Different Types Of Communities Research Articles

Exploring Wildfire Evacuation Strategies for Diverse Communities

Wildfire evacuations have become a persistent challenge all over the world in recent years. Studies have proposed various evacuation strategies, such as vehicle reduction, phased evacuation, and prohibition of on-street parking, which have demonstrated effectiveness in specific communities. However, a comprehensive study that generalizes the effectiveness and applicability of these strategies across different types of communities is lacking. This generalization could hold significant value for small, resource-strapped communities situated in wildland–urban interface zones (i.e., comprising a mix of residences and flammable vegetation) that lack the resources to conduct dedicated evacuation studies. In this study, two indicators, the ratio of background traffic volume to the number of evacuees (RBE), and the ratio of the capacity of the main evacuation roads to the number of evacuees (RCE) were derived to categorize communities into specific groups based on their characteristics during wildfire events. Through evacuation simulations of some typical real-world communities, the applicability and effectiveness of each strategy for each group was assessed. For the given scenarios considered, the findings revealed that for communities with high a RBE and low RCE, promoting carpooling with more than two people per vehicle, extending phased evacuation intervals with safety assurance for evacuees, and enforcing on-street parking prohibition made evacuations more effective. For other communities, encouraging families to use fewer vehicles and implementing a 15-min phased interval, if possible, could potentially be useful.

Exploring and Enhancing Community Disaster Resilience: Perspectives from Different Types of Communities

This study aimed to explore the differences in various aspects of community disaster resilience and how to enhance disaster resilience tailored to different community types. The evaluation results were validated using the flood event that occurred in Zhengzhou on 20 July 2021 (hereinafter referred to as the “7.20” rainstorm disaster). The main results of the analysis showed that the respondents’ overall evaluation of their community’s resilience to the “7.20” disaster was relatively high. Commercial housing communities performed the best, followed by urban village communities, and employee family housing communities performed the worst. Specifically, commercial housing communities scored highest in three dimensions: human capital, physical infrastructure, and adaptation. Urban village communities scored highest in the three dimensions of social capital, institutional capital, and community competence, while employee family housing communities consistently ranked the lowest in each dimension. The most significant disparities were found in human capital, followed by community competence and social capital, adaptation, and, lastly, institutional capital and physical infrastructure. Targeted improvement strategies and measures are suggested for each type of community, offering valuable recommendations for relevant government agencies aiming to enhance community disaster resilience and disaster risk reduction.

Seasonal changes in bird communities on poultry farms and house sparrow-wild bird contacts revealed by camera trapping.

Wild birds are considered reservoirs of poultry pathogens although transmission routes have not been conclusively established. Here we use camera trapping to study wild bird communities on commercial layer and red-legged partridge farms over a one-year timeframe. We also analyze direct and indirect interactions of other bird species with the house sparrow (Passer domesticus), a potential bridge host. We conducted camera trapping events between January 2018 and October 2019, in two caged layer farms, one free-range layer farm, and two red-legged partridge farms in South-Central Spain. We observed wild bird visits on all types of farms, with the significantly highest occurrence on red-legged partridge farms where food and water are more easily accessible, followed by commercial caged layer farms, and free-range chicken farms. The house sparrow (Passer domesticus) followed by spotless starlings (Sturnus unicolor) was the most encountered species on all farms, with the highest frequency in caged layer farms. On partridge farms, the house sparrow accounted for 58% of the wild bird detections, while on the free-range chicken farm, it made up 11% of the detections. Notably, the breeding season, when food and water are scarce in Mediterranean climates, saw the highest number of wild bird visits to the farms. Our findings confirm that the house sparrow, is in direct and indirect contact with layers and red-legged partridges and other wild birds independent of the type of farm. Contacts between house sparrows and other bird species were most frequent during the breeding season followed by the spring migration period. The species most frequently involved in interactions with the house sparrow belonged to the order Passeriformes. The study provides a comparative description of the composition and seasonal variations of bird communities in different types of layer/ poultry farms in Southern Spain i.e. a Mediterranean climate. It confirms the effectiveness of biosecurity measures that restrict access to feed and water. Additionally, it underscores the importance of synanthropic species, particularly the house sparrow, as potential bridge vector of avian pathogens.

