Evolutionary Structure Research Articles

Evolutionary trend and network structure characteristics of publicity information dissemination about waste separation by different opinion leaders

Opinion leaders play significant roles in encouraging waste separation behaviors and increasing individual knowledge about environmental protection. To encourage waste reduction at its source, it is critical to determine the dissemination law and the structure characteristics of opinion leaders when they discuss waste separation information. This study explored the dynamic evolution law of information dissemination by official and celebrity opinion leaders. The results showed that the information released by celebrities showed a higher level of dissemination. The key forwarding nodes appeared in the transmission chain of highly influential celebrities, boosting the transmission depth of information. Official opinion leaders can use weak relationships to spread information to different groups, expanding the spread of information. Besides, the audience distribution pattern for official opinion leaders was highly coincident with the Hu Line and that the audience response degree achieved by celebrities showed a decreasing trend from the southeast coast to northwest inland.

Identification and analysis of isoflavone reductase gene family in Gossypium hirsutum L.

Isoflavone reductase (IFR) is a key enzyme controlling isoflavone synthesis and widely involved in response to various stresses. In this study, the IFR genes in four Gossypium species and other 7 species were identified and analyzed in the whole genome, and the physicochemical properties, gene structures, cis-acting elements, chromosomal locations, collinearity relationships and expression patterns of IFR genes were systematically analyzed. 28, 28, 14 and 15 IFR genes were identified in Gossypium hirsutum, Gossypium barbadense, Gossypium arboreum and Gossypium raimondii, respectively, which were divided into five clades according to the evolutionary tree and gene structure. Collinear analysis showed that segmental duplication and whole genome duplication were the main driving forces in the process of evolution, and most genes underwent pure selection. Gene structure analysis showed that IFR gene family was relatively conserved. Cis-element analysis of promoter showed that most GhIFR genes contain cis-elements related to abiotic stresses and plant hormones. Analysis of GhIFR gene expression under different stresses showed that GhIFR genes were involved in the response to drought, salt, heat and cold stresses through corresponding network mechanisms, especially GhIFR9A. Phenotypic analysis after silencing GhIFR9A gene by VIGS was shown that GhIFR9A gene was involved in the response to salt stress. This study laid a foundation for the subsequent functional study of cotton IFR genes.

Topology Optimization Based on SA-BESO

Bidirectional asymptotic structure methods have long been used to solve topological optimization problems, but are prone to being stuck in local optimal solutions. To solve this problem, this paper proposed a topology optimization method based on the Bi-directional Evolutionary structure Structural Optimization and Simulated Annealing algorithm (SA-BESO). First, the structural elements of the structural partition are encoded by a dual encoding, where elements are assigned with density values and binary strings. Second, binary strings are crossed and mutated, while criteria for adding and removing structural units are formulated. Then, structures are updated randomly. Finally, the structural compliance of the current structure is evaluated. If the structural compliance of the original structure increases, it will be accepted with a certain probability, thus jumping out of the local optimal solution. Related examples show that the SA-BESO method improves the smoothness of the optimization process and can obtain optimized structures with lower structural compliance and computational cost.

The role of dominant prairie species ecotypes on plant diversity patterns of restored grasslands across a rainfall gradient in the US Great Plains

AbstractQuestionsA robust ecosystem requires a functionally heterogeneous community of organisms with ecological traits that permit broad resource partitioning. Understanding community diversity patterns can help investigate drivers of community assembly and assess restoration success. Do biodiversity patterns differ among grassland communities sown with different ecotypes of dominant species during restoration along a rainfall gradient in the tallgrass prairie of the central US Great Plains?LocationFour field sites across a rainfall gradient within the North American Great Plains: Colby, Kansas (39°23′17.8″N, 101°04′57.4″W), Hays, Kansas (38°51′13.2″N, 99°19′08.6″W), Manhattan, Kansas (39°08′22.3″N, 96°38′23.3″W), and Carbondale, Illinois (IL, 37°41′47.0″N, 89°14′19.2″W).MethodsWe applied linear mixed models to assess the effect of dominant species ecotype, year, and location on grassland taxonomic, phylogenetic, and functional diversity.ResultsThe non‐local grass ecotype (compared to the local ecotype) promoted species richness. In contrast, the effect of the dominant species ecotype on phylogenetic or functional diversity was site‐specific over the 10‐year restoration. Richness decreased across the rainfall gradient from dry to moist sites, and the wettest site had the highest phylogenetic and functional diversity.ConclusionsOur results suggest that abiotic filtering by rainfall is a key assembly mechanism that could predict grassland changes in biodiversity in the early restoration phases. Given the community response across the tallgrass prairie, restoration practitioners should consider the impact of regional sources of dominant species used in restoration when biodiversity is a restoration goal. It is recommended for future grassland restoration to detect gaps and limitations in evolutionary and trait structure that will reveal which diversity components to evaluate.

