-end code based on UI images. Existing methods poorly capture the features of UI images, and the accuracy of the generated code is low. To mitigate these problems, we propose an encoder–decoder model, called image2code, based on the Swin Transformer, which is used to generate web front-end code from UI images. Image2code regards the process of generating web front-end code from UI images as an image captioning task and uses Swin Transformer with a sliding window design as the backbone network of the encoder and decoder. The sliding window operation limits the attention calculation to one window, which reduces the amount of calculation by the attention mechanism while simultaneously ensuring that feature connections remain across windows. In addition, image2code generates Emmet code, which is much simpler and can be directly converted to HTML code, improving the efficiency of model training. Experimental results show that image2code performs better than existing representative models, such as pix2code and image2emmet, in the task of web front-end code generation on existing and newly constructed datasets.

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    Research on travel time prediction based on neural network
    Zhaoyang WU, Jiali MAO
    Journal of East China Normal University(Natural Science)    2023, 2023 (2): 106-118.   DOI: 10.3969/j.issn.1000-5641.2023.02.012
    Abstract235)   HTML8)    PDF (1993KB)(154)      

    The popularity of positioning devices has generated a large volume of vehicle driving data, making it possible to use historical data to predict the driving time of vehicles. Vehicle driving data consists of two parts: the sequence of road segments that the vehicle travels through, the departure time, the total length of the path, and other external information. The questions of how to extract sequence features in road segments and how to effectively fuse sequence features with external features become the key issues in predicting the travel time. To solve the aforementioned problems, a transformer-based travel time prediction model is proposed, which consists of two parts: a road segment sequence processing module and a feature fusion module. First, the road segment sequence processing module uses the self-attention mechanism to process the road segment sequence and extract the road segment sequence features. The model can not only fully consider the spatiotemporal correlation of road speeds between each road segment and other road segments, but also ensures the parallel input of data into the model, avoiding the low efficiency problem caused by sequential input of data when using recurrent neural networks. The feature fusion module fuses the road segment sequence features with external information, such as departure time, and obtains the predicted travel time. On this basis, the number of road segments connected by the intersection is determined by the upstream and downstream intersection features of the road segment, and the input model is combined with the road segment characteristics to further improve the prediction accuracy of the driving time. Comparative experiments with mainstream prediction methods on real data sets show that the model improves prediction accuracy and training speed, reflecting the effectiveness of the proposed method.

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    A scheme of vegetation classification system at city scale and its application in Shanghai
    Liangjun DA, Zhiwen GAO, Yongchuan YANG, Kun SONG, Xueyan GUO, Hong LIANG, Tiyuan XIA, Huafeng WANG, Ting ZHOU, Daigui ZHANG, Zhihui TIAN, Yuandong HU, Bo JIA
    Journal of East China Normal University(Natural Science)    2023, 2023 (3): 1-8.   DOI: 10.3969/j.issn.1000-5641.2023.03.001
    Abstract217)   HTML240)    PDF (574KB)(214)      

    The development of city-scale vegetation maps is helpful for vegetation management and conservation. Vegetation classification systems in China mainly consider natural vegetation and most classification systems operate at the national or provincial scale, making them unsuitable for city-scale classification. Until now, the lack of a classification system designed specifically for urban vegetation has limited the studies on urban vegetation. Based on the origin, disturbance, and function, our classification system divides urban vegetation into natural, secondary, and cultivated vegetations. Based on the function, cultivated vegetation is further divided into artificial forest land, landscape green land , and urban agricultural vegetations. Based on the Classification System of China’s Vegetation in 1980 and the three newly proposed preliminary guideline documents for classification of natural vegetation, we establish a new urban vegetation classification system. We applied the principles of this new urban system in Shanghai and other areas in China, to further refine the system and ensure it has both academic and practical values. This work provides the theoretical basis for compiling information about urban vegetation and provides technical support for the recognition, protection, construction, and management of urban vegetation.