A bitcoin service community classification method based on Random Forest and improved KNN algorithm

AbstractThere are service communities with different functions in the Bitcoin transactions system. Identifying community categories helps to further understand the Bitcoin transactions system and facilitates targeted regulation of anonymized Bitcoin transactions. To this end, a Bitcoin service community classification method based on Random Forest and improved K‐Nearest Neighbor (KNN) algorithm is proposed. First, the transaction characteristics of different types of communities are analyzed and summarized, and the corresponding transaction features are extracted from the address and entity levels; then multiple classification algorithms are compared, the optimal model to filter the effective features is selected, and the feature vector of entity addresses is constructed. Finally, a classification model is constructed based on Random Forest and improved KNN algorithm to classify the entities. By constructing different classification models for experimental comparison, the accuracy and stability advantages of the proposed method for classification in service community classification research are verified.

Identifying vulnerable populations in urban society: a case study in a flood-prone district of Wuhan, China

Abstract. In the context of unprecedented extreme weather and climatic events, the internal structural factors of society play a decisive role in determining the extent to which human beings are affected by disasters and their ability to respond to them. In the past few decades, rapid urbanization in developing countries, such as China, has greatly increased social vulnerability. This process has generated uneven living conditions and created many vulnerable groups, including urban poverty, migrants, and socially and geographically marginalized groups. These groups face difficulties in living conditions, education, livelihood stability, and more. This study sets up indicators from a micro-perspective: three indicators of exposure, four indicators of sensitivity, and eight indicators of adaptive capacity. Based on this evaluation index system, this study conducted a social vulnerability assessment of the population in Hongshan District, Wuhan, China, through individual questionnaire surveys. K-means cluster analysis was used to determine high, medium, and low levels of social vulnerability, which were used to compare different community types and identify vulnerable groups. The results showed close interrelationships between different types of communities in terms of physical and built environments as well as varying levels of social vulnerability to disasters. The high-vulnerability group accounted for 12.9 % of the 599 samples, the medium-vulnerability group accounted for 48.4 %, and the low-vulnerability group accounted for 38.7 %. The higher-vulnerability groups exhibited characteristics such as low education, poor health, low annual income, unstable work, and insufficient social security. Quantitative understanding of the degree of dissimilarity in social vulnerability among different communities and populations is significant in reducing social vulnerability and disaster risk specifically and effectively.

ON TWO CONCEPTS OF THE COMMON GOOD: CONSTITUTIONAL DILEMMAS AND POSSIBLE FOUNDATIONS OF LABOUR LAW

The common good is often considered to be the value that integrates a community. Reflection on the common good has taken place primarily in the context of the state. Nevertheless, the common good can also be spoken of in the context of different types of community, including the community created in the workplace. How might one understand the statement that a workplace is the common good of all of its employees?The aim of this paper is to outline two fundamentally different concepts of the common good that have arisen in Polish constitutionalism in connection with the recognition of the state as the common good of all citizens. One of these concepts was applied in the April Constitution of 1935: it has at its centre the raison d’état. The other concept of the common good was adopted in the Constitution of the Republic of Poland of 1997: at its centre is the dignity of the individual. Depending on which of these concepts is adopted, the relationship between the individual and the state will be fundamentally different. The first leads to the conclusion that – to put it simply – the individual is for the state, while the second implies that the state is for the person. Assuming that a workplace is the common good of all employees, depending on which of these concepts of the common good is adopted, either the workplace or the employee will be the primary value, and the perception of the relationship between the employee and the workplace will be fundamentally different.

COMPOSITION AND STRUCTURE OF HYDROPHYTE COMMUNITIES IN DIFFERENT TYPES OF WATER BODIES IN THE CITY OF POLTAVA

The article highlights the results of studying the composition and structure of the true aquatic plant communities in different types of water bodies of the city of Poltava (artificial and natural reservoirs, the urban section of the middle River Vorskla), where, according to the ecological and floristic classification, 21 associations (including 8 subassociations) of eight alliances, three orders and two classes were identified. Of these, only association Ceratophylletum demersi is the most typical in urban area. The class POTAMETEA differs in the relatively higher coenotic diversity (13 associations), and the class LEMNETEA differs in the lower diversity (8 associations). 
 The studied plant associations are characterized by a low species richness, the absolute majority of them represents a simplified version of the original natural associations. Communities of class POTAMETEA, observed in urban reservoirs, are especially depleted (1–3 species in the descriptions). There is a general tendency to increase the coenotic activity of the floristic elements that are tolerant to anthropogenic load and eutrophication.
 In the rank of associations there are 18 communities in urban lentic water bodies and 9 communities on the urban section of the middle river. Most of the identified associations (12) are confined exclusively to urban reservoirs, while only 3 associations are specific to the urban section of the river. Of those 6 associations found both in urban reservoirs and in the urban section of the middle river, it is the river coenoses that are more diverse and better developed.
 In the conditions of an urbanized environment, the middle river ecosystems show a higher resistance to anthropogenic influence compared to ecosystems of artificial urban water bodies, which is evidenced, in particular, by a more complex coenotic structure of common associations, as well as the presence of sozologically valuable communities specifically in the river hydroecotopes.