Evaluation of the evolutionary genetics and population structure of Culex pipiens pallens in Shandong province, China based on knockdown resistance (kdr) mutations and the mtDNA-COI gene

BackgroundMosquitoes are important vectors for a range of diseases, contributing to high rates of morbidity and mortality in the human population. Culex pipiens pallens is dominant species of Culex mosquito in northern China and a major vector for both West Nile virus and Bancroftian filariasis. Insecticide application were largely applied to control the mosquito-mediated spread of these diseases, contributing to increasing rates of resistance in the mosquito population. The voltage-gated sodium channel (Vgsc) gene is the target site of pyrethroids, and mutations in this gene cause knockdown resistance (kdr). While these kdr mutations are known to be critical to pyrethroid resistance, their evolutionary origins remain poorly understood. Clarifying the origins of these mutations is potential to guide further vector control and disease prevention efforts. Accordingly, the present study was designed to study the evolutionary genetics of kdr mutations and their association with the population structure of Cx. p. pallens in Shandong province, China.MethodsAdult Culex females were collected from Shandong province and subjected to morphological identification under a dissection microscope. Genomic DNA were extracted from the collected mosquitoes, the Vgsc gene were amplified via PCR and sequenced to assess kdr allele frequencies, intron polymorphisms, and kdr codon evolution. In addition, population genetic diversity and related population characteristics were assessed by amplifying and sequencing the mitochondrial cytochrome C oxidase I (COI) gene.ResultsTotally, 263 Cx. p. pallens specimens were used for DNA barcoding and sequencing analyses to assess kdr allele frequencies in nine Culex populations. The kdr codon L1014 in the Vgsc gene identified two non-synonymous mutations (L1014F and L1014S) in the analyzed population. These mutations were present in the eastern hilly area and west plain region of Shandong Province. However, only L1014F mutation was detected in the southern mountainous area and Dongying city of Shandong Province, where the mutation frequency was low. Compared to other cities, population in Qingdao revealed significant genetic differentiation. Spatial kdr mutation patterns are likely attributable to some combination of prolonged insecticide-mediated selection coupled with the genetic isolation of these mosquito populations.ConclusionsThese data suggest that multiple kdr alleles associated with insecticide resistance are present within the Cx. p. pallens populations of Shandong Province, China. The geographical distributions of kdr mutations in this province are likely that the result of prolonged and extensive insecticide application in agricultural contexts together with frequent mosquito population migrations. In contrast, the low-frequency kdr mutation detected in central Shandong Province populations may originate from the limited selection pressure in this area and the relative genetic isolation. Overall, the study compares the genetic patterns revealed by a functional gene with a neutral marker and demonstrates the combined impact of demographic and selection factors on population structure.

CaB2O2F4: A Novel [BOF2]∞-Based Structural Template with a Strong Second Harmonic Generation Response and Large Band Gap

Nonlinear optical (NLO) materials are significant for their crucial role in the development of modern optoelectronic and laser technology. Recently, fluorooxoborates have aroused the widespread attention for their tight relationship between the micro-properties of functional [BOxF4–x](x+1)– (x = 0, 1, 2, and 3) modules and macroscopic performances. Nevertheless, whether fluorooxoborates with the anionic groups only composed of condensed [BO2F2] units exhibit a strong second harmonic generation (SHG) response remains unclear. Here, eight possible synthetic structures with the [BOF2]∞ chain in the CaB2O2F4 system were predicted by using evolutionary algorithm crystal structure prediction techniques. Among them, CaB2O2F4-I, II, IV, and V are centrosymmetric and CaB2O2F4-III, VI, VII, and VIII are non-centrosymmetric structures. Hence, CaB2O2F4-VI (C2) possesses an extremely short ultraviolet cutoff edge (147 nm) and the largest SHG coefficient among reported non-centrosymmetric fluorooxoborates only consisting of the [BO2F2] group. Also, the origin of the SHG coefficient was analyzed in detail through theoretical calculation.