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    A memory allocation strategy for learned index based on huge pages
    Jialin GUAN, Yan ZHU, Tingliang WU, Yan CHEN, Jingwei ZHANG
    Journal of East China Normal University(Natural Science)    2023, 2023 (2): 73-81.   DOI: 10.3969/j.issn.1000-5641.2023.02.009
    Abstract209)   HTML11)    PDF (1015KB)(64)      

    In the era of big data and with the continuous expansion of data, there are significant challenges with efficient access to data. Hence, designing an efficient index structure is of great significance. ALEX (updatable adaptive learned index) is a learned index that uses a machine learning model to replace the traditional B-tree index structure. Although it offers good time and space performance, it suffers from frequent page faults. In order to solve this problem and further improve the performance of ALEX, a memory pre-allocation strategy based on huge pages is proposed, on the basis of ALEX, that can help reduce the rate of memory page faults and improve the overall performance of ALEX. In the memory allocation phase, the pre-allocation strategy is adopted, and the memory free phase adopts a delayed release strategy. Experiments on the Longitudes dataset show that this strategy offers good performance.

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    Two-degree trees
    Pu QIAO, Xingzhi ZHAN
    Journal of East China Normal University(Natural Science)    2023, 2023 (2): 1-4.   DOI: 10.3969/j.issn.1000-5641.2023.02.001
    Abstract207)   HTML20)    PDF (427KB)(129)      

    A graph is called a two-degree graph if its vertices have only two distinct degrees. A two-degree tree of order at least three have two degrees, $ 1 $ and $ d $ for some $ d\geqslant 2; $ such a tree is called a $ (1,d) $ -tree. Given a positive integer $ n, $ we determine: (1) the possible values of $ d $ such that there exists a $ (1,d) $ -tree of order $ n; $ (2) the values of $ d $ such that there exists a unique $ (1,d) $ -tree of order $ n $ , and (3) the maximum diameter of two-degree trees of order $ n. $ The results provide a new example showing that the behavior of graphs may sometimes be determined by number theoretic properties.

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    Target-dependent event detection from news
    Tiantian ZHANG, Man LAN
    Journal of East China Normal University(Natural Science)    2023, 2023 (2): 60-72.   DOI: 10.3969/j.issn.1000-5641.2023.02.008
    Abstract187)   HTML14)    PDF (1822KB)(92)      

    In real-world scenarios, various events in the news are not only too nuanced and complex to distinguish, but also involve multiple entities. To address these problems, previous event-centric methods are designed to detect events first and then extract arguments, relying on imperfect performance for event trigger detection; this process, however, is unfit to deal with the sheer volume of news in the real world. Given that the performance of named entity recognition (NER) is satisfactory, we shift our perspective from an event-centric to a target-centric view. This paper proposes a new task: target-dependent event detection (TDED), which aims to extract target entities and detect their corresponding events. We also propose a semantic and syntactic aware approach to support thousands of target entity extractions first and subsequently the detection of dozens of event types; this approach can be applied to data from massive corporations. Experimental results on a real-world Chinese financial dataset demonstrated that our model outperformed previous methods, particularly in complex scenarios.

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    Fault location algorithm based on Kirchhoff ’s law and a Boolean equation
    Xiaoqiu LU, Yang CAI, Jiajun CHEN, Xi ZHOU, Xueming ZHOU, Yunzhe TANG, Dingjiang HUANG
    Journal of East China Normal University(Natural Science)    2023, 2023 (2): 143-154.   DOI: 10.3969/j.issn.1000-5641.2023.02.015
    Abstract182)   HTML8)    PDF (1422KB)(47)      

    With the continuous development of China’s electric power system, the security and reliability of power supply directly affects regional production output and people’s economic life. As an important part of the power dispatch system, traditional fault locations rely on the cumulative experience and manual judgment of dispatchers. Faced with increasing demands, fault locations that rely solely on the traditional method are likely to result in an increase in misjudgment rates and pose a threat to the stable operation of the power system. This paper proposes a Boolean equation based on Kirchhoff’s law and the grid fault location algorithm to address this challenge. The fault location issue can effectively be converted to Boolean linear mixed programming problems and combined with simulated annealing algorithms. When these genetic algorithms are applied to the idea of a network and realized in the grid for fast positioning of small faults, the scheduling error rate can be reduced and the time difference from fault occurrence to fault isolation and fault processing can be shortened; in turn, this saves human resources and improves scheduling efficiency.

