Next Article in Journal
The Swedish Fauna of Freshwater Snails—An Overview of Zoogeography and Habitat Selection with Special Attention to Red-Listed Species
Previous Article in Journal
Diversity and Composition of Soil Microbes Associated with Barringtonia racemosa Communities
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Diversity
Volume 17
Issue 4
10.3390/d17040250
diversity-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Fish Community Composition in the Emur River, a Tributary of the Upper Heilongjiang (Amur) Basin in China

by
Zepeng Zhang
1,2,
Shenhui Li
1,3,
Lianghan Pan
1,4,
Haipeng Wang
1,
Hongyu Jin
1,2,
Wanqiao Lu
1,2 and
Lei Li
1,2,*
1
Heilongjiang River Fishery Research Institute of Chinese Academy of Fishery Sciences, Heilongjiang River Basin Fishery Resources and Environment Scientific Observation and Experiment Station of the Ministry of Agriculture and Rural Affairs, Harbin 150070, China
2
Fuyuan Observation and Experimental Station of National Fishery Resources and Environment, Harbin 150070, China
3
College of Fisheries and Life Sciences, Shanghai Ocean University, Shanghai 201306, China
4
College of Marine Science and Environment, Dalian Ocean University, Dalian 116023, China
*
Author to whom correspondence should be addressed.
Diversity 2025, 17(4), 250; https://doi.org/10.3390/d17040250
Submission received: 28 February 2025 / Revised: 17 March 2025 / Accepted: 19 March 2025 / Published: 31 March 2025
Browse Figures
Versions Notes

Abstract

:
This study investigated the fish species composition and environment of the Emur River, a tributary of the Upper Heilongjiang (Amur) River system, which is a typical extreme-cold region of China. From 2022 to 2024, 28 native species (27 species of fish and 1 species of lamprey), including 4 endangered species, were monitored from 14 sampling sites. When grouped according to the main stream vs. tributaries and summer vs. autumn, we found significant differences (p < 0.05) in the composition of the fish communities. In autumn, the main stream fish assemblage was dominated by common species that prefer a slow current, including Phoxinus phoxinus (33.7%), Lota lota (25.2%), and Phoxinus lagowskii (19.8%). The tributary fish assemblage was primarily composed of typical coldwater fish species, such as L. lota (48.9%), Cottus poecilopus (20.2%), and Thymallus grubii (18.1%). However, in summer, there was no significant difference between the main course and tributaries. Canonical correspondence analysis showed environmental factors, including water temperature, elevation, and dissolved oxygen, to have significant impacts on the fish distribution to an extent that varied with species. This study may contribute to the management of coldwater fish diversity in mountain rivers and the protection of aquatic species habitats in regions of extreme cold.

1. Introduction

Fish, apex organisms of the aquatic food chain, are sensitive to environmental change and are often regarded as key indicators of the health of aquatic ecosystems [1,2]. Anthropogenic impacts pose unprecedented challenges to freshwater biodiversity, directly leading to a decline in fish resources and alterations in the community structure within rivers [3,4,5]. The composition of fish communities is influenced by elevation, latitude, river hierarchy, hydrological conditions, and water quality [6,7]. Identification of the dominant factors influencing a given fish community structure is essential in guiding conservation and the restoration of damaged river ecosystems.
The Emur River is located in the northernmost Mohe region of China, a tributary to the upper stretch of the Heilongjiang (Amur) River, which forms the border between China and Russia. The area is characterized by long periods of extremely low temperatures (record −53 °C) and diurnal temperature variation of up to 30 °C (average 17 °C). The annual mean temperature is −5.5 °C, with eight months having an average temperature below 0 °C [8].
The management and protection of the Emur River is vital to maintaining ecological balance and sustainable development [9,10], and the hydrological characteristics of its watershed have a direct impact on local resource management and agricultural development. In its mid-to-lower reaches, the Emur River flows mainly through plains with riverbed substrates primarily composed of pebbles and pronounced lateral erosion. Several tributaries flow into the Emur, including the Laocao, Dalin, and Gulian Rivers.
With the increasing emphasis on and advancement of environmental protection projects in China, extensive research has been conducted on aquatic ecosystems, particularly on the Liao and Yangtze River Basins [11,12,13]. In contrast, there is a dearth of research on the Heilongjiang River Basin, especially concerning the fish communities of its upstream stretches and tributaries. According to Li and Zhang [14], changes in the environment, for example, habitat destruction, environmental pollution, and human activity, have brought a declining trend in fishery resources in the Heilongjiang River Basin within China that adversely affects fishery production and sustainable development.
The Emur River is rich in fish resources, such as Lota lota and Thymallus grubii [15,16], coldwater species with a survival temperature range of typically 0–20 °C and optimal growth at 12–18 °C [17,18]. This restricted temperature range leads to a high degree of vulnerability, making the species that live here sensitive to climate change. Detailed surveys of fish populations in the Emur River Basin have yet to be carried out.
We recorded the fish population and abiotic parameters for 14 sites in the main Emur River course and its tributaries to determine the fish species composition and spatiotemporal distribution patterns of fish ecological types and identified the key abiotic factors that may influence fish communities, and we tested our hypothesis that environmental factors can affect coldwater fish in cold regions to varying degrees as the climate warms and due the effects of human activities. The results of this study will provide basic information to guide conservation of the Emur River ecosystem and have applications for the conservation of fish communities and biodiversity in other cold regions.