The biogeography of host‐associated bacterial microbiomes: Revisiting classic biodiversity patterns

AbstractBackgroundThe question of which ecological and evolutionary processes structure the distribution of biodiversity has intrigued scientists for centuries, and historically, inferences have been gained predominantly by studying animals and plants. Although substantial progress has been made towards understanding the multitude of factors that shape host‐associated microbial communities (i.e., microbiomes), it remains largely unknown whether large‐scale geographical patterns in diversity observed for macroorganisms also apply for their microbiomes and whether microbiomes are shaped by the same processes that appear key for determining biogeographical patterns in their hosts.The geographical distribution of microbiome diversityWe discuss challenges and potential approaches for studying microbiome biogeography, with the goal of inspiring future lines of research that can stimulate the development of new ecological and evolutionary theory in the microbiome field. The theory and examples presented here focus specifically on bacterial microbiomes, and we give an overview of host‐associated bacterial microbiome research beginning to examine some of the classic biodiversity patterns central to the fields of ecology and evolution.Potential impacts of microbiome variation for host ecology and evolutionMicrobiome diversity patterns are particularly important to consider because microbes are crucial for many aspects of the biology of their hosts. We discuss how more comprehensive knowledge of the geographical variation of microbiome diversity at the host individual and population levels might be crucial for understanding host ecology and evolution.

Genome-wide identification and characterization of the WOX gene family in Brassica juncea

The WUSCHEL related-homeobox (WOX) family is one of the plant-specific transcription factor families, playing important roles in plant growth and development. In this study, 51 WOX gene family members were identified from the genome data of Brassica juncea by searching and screening with HUMMER, Smart and other software. Their protein molecular weight, amino acids numbers, and isoelectric point were analyzed by using Expasy online software. Furthermore, bioinformatics software was used to systematically analyze the evolutionary relationship, conservative region, and gene structure of the WOX gene family. The mustard WOX gene family was divided into three subfamilies: ancient clade, intermediate clade, and WUS clade/modern clade. Structural analysis showed that the type, organization form and gene structure of the conservative domain of WOX transcription factor family members in the same subfamily were highly consistent, while there was a certain diversity among different subfamilies. 51 WOX genes are distributed unevenly on 18 chromosomes of mustard. Most of the promoters of these genes contain cis acting elements related to light, hormone and abiotic stress. Using transcriptome data and real-time fluorescence quantitative PCR (qRT-PCR) analysis, it was found that the expression of mustard WOX gene was spatio-temporal specific, among which BjuWOX25, BjuWOX33, and BjuWOX49 might play an important role in the development of silique, and BjuWOX10, BjuWOX32, and BjuWOX11, BjuWOX23 respectively might play an important role in the response to drought and high temperature stresses. The above results may facilitate the functional study of mustard WOX gene family.

History of the study of the neural crest (review)

The neural crest has long attracted the attention of evolutionary biologists and, more recently, clinical specialists, as research in recent decades has significantly expanded the boundaries of knowledge about the involvement of neural crest and neural crest cells in the development of human pathology. The neural crest and neural crest cells are a unique evolutionarily based embryonic structure. Its discovery completely changed the view of the process of embryogenesis. Knowledge of neural crest development sheds light on many of the most «established» questions of developmental biology and evolution. Our article will reflect on the historical stages of the discovery and study of the neural crest and the impact of this discovery on entrenched ideas about germ layer specificity and the theory of germ layers – the reasoning of the neural crest as the fourth germ layer. The aim of this review is to describe the history of the discovery and study of neural crest and neural crest cells based on an analysis of the literature. In writing this article, an analysis of the scientific literature was conducted using the search terms «neural crest», «neural crest cells», «neural crest cell morphology», «germinal layers» and «embryonic development» in the computer databases PubMed, Scopus, Web of Science, and eLibrary. The depth of the analytical search corresponds to the period of the discovery of the neural crest and the first mention of the neural crest as an embryonic morphological structure in the scientific literature. The information presented confirms the high interest of research scientists and clinical specialists in the study of neural crest and neural crest cells. The involvement of neural crest cells in the formation of somatic and musculoskeletal pathologies has received particular attention in recent decades. The literature sources are represented by 169 full-text manuscripts and monographs mainly in English. Conclusions. Neural crest and neural crest cells are unique evolutionary structures. Regularities of formation, reasons which condition migration, differentiation, interaction of neural crest cells with other structures during embryogenesis as well as their potential, which is realized in postnatal period, continue to be the subject of research up to now.

Genome-wide characterization of aldehyde dehydrogenase gene family members in groundnut (Arachis hypogaea) and the analysis under saline-alkali stress.