LOCAL COMMUNITY FESTIVALS: URBAN AND RURAL FEATURES

The purpose of the article is to highlight the specifics of local festivals in different types of communities, distinguished by the indicator of “place of residence” capital, regional city, town and village, pointing out the common features and differences between them. For the realization of this goal, it is necessary to study such important features as: frequency of conduct, thematic focus, activities carried out during the festivals, the subjects that organize and conduct them, the participation of local authorities, institutions, NGOs, media and local people. The leading method in the study of festivals in the text is sociological and its choice is a consequence of the set goal. Object of study are local communities as a specific social construct and social group entity with characteristic social relations, functions, interactions, resources, values and identity. Local festivals are an important element of the lifestyle of local communities; depending on whether the latter are located and developed in an urban or rural environment, the peculiarities, similarities and differences between their festivals are determined. The article analyzes the results of a nationally representative empirical sociological survey conducted on the field in FebruaryMarch 2023 with 800 respondents throughout the country. It was realized within the project “Local Festivals: A Resource of Local Communities to Deal with Crises”. According to the empirical information received, festivals are more often organized and held in regional centers and cities than in Sofia and the villages. The analysis of the results shows that festivals in regional cities, towns and villages have a more diverse thematic focus and more varied activities are carried out during their conduct than in Sofia. The festivals in the regional centers in their thematic focus are closer to those organized in the towns and villages than to those in Sofia. Their main organizer in all types of local communities is the local government in the face of the municipality or the mayoralty. The chitalishte (literally “reading centers” are important cultural institutions in Bulgarian tradition and contemporary society) has a leading role in the organization of the festivals in the towns and villages, unlike the regional centers and Sofia, where their participation is unremarkable. A kind of “profiling” of the festivalization of contemporary lifestyle is formed according to the type of local communities whether they are in the capital, in the regional centers, in the towns or in the villages. Residents of smaller settlements, such as towns and villages, are more actively involved in the organization and holding of festivals than those from regional centers, and in Sofia their participation is the weakest. In these local communities, local institutions and residents manifest themselves as enterprising social actors, their festivals are really local in nature, organization and holding, they carry the spirit, values, traditions, energy, atmosphere and identity of local people.

Beware the community type: engagement and growth in core vs. open online communities

Entrepreneurs can benefit from the communities they build. Therefore, many entrepreneurs create online communities that allow self-selected stakeholders, such as customers, crowd investors, or enthusiasts, to interact with the venture and other like-minded individuals. However, research on how entrepreneurs can successfully engage community members and grow such online communities is only slowly emerging. In particular, it is unclear if, how much, and which content entrepreneurs should contribute to foster engagement in different types of communities and which role these community types play in the community’s overall growth. Based on a longitudinal case study in the video game industry, we first theorize and show that—depending on the community type—both too much and too little entrepreneur-provided content fails to leverage community engagement potential and that different communities require more or less diverging content. We then theorize and show that community growth is largely driven by engagement in open communities, such as those hosted on social media. We outline the implications this has for entrepreneurs, our understanding of online communities, and entrepreneurial communities more generally.

Coordination of Public Service Facilities and Greening in Residential Communities in Beijing

The coordination of green space and public service facilities is of great importance in improving the spatial quality of existing residential districts. This paper adopts the method of a questionnaire survey to investigate the current cooperation between green space and service facilities in residential communities in urban areas in Beijing, China, explores the possibility of their coordinated development in residential areas, and puts forward countermeasures and suggestions for their collaborative transformation. The results show that the three types of facilities that residents thought should be coordinated most with green space were cultural and sports, educational, and social welfare facilities, while commercial service facilities were the most frequently used. Based on the survey results and considering the difficult degree of collaborative transformation of different service facilities and practical problems in implementation, three suggestions were put forward: (a) Differentiated hierarchical control strategies should be put forward for the collaborative transformation of service facilities and green space for different types of communities. (b) Urban planners should optimize the spatial layout relationship between green space and service facility land and pay attention to their functional combination, considering both spatial and functional coordination. (c) In the actual reconstruction, the residents' willingness to transform different public service facilities, the frequency of use, and the objective economic conditions of the community should be comprehensively considered, and the reconstruction should be carried out in stages according to the order of priority.