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    Device component state recognition method of power distribution cabinet based on a residual networks
    Yang ZHANG, Yejing LAI, Dingjiang HUANG
    Journal of East China Normal University(Natural Science)    2023, 2023 (2): 132-142.   DOI: 10.3969/j.issn.1000-5641.2023.02.014
    Abstract166)   HTML11)    PDF (970KB)(64)      

    With the continuous development of industrial intelligent inspection technology, the equipment element state recognition system based on digital image processing is widely used. In order to improve the accuracy of power distribution cabinet(PDC) equipment element state recognition in a distribution room, a ResNet(residual networks)-based equipment element state recognition method is proposed. Firstly, the data acquisition system is set up and the data set is constructed. Then, for the PDC image, the preset device component target area is cropped to generate the device component image. For device component images, a ResNet-based component state recognition model was constructed and trained, and the trained model was used to identify component states. Taking the data set for power distribution cabinet equipment element in substation distribution rooms as the research object, a network of single prediction heads is adopted as the component with complex features, and the network of multiple prediction heads is adopted as the component with simple features. Then, the compact and pruning model compression method is used to reduce the number of parameters and the calculation amount under the condition of less accuracy loss. Finally, the architecture design of the inspection system is introduced. A JetSon Nano edge terminal is used as the running hardware of the algorithm module to reduce the communication cost.

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    Surface-modified aluminum used for hydrogen generation and aqueous contaminant removal
    Yang YANG, Zhenyan DENG, Xiaohan GUO, Genwang MA, Weizhuo GAI
    Journal of East China Normal University(Natural Science)    2023, 2023 (2): 168-182.   DOI: 10.3969/j.issn.1000-5641.2023.02.018
    Abstract165)   HTML13)    PDF (3313KB)(38)      

    Aluminum (Al) used for hydrogen generation and aqueous contaminant removal has been widely studied given its abundance and low redox potential; the reduction ability of Al, moreover, is restricted by the passive surface oxide film on Al particles. In addition to common Al surface treatment methods, such as acid/alkali washing, alloying, and mechanical ball-milling, Al surface modification technology arising in recent years has also been confirmed as an efficient Al activation method given its economical cost and benign manufacturing process. In this study, the merits and disadvantages of surface modification relative to other Al surface treatment methods were highlighted by reviewing existing research on the application of Al surface modification in hydrogen generation and aqueous contaminant removal. In addition, the paper presents an outlook on Al surface modification technology used for hydrogen generation and aqueous contaminant removal to promote the study of related processes.

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    Growth response of Heterosigma akashiwo to the changes of CO2 concentration, temperature and nutrient
    Anqiang YANG, Lixia ZHAO, Shuzhen SONG, Jie LIU, Yanlong HE, Yanna WANG
    Journal of East China Normal University(Natural Science)    2023, 2023 (3): 108-117.   DOI: 10.3969/j.issn.1000-5641.2023.03.011
    Abstract161)   HTML20)    PDF (1212KB)(59)      