Groundnut or peanut (Arachis hypogaea) is a legume crop. Its seeds are rich in protein and oil. Aldehyde dehydrogenase (ALDH, EC: 1.2.1.3) is an important enzyme involved in detoxification of aldehyde and cellular reactive oxygen species, as well as in attenuation of lipid peroxidation-meditated cellular toxicity under stress conditions. However, few studies have been identified and analyzed about ALDH members in Arachis hypogaea. In the present study, 71 members of the ALDH superfamily (AhALDH) were identified using the reference genome obtained from the Phytozome database. A systematic analysis of the evolutionary relationship, motif, gene structure, cis-acting elements, collinearity, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and expression patterns was conducted to understand the structure and function of AhALDHs. AhALDHs exhibited tissue-specific expression, and quantitative real-time PCR identified significant differences in the expression levels of AhALDH members under saline-alkali stress. The results revealed that some AhALDHs members could be involved in response to abiotic stress. Our findings on AhALDHs provide insights for further study.

Trehalose transporter-like gene diversity and dynamics enhances stress response and recovery in Helicoverpa armigera

Trehalose is a primary sugar and its distribution across the insect body, regulated by trehalose transporters (TRETs), is essential for sugar metabolism and energy homeostasis. The large diversity of Tret-like sugar transporters (ST), belonging to SLC2A transporter family, in polyphagous insects probably contributes to their extremely adaptive nature. We aim to study spatio-temporal expression dynamics and functional relevance of ST transcript variants in the lepidopteran model organism, Helicoverpa armigera. Identification of 69 putative Tret-like HaST transcript variants from databases and their digital gene expression analysis indicated tissue and development-specific expression patterns. Phylogenetic and sequence similarity network analysis of HaSTs signify evolutionary divergence, while motif and structure analysis depicted conserved signatures. In vitro gene expression validation for selected genes depicts that HaST09 and 69 are fat body and haemolymph-specific. While, HaST06, 30, 36 and 57 are developmental stage or sex-specific. HaST69 has high expression in the haemolymph of fifth instar larvae. In the presence of trehalose metabolism inhibitors and abiotic stress, HaSTs expression show dysregulation, indicating their possible association with trehalose metabolism and stress recovery. In vivo gene silencing of HaST69 resulted in reduced trehalose accumulation in the insect body, suggesting its plausible role in sugar metabolism. The overall understanding of HaST diversity and expression dynamics highlights their putative roles in sugar transport during adaptation and stress recovery of insects.

EGNN: Graph structure learning based on evolutionary computation helps more in graph neural networks

In recent years, graph neural networks (GNNs) have been successfully applied in many fields due to their characteristics of neighborhood aggregation and have achieved state-of-the-art performance. While most GNNs process graph data, the original graph data is frequently noisy or incomplete, resulting in suboptimal GNN performance. In order to solve this problem, a Graph Structure Learning (GSL) method has recently emerged to improve the performance of graph neural networks by learning a graph structure that conforms to the ground truth. However, the current strategy of GSL is to iteratively optimize the optimal graph structure and a single GNN, which will encounter several problems in training, namely vulnerability and overfitting. A novel GSL approach called evolutionary graph neural network (EGNN) has been introduced in this work in order to improve defense against adversarial attacks and enhance GNN performance. Unlike the existing GSL method, which optimizes the graph structure and enhances the parameters of a single GNN model through alternating training methods, evolutionary theory has been applied to graph structure learning for the first time in this work. Specifically, different graph structures generated by mutation operations are used to evolve a set of model parameters in order to adapt to the environment (i.e., to improve the classification performance of unlabeled nodes). An evaluation mechanism is then used to measure the quality of the generated samples in order to retain only the model parameters (progeny) with good performance. Finally, the progeny that adapt to the environment are retained and used for further optimization. Through this process, EGNN overcomes the instability of graph structure learning and always evolves the best progeny, providing new solutions for the advancement and development of GSL. Extensive experiments on various benchmark datasets demonstrate the effectiveness of EGNN and the benefits of evolutionary computation-based graph structure learning.