Efficient community detection in multilayer networks using boolean compositions.

Networks (or graphs) are used to model the dyadic relations between entities in complex systems. Analyzing the properties of the networks reveal important characteristics of the underlying system. However, in many disciplines, including social sciences, bioinformatics, and technological systems, multiple relations exist between entities. In such cases, a simple graph is not sufficient to model these multiple relations, and a multilayer network is a more appropriate model. In this paper, we explore community detection in multilayer networks. Specifically, we propose a novel network decoupling strategy for efficiently combining the communities in the different layers using the Boolean primitives AND, OR, and NOT. Our proposed method, network decoupling, is based on analyzing the communities in each network layer individually and then aggregating the analysis results. We (i) describe our network decoupling algorithms for finding communities, (ii) present how network decoupling can be used to express different types of communities in multilayer networks, and (iii) demonstrate the effectiveness of using network decoupling for detecting communities in real-world and synthetic data sets. Compared to other algorithms for detecting communities in multilayer networks, our proposed network decoupling method requires significantly lower computation time while producing results of high accuracy. Based on these results, we anticipate that our proposed network decoupling technique will enable a more detailed analysis of multilayer networks in an efficient manner.

Light Pollution Risk Level Evaluation model Based on AHP and TOPSIS

In recent years, light pollution problem was hanging over our heads. This paper established Light Pollution Risk Level Evaluation Model(RLE Model)to evaluate the light pollution risk Level of 4 different types of communities. It focused on the following 5 indicators: SQM, region type, GDP, population density and biodiversity. We not only considered the SQM value, but also incorporate other influencing factors into the model and use the Analytic Hierarchy Process(AHP) method to calculate reasonable weights (W1=0.0437, W2=0.0752, W3=0.1425, W4=0.2677 and W5=0.4710). These weights allowed our metric to identify the risk level of light pollution in a region objectively and comprehensively. This paper also use Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to evaluate the light pollution level of different location and got the light pollution level index. This paper divided the light pollution risk levels of 12 sample points into three levels. Four community risk levels are ranked from high to low as urban, suburban, protected areas, and rural areas.

Microbial Community Composition and Diversity in Metal Sulfide Mine Water Systems

To understand the characteristics of heavy metal pollution and physicochemical properties caused by mining activities in mine water systems and the response of the microbial community to habitats with different contamination levels, this study selected different types of water (mining area wastewater, spoil heap area wastewater, dressing area wastewater, mine seepage water, and pond water) as the variables related to the mining activities in the water system of the Shizishan mining area in Tongling, Anhui Province. The pollution characteristics and physicochemical properties were compared, and the relationship between environmental factors and the microbial communities were analyzed. The results showed that the content of heavy metals, the physicochemical properties, and the structure and diversity of the microbial community of different types of water were significantly different in different mine areas, among which the most seriously polluted areas were the mining area, the spoil heap area, and the dressing area. There were significant differences in microbial community structure among different functional types of wastewaters, and the diversity and abundance of the microbial community in DW with the heaviest heavy metal pollution were weaker than those in the other four regions. PcoA analysis showed that samples of similar water types had similar clustering. Spearman correlation heat map analysis and canonical correlation analysis (CCA) indicated that heavy metal pollution, pH, electrical conductivity (EC), SO2-4, and chemical oxygen demand (COD) had the greatest effect on the microbial communities in the mine water systems. Moreover, this study found that Proteobacteria, Euryarchaeota, and Bacteroidetes dominated in mine water systems, and their potential use could be explored in the future. Our results provide a better understanding of the different types of water pollution characteristics in mine water systems and the key factors that determine the microbial community structure.