    Heterosigma akashiwo is one of the species of harmful algal blooms (HABs) threatening marine ecosystems and the fishing industry across coastal waters worldwide. With increasing global levels of atmospheric CO2 and global warming, HABs have increased in prevalence, duration, and geographic span; this phenomenon has been further stressed by intensified anthropogenic influences, such as eutrophication. Through controlled experiments with different nutrients, CO2 concentrations, and temperatures, our study aimed to understand the response of H. akashiwo to different nutrients with changes in climate. In all simulated CO2 and temperature scenarios, both cell density and the specific growth rate of H. akashiwo in the low phosphorus groups were significantly lower than those in the high phosphorus groups. Furthermore, the maximum cell density and specific growth rate of H. akashiwo were significantly enhanced by increased CO2, while the specific growth rate was accelerated by the dual effect of increased CO2 levels and temperature. The growth response of H. akashiwo to CO2 and temperature was similar between different nutrient treatments. Taken together, the results indicate that phosphorus concentration could be the major factor controlling the growth of H. akashiwo, and the intensity and risk of H. akashiwo blooming in the future is increasing. Hence, controlling the increase of nutrients, particularly phosphate, could be a critical pathway to decrease the occurrence of H. akashiwo blooms. In summary, our case study provides scientific support for marine ecological management of HABs.

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    Fast establishment of a point cloud model for a lock pin based onhigh overlapping views
    Zhiwei JIN, Chang HUANG, Ruihong ZHU
    Journal of East China Normal University(Natural Science)    2023, 2023 (2): 95-105.   DOI: 10.3969/j.issn.1000-5641.2023.02.011
    Abstract161)   HTML8)    PDF (2472KB)(73)      

    In this paper, we propose a method for fast splicing of three-dimensional point clouds based on the lock pin model on a container terminal using high overlapping views. This experiment first uses an Azure Kinect depth camera to collect scene point clouds, and subsequently preprocesses the point cloud. The target point cloud is thus obtained. For lock pins with slightly different views, the sample consensus initial algorithm (SAC-IA) is used on the basis of the classic iterative closest point (ICP) algorithm to determine the overlapping position relationship of the two point clouds. In the overall splicing process, the relative size of the bounding box area projected by the lock pin in the z-direction of the camera is adopted to estimate the general shape of the lock pin; the relative size of the bounding box area is also used to select an appropriate number of point cloud views with high overlap in order to ensure the accuracy of registration and reduce processing time by comparing the difference between the area of adjacent views. The experimental results show that the proposed method has a lower relative registration error for the lock pin, and can quickly establish a workpiece model suitable for type matching.

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    Multimodal-based prediction model for acute kidney injury
    Wei DENG, Fang ZHOU
    Journal of East China Normal University(Natural Science)    2023, 2023 (4): 52-64.   DOI: 10.3969/j.issn.1000-5641.2023.04.006
    Abstract158)   HTML12)    PDF (1179KB)(173)      

    Acute kidney injury is a clinical disease with a high morbidity rate, and early identification of potential patients can facilitate medical interventions to reduce morbidity and mortality. In recent years, electronic health records have been widely used to predict an individual’s potential risk. Most of the existing acute kidney injury prediction models tackle the issue of sparsity and irregularity in the physiological variables data by aggregating data or imputing the missing value, but ignore the patient’s health status implied by the missing information. Moreover, they do not consider the characteristics of and correlation between the various modalities. To solve the above issues, we present a multi-modal disease prediction model for acute kidney injury. The proposed model considers a variety of modal data, including physiological variables, disease, and demographic data. A new mask and time span based long short term memory (LSTM) network is designed to learn the time span and missing information of individual Physiological variables, and furthermore, to capture their numerical changes and frequency changes. The multi-head self-attention mechanism is introduced to promote interaction learning of each modality representation. Experiments on the real-world application of acute kidney injury risk prediction and mortality risk prediction demonstrate the effectiveness and rationality of the proposed model.

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    Strongly Gorenstein weak flat modules
    Yanhui SONG, Ting GUO
    Journal of East China Normal University(Natural Science)    2023, 2023 (2): 12-16.   DOI: 10.3969/j.issn.1000-5641.2023.02.003
    Abstract157)   HTML10)    PDF (499KB)(92)      

    In this paper, we introduce the notion of strongly Gorenstein weak flat modules, and we subsequently provide homological characterizations of strongly Gorenstein weak flat modules. It is shown that a Gorenstein weak flat module is a summand of a strongly Gorenstein weak flat module.