Bimodal effect on mass transport of proton exchange membrane fuel cells by regulating the content of whisker-like carbon nanotubes in microporous layer

The excellent microporous layers (MPLs) in the gas diffusion layer requires superior mass transfer capacity, which is essential to high-performance proton exchange membrane fuel cells. However, the correspondence between MPL structure and mass transfer performance is ambiguous. Here, we design efficient mass transfer channels in MPLs with evolutionary structures by adjusting the content of whisker-like carbon nanotubes (WCNTs). The cell power density exhibits a bimodal shape with the increase of WCNTs in MPLs, which verifies that the perforated cracks of 5–10 μm in the MPL provide the separated channels for water and gas transport, and the optimal hydrophobic mesopores (34.87%) promote the mass transfer efficiency by elevating the capillary force of water transport. At 100% relative humidity (RH), the peak power densities of cells with the two MPLs are increased to 2.321 W cm−2 and 2.117 W cm−2, respectively. The electrochemical impedance spectroscopy confirms that the impedance of both MPLs are 109.35 mΩ cm2 and 63.55 mΩ cm2 at 100% RH and 3 A cm−2. The simple and scalable strategy provides a novel idea to relieve the mass transport loss of fuel cells.

Identification and expression of the CCO family during development, ripening and stress response in banana.

Plant hormone abscisic acid (ABA) plays an important role in plant growth, development and response to biotic / abiotic stressors. Thus, it is necessary to investigate the crucial genes associated with ABA synthesis. Currently, the carotenoid cleavage oxygenases (CCOs) family that function as the key step for ABA synthesis are not well understood in banana. In this study, 13 MaCCO genes and 12 MbCCO genes, divided into NCED subgroup and CCD subgroup, were identified from the banana genome, and their evolutionary relationship, protein motifs, and gene structures were also determined. Transcriptomic analysis suggested the involvement of CCO genes in banana development, ripening, and response to abiotic and biotic stressors, and homologous gene pairs showed homoeologue expression bias in the A or B subgenome. Our results identified MaNCED3A, MaCCD1, and MbNCED3B as the genes with the highest expression during fruit development and ripening. MaNCED5 / MbNCED5 and MaNCED9A might respond to abiotic stress, and MaNCED3A, 3B, 6A, 9A, and MbNCED9A showed transcriptional changes that could be a response to Foc4 infection. These findings may contribute to the characterization of key enzymes involved in ABA biosynthesis, as well as to identify potential targets for the genetic improvement of banana.

A Process-Oriented Exploration of the Evolutionary Structures of Ocean Dynamics with Time Series of a Remote Sensing Dataset

Advanced Earth observation technologies provide a tool for the study of ocean dynamics either in basins or in oceans. In a comparison of when and where, how ocean dynamics evolves in space and time is still a challenge. In view of an evolutionary scale, this paper proposes a novel approach to explore the evolutionary structures of ocean dynamics with time series of a raster dataset. This method, called PoEXES, includes three key steps. Firstly, a cluster-based algorithm is enhanced by process semantics to obtain marine snapshot objects. Secondly, the discriminant rule is formulated on the basis of successive marine snapshot objects’ spatiotemporal topologies to identify marine sequence objects and marine linked objects. Thirdly, a sequence-linked object-based algorithm (SLOA) is used for marine sequence objects and linked objects to obtain their evolutionary structures and to achieve four evolutionary relationships, i.e., development, merging, splitting, and a splitting–merging relationship. Using the evolutionary relationships and their occurring orders in a lifespan of ocean dynamics, this paper reformulates five types of evolutionary structures, which consist of origination nodes, linked nodes, sequence nodes and dissipation nodes. The evolutionary-scale-based dynamic structure ensures the optimum evolutionary relationships of ocean dynamics as much as possible, which provides a new way to design a spatiotemporal analysis model for dealing with geographical dynamics. To demonstrate the effectiveness and the advantages of PoEXES, a real 40-year dataset of satellite-derived sea surface temperatures is used to explore the evolutionary structure in global oceans; the new findings may help to better understand global climate change.

An Improved Evolutionary Structure Optimization Method for Smooth Topology Design of Structures

To meet the needs of industrial production, an improved evolution structural optimization (ESO) method with high efficiency is proposed. The optimized design variables with intermediate density were designed using the windowed evolution structural optimization (WESO) method to increase the stability of the algorithm. The efficient calculation method of the element node sensitivity was established, which realizes the establishment of level set functions, smooth topological design of structures and the updating of design variables. The stability of the proposed algorithm was verified by the Zhou–Rozvany problem, two- and three-dimensional (3D) numerical results. The effectiveness and efficiency of the proposed algorithm was further verified by numerical comparison with other topology optimization frameworks. Lastly, the improved windowed ESO method was applied to the initial configuration design of the double-deck bridge structure, which not only provides guidance for its initial design but also demonstrates the applicability of the method in complex structural systems.