Analysis on the loss path and cooperative protection of global biodiversity based on input-output model

Biodiversity plays a vital role in human survival and development. In the context of economic globalization and increasingly serious global biodiversity loss, the division of global biodiversity responsibilities and cross-regional cooperative conservation are important parts of species conservation. In this paper, an environmentally expanded multi-regional input-output analysis model is used to measure biodiversity loss footprint (overall footprint, internal footprint and external footprint), which not only covers the interference within the region, but also traces the influence out of it. In addition, structural path analysis and social network analysis were used to identify the transmission process and divide the biodiversity protection communities in various countries. The results show that: (1) There are significant differences among countries in terms of biodiversity loss footprint. The top five countries in terms of overall biodiversity loss footprint are Indonesia, China, the United States, Mexico and Brazil, but they have different impact modes on biodiversity; (2) While most of the footprint of biodiversity loss occurs within the region, more than a quarter of the footprint is due to global production chains outside the region. The study concluded that through the global production chain, species will eventually be influenced by the United States, Japan, India and China; (3) Among economic sectors, agriculture has the largest direct biodiversity footprint. Food & Beverages sector has the largest indirect biodiversity footprint; (4) Eight biodiversity protection communities have been formed around the world, including source community and mixed community of biodiversity protection, each four. Among them, the source community is represented by Indonesia, India, Australia, the Philippines and Thailand in South and Southeast Asia, while the mixed community is mainly composed of China, Japan, Cameroon and Vietnam in East Asia and South Africa. In order to protect biodiversity effectively, different strategies are proposed for different types of communities.

Sustainability and interactive network branding in fast‐changing business environments

Sustainability and interactive network branding in fast‐changing business environments

Characteristics of Phytoplankton Communities and Key Impact Factors in Three Types of Lakes in Wuhan

To reveal the characteristics and key impact factors of phytoplankton communities in different types of lakes, sampling surveys for phytoplankton and water quality parameters were conducted at 174 sampling sites in a total of 24 lakes covering urban, countryside, and ecological conservation areas of Wuhan in spring, summer, autumn, and winter 2018. The results showed that a total of 365 species of phytoplankton from nine phyla and 159 genera were identified in the three types of lakes. The main species were green algae, cyanobacteria, and diatoms, accounting for 55.34%, 15.89%, and 15.07% of the total number of species, respectively. The phytoplankton cell density varied from 3.60×106-421.99×106 cell·L-1, chlorophyll-a content varied from 15.60-240.50 μg·L-1, biomass varied from 27.71-379.79 mg·L-1, and the Shannon-Wiener diversity index varied from 0.29-2.86. In the three lake types, cell density, Chla, and biomass were lower in EL and UL, whereas the opposite was true for the Shannon-Wiener diversity index. NMDS and ANOSIM analysis showed differences in phytoplankton community structure (Stress=0.13, R=0.048, P=0.2298). In addition, the phytoplankton community structure of the three lake types had significant seasonal characteristics, with chlorophyll-a content and biomass being significantly higher in summer than in winter (P<0.05). Spearman correlation analysis showed that phytoplankton biomass decreased with increasing N:P in UL and CL, whereas the opposite was true for EL. Redundancy analysis (RDA) showed that WT, pH, NO3-, EC, and N:P were the key factors that significantly affected the variability in phytoplankton community structure in the three types of lakes in Wuhan (P<0.05).

Patterns of the red-listed epiphytic species distribution in coniferous-deciduous forests of the Moscow Region

Epiphytes model the diversity of forest communities and indicate the integrity of natural ecosystems or the threat to their existence. The high sensitivity of epiphytic species to the environmental quality makes them good indicators in anthropogenic landscapes. The study deals with the distribution patterns of rare indicator epiphytic species at the border of their range in the broadleaved– coniferous forest zone, in the central part of the East European Plain within the Moscow region. The distribution and abundance of eight lichen species Anaptychia ciliaris, Bryoria fuscescens, B. implexa, Usnea dasopoga, U. glabrescens, U. hirta, U. subfloridana and the epiphytic moss Neckera pennata were studied. The main environmental factors at the regional level were climate variables based on the Worldclim database, water indices based on Sentinel-2 multispectral remote sensing data, and the anthropogenic impact factor in terms of the Nighttime lights of the earth’s surface based on the Suomi NPP satellite system. It was revealed that the vast majority of records were in the western and northern sectors of the region, i.e. in the broad-leaved–coniferous forest zone, while the vast majority of 0-records were in the southern and eastern sectors, in the area of broad-leaved and pine forests and extensive reclaimed wetlands. The association with different types of communities and biotopes, as well as tree species, was assessed at the ecosystem level, using field data. It has been established that the distribution of the studied species is governed by natural-geographic features of the territory. The principal limiting factors are air pollution, ecological restrictions (high humidity requirement of sites), cutting of mature forests and formation of local anthropogenic infrastructure. In perspective the study of ecology and living conditions of the studied rare species will help determine the optimal conditions contributing to biodiversity conservation in forests near large metropolitan areas and optimization of habitat diversity.