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    Complete convergence of weighted sums for extended negatively dependent sequences under sublinear expectation
    Dandan FEI, Zongkui FU
    Journal of East China Normal University(Natural Science)    2023, 2023 (2): 17-25.   DOI: 10.3969/j.issn.1000-5641.2023.02.004
    Abstract154)   HTML10)    PDF (585KB)(80)      

    The complete convergence of sequences of random variables under sublinear expectation was studied. Using the properties of extended negatively dependent (ND) sequences, under the condition that the $ \lambda $ -order Choquet integrals of the random variable are finite, the complete convergence of the weighted sums for extended ND sequences under a sublinear expectation was proved. The results generalize and improve the results of independent sequences in the classical probability space.

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    Effects of coastal engineering and biological invasion on changes in the coastal pattern of Nanhui Dongtan, Shanghai
    Tingyu ZHANG, Lin YUAN, Chao ZHANG, Yang LI, Zhiyuan ZHAO, Yuxiao SHI, Liquan ZHANG, Jinghua GU
    Journal of East China Normal University(Natural Science)    2023, 2023 (3): 167-180.   DOI: 10.3969/j.issn.1000-5641.2023.03.016
    Abstract147)   HTML17)    PDF (2515KB)(68)      

    Under the dual influence of human activities and natural factors, the coastal zone patterns are prone to rapid changes which can directly or indirectly affect the structure, function, and sustainable development of the coastal ecosystem. Using the coastal zone of Nanhui Dongtan in Shanghai as a typical research area, we used remote sensing interpretation, sea chart digitization, and field investigation to analyze changes in spatial patterns and changes in coastal zones over the last 20 years (from 2000 to 2020). In addition, the effects of coastal engineering (including reclamation engineering and siltation promotion engineering) and S. alterniflora invasion on coastal pattern dynamics were analyzed. The results showed that: ① Since 2000, under the influence of coastal engineering and biological invasion, the land use types of Nanhui Dongtan coastal zone changed from a simple pattern dominated by coastal wetlands to a complex pattern which included multiple land use types (i.e. coastal wetlands, inland wetlands, constructed wetlands, farmland, and construction land). ② Coastal reclamation engineering decreased 11894.7 hm2 of coastal wetlands in the Nanhui Dongtan coastal zone from 2000 to 2005. The reclaimed coastal wetlands were transferred into land use types such as rice fields, ponds, and farmland due to human activities; the reclamation engineering promoted deposition of sediment in the estuary and tidal mudflat (above 0 m) and the intertidal salt marsh developed with increased rates of 320.5 hm2/a and 110.9 hm2/a, respectively; meanwhile, the siltation rate decreased to 286.8 hm2/a and 15.7 hm2/a, respectively, after 2015. After 10 years (2005—2015) of natural recovery, the area of coastal wetlands did not reach the levels seen before reclamation in Year 2000. ③ Two types of siltation promotion engineering—hard siltation promotion engineering and biological siltation promotion engineering—have both significantly promoted the rapid development of coastal wetlands in Nanhui Dongtan. Hard silting promotion engineering with propagation rates of 516.9 hm2/a in tidal mudflats (above 0 m) and 915.7 hm2/a in intertidal salt marshes, respectively, was 5.4 times and 13.9 times higher than rates observed in non-siltation areas; hence, the effects were more significant than biological siltation promotion engineering which only resulted in pattern changes in a limited area between the seawall and the wave dissipation dike by planting S. alterniflora. ④ After introducing S. alterniflora in Nanhui Dongtan, it became the most dominant plant in the Nanhui Dongtan salt marsh, accounting for 56% of the total area; this significantly changed the ecological structure and function of coastal wetlands in 2020. Coastal engineering and biological invasion have a great impact on coastal zone patterns. Although the coastal ecosystem showed a certain resilience to coastal human activities, changes in the wetland type, area, and function were difficult or impossible to recover at a great cost in the future. How to integrate the ecological functions of coastal wetlands and inland wetlands through the implementation of coastal zone restoration, ecological protection, and other measures to achieve the sustainable and healthy development of coastal zones is an important problem for future land and sea planning.

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