Superconducting boron allotrope featuring pentagonal bipyramid at ambient pressure.

Elemental boron has evoked substantial interest owing to its chemical complexity in nature. It can form multicenter bonds due to its electron deficiency, which induces the formation of various stable and metastable allotropes. The search for allotropes is attractive for finding functional materials with fascinating properties. Using first-principles calculations with evolutionary structure search, we have explored boron-rich K-B binary compounds under pressure. A series of dynamically stable structures (Pmm2 KB5, Pmma KB7, Immm KB9, and Pmmm KB10) containing boron framework with open channels are predicted, which can possibly be synthesized under high pressure and high temperature conditions. After the removal of K atoms, we obtain four novel boron allotropes, o-B14, o-B15, o-B36, and o-B10, which exhibit dynamical, thermal, and mechanical stability at ambient pressure. Among them, o-B14 contains an unusual B7 pentagonal bipyramid and appears in a bonding combination of seven-center-two-electron (7c-2e) B-B π bonds, which is the first time to be identified in three-dimensional boron allotropes. Interestingly, our calculation reveals that o-B14 can act as a superconductor with a Tc value of 29.1 K under ambient conditions.

Polyether phases of formic acid revealed under high pressure.

Evolutionary structure searches reveal that at 20 GPa, formic acid (FA) transforms to an orthorhombic ether-chain polymer phase, ruling out hydrogen bond symmetrization, followed by a novel crowned cyclic-ether tetragonal phase above 60 GPa. Emergence of characteristic polyether and new OH stretching modes in infrared experiments validate the findings. Resemblance of polymer chain with a cosmopolymer polyoxymethylene, shows an engrossing multifaceted evolution of FA.

Uncovering Network Heterogeneity of China’s Three Major Urban Agglomerations from Hybrid Space Perspective-Based on TikTok Check-In Records

Urban agglomeration is an essential spatial support for the urbanization strategies of emerging economies, including China, especially in the era of mediatization. From a hybrid space perspective, this paper invites TikTok cross-city check-in records to empirically investigate the vertical and flattened distribution characteristics of check-in networks of China’s three major urban agglomerations by the hierarchical property, community scale, and node centrality. The result shows that (1) average check-in flow in the Yangtze River Delta, Beijing-Tianjin-Hebei, and Pearl River Delta network decreases in descending order, forming a Z-shaped, single-point radial, and N-shaped structure, respectively. (2) All three urban agglomerations exhibit a nexus community structure with the regional high-flow cities as the core and the surrounding cities as the coordinator. (3) Geographically proximate or recreation-resource cities have a high degree of hybrid spatial accessibility, highlighting their nexus role. Finally, the article further discusses the flattened evolutionary structure of the check-in network and proposes policy recommendations for optimizing check-in networks at both the digital and geospatial levels. The study gains from the lack of network relationship perspective in the study of location-based social media and provides a novel research method and theoretical support for urban agglomeration integration in the context of urban mediatization.

Impact of changes in river network structure on hydrological connectivity of watersheds

River network connectivity is a key factor affecting watershed ecosystems and an important criterion for evaluating the health of river. The river network structure of the basin has changed dramatically in recent years due to human activity, but the response of connectivity to changes in physical structure is still poorly understood. In this paper, a dynamic index (connectivity index) based on daily-scale flow and probability density function is proposed to characterize the connectivity capacity of river networks. The Haihe River basin in China is selected as the study area, and a graphic model is constructed to assess the evolutionary structure of the river network. The 54 sections were classified into Low human impact (LHI) and High human impact (HHI), and the trends and causes of connectivity changes of the sections with the evolution of the network were analyzed. The results reveal that the river network degree and clustering coefficient keep increasing, the path length decreases and becomes more dense downstream, and the river network gradually evolves into a “small-world” network. The “small-world” characteristics improve the potential efficiency and specific functionality of the river network, but make the physical structure mismatch with the hydraulic gradient, and the network flow disperses severely, leading to a significant decrease in connectivity (HHI connectivity index is lower than LHI 52.1%). Moreover, the structural changes enhance the spatial and temporal differences in hydrological connectivity, which further restricts the function of the river system. “Small-world” and connectivity indicators (duration, start time, and intermittency) show strong correlations. Therefore, physical structure is an important factor influencing connectivity capacity of river networks. The planning and management of the watershed should consider the changes in hydrological connectivity caused by the structural modifications of the river network.