Digital Practices by Citizens During the COVID-19 Pandemic: Findings From an International Multisite Study.

The COVID-19 pandemic brought digital practices and engagement to the forefront of society, which were based on behavioral changes associated with adhering to different government mandates. Further behavioral changes included transitioning from working in the office to working from home, with the use of various social media and communication platforms to maintain a level of social connectedness, especially given that many people who were living in different types of communities, such as rural, urban, and city spaces, were socially isolated from friends, family members, and community groups. Although there is a growing body of research exploring how technology is being used by people, there is limited information and insight about the digital practices employed across different age cohorts living in different physical spaces and residing in different countries. This paper presents the findings from an international multisite study exploring the impact of social media and the internet on the health and well-being of individuals in different countries during the COVID-19 pandemic. Data were collected via a series of online surveys deployed between April 4, 2020, and September 30, 2021. The age of respondents varied from 18 years to over 60 years across the 3 regions of Europe, Asia, and North America. On exploring the associations of technology use, social connectedness, and sociodemographic factors with loneliness and well-being through bivariate and multivariate analyses, significant differences were observed. The levels of loneliness were higher among respondents who used social media messengers or many social media apps than among those who did not use social media messengers or used ≤1 social media app. Additionally, the levels of loneliness were higher among respondents who were not members of an online community support group than among those who were members of an online community support group. Psychological well-being was significantly lower and loneliness was significantly higher among people living in small towns and rural areas than among those living in suburban and urban communities. Younger respondents (18-29 years old), single adults, unemployed individuals, and those with lower levels of education were more likely to experience loneliness. From an international and interdisciplinary perspective, policymakers and stakeholders should extend and explore interventions targeting loneliness experienced by single young adults and further examine how this may vary across geographies. The study findings have implications across the fields of gerontechnology, health sciences, social sciences, media communication, computers, and information technology. RR2-10.3389/fsoc.2020.574811.

Community organizing during the COVID-19 pandemic: How should we act when it comes to minority communities?

Minority communities have borne a disproportionate burden of adverse health outcomes during the COVID-19 pandemic. Notwithstanding, there is a lack of empirical evidence regarding efforts to reduce health inequalities through community organizing. It is also unclear under what conditions professionals act as external assistance providers for community organizing as part of their role. Through multimethod research conducted among social workers who provide services to ultra-Orthodox minority communities in Israel during the pandemic, this study identified that the combination of critical awareness of social justice, weakened social cohesion, and work environment expectations led professionals to assist communities in their community organizing efforts. These strategies include an intercommunity component-building trust in the community and promoting collective efficacy; an interactional component-creating multidimensional platforms that support action; and a behavioral component-increasing the involvement of communities in decision-making spaces in public arenas. The crucial characteristic of providing assistance and support in community organizing lies in the adoption of cultural perspectives. It requires knowledge about and familiarity with the different types of communities within which the professionals operate. This vital understanding can promote critical awareness among a wide range of professionals to promote health equity at the present time when the pandemic is still ongoing.

Structural Organization of Zooplankton Communities in Different Types of River Mouth Areas

The gradients of hydrological, hydrophysical, and hydrochemical conditions form the transition zones in river mouth areas. These areas are considered ecotones in the presence of the edge effect. Our research aimed to identify the main patterns in the structural organization of zooplankton communities in different types of river mouth areas in lowland reservoir tributaries within the Middle Volga basin. A cluster analysis was performed to structure and determine the zooplankton communities. The identified zooplankton communities were characterized by the noticeable heterogeneity in the species structure. We analyzed the spatial distribution of the structural indicators of zooplankton communities and, on the basis of RDA, determined the factors that significantly affect the organization of the ecotone community. An ecotone was found in all types of river mouth areas where the highest density, biomass, diversity, species, and functional richness of zooplankton were noted, as compared to bordering zooplankton communities. As the morphological structure of the mouth areas became more complex, the values of the main structural parameters of zooplankton communities increased. It was demonstrated that conditions in the ecotones are favorable to the development of zooplankton alien species. The major factors determining the species structure of the ecotone zooplankton community were water electrical conductivity (R2 = 21.07%, p-value = 0.001), dissolved oxygen content (R2 = 10.33%, p-value = 0.003), and water transparency (R2 = 9.77 %, p-value = 0.001).