2. Materials and Methods

2.1. Sample Area

The Emur River originates on the northern slope of Mount Zhijichang in the Da Xing’an Mountains, flowing northward and integrating tributaries including the Laocao River (southern branch) and the Dalin River (northern branch). The Emur Basin spans the territory of Mohe City and joins the Heilongjiang River near Dahexi Village in Xing’an town, becoming the second-largest tributary of the upper Heilongjiang River after the Huma River. The geographic coordinates of the Emur River basin are from 52°15′03″ N to 53°33′15″ N and from 122°38′30″ E to 124°05′05″ E. Elevation ranges from 248 to 1397 m asl. The climate is classified as continental monsoon in a cold temperate zone with cold winters and annual precipitation of ~368 mm. The river is 469 km long and 2–5 m deep, with a width of generally 20–150 m and, in some sections, reaching 400–600 m. The drainage area is 16,280 km2. The period of ice cover usually begins in early November and lasts until the spring thaw, lasting 150–180 days [10]. The Emur River is an important tributary of the upper Heilongjiang (Amur) River, which provides habitat for a variety of coldwater fish species.

2.2. Sampling Time and Location

Integrating the life history of fish throughout the year, the surveys were conducted in October 2022 (autumn at the study area latitude), May 2023 (spring), July 2023 (summer), October 2023 (autumn), December 2023 (winter), and May (summer) 2024 at 14 location, covering the entire main stream of the Emur River from the town of Amur to the town of Xing’an along with its major tributaries (11 sites along the main stream E1-11 and 1 sampling point each on the Laocao Z1, Dalin Z2, and Long Rivers Z3) (Figure 1) at an elevation of 252–494 m. In addition to direct sampling, the survey included reports from local residents. Because of forest fire prevention in the Da Xing’an Mountain region and freezing periods, the only time we collected samples from all sites was once in October 2022 and once in July 2023; at other times, additional surveys for rare fish species were monitored.

2.3. Sampling

Fish samples were collected at each site using bottom traps (mesh size 4 mm) and fixed gill nets (mesh size 2–7 cm), with two of each type placed at every sampling point for approximately 12 h. The range of the river section for sample collection (0.5–1 km) and the mesh size were based on the river width, water depth, and flow velocity. Body length (to 1 mm) and weight (to 0.1 g) were measured. Species that could be identified on-site were released immediately after measurement. Fish that could not be identified were preserved in 4% formaldehyde solution and taken to the laboratory of Heilongjiang River Fishery Research Institute for identification. All fish were classified by ecological type according to the relevant literature and materials in the results [19,20,21,22,23]. Considering the threatened or endangered status of some lamprey species, adding them to the study of the fish community structure will help in understanding the dynamics and changes in the diversity of the entire community in the Emur River more comprehensively.

2.4. Environment and Habitat

The longitude, latitude, and elevation (m) of each sampling point were determined using a global positioning system (GPS-76, Garmin Ltd., Olathe, KS, USA). Water depth (m) was estimated, and water temperature (°C), conductivity (μs/cm), dissolved oxygen (mg/L), pH, and total dissolved solids (mg/L) were measured using a portable water quality analyzer (YSI Pro Quatro, YSI Incorporated, Yellow Springs, OH, USA). Transparency (m) was assessed with a Secchi disk on a clear and calm day. In July 2023, flow velocity (m/s) and river width were measured using a flow meter (FP111, Global Water Instrumentation, Inc., Sacramento, CA, USA) and a laser rangefinder (NK-450B, Nohawk Technology, Shenzhen, China), respectively.

2.5. Data Analysis

In order to obtain data on the ecological habits of fish species, the FishBase database (http://www.fishbase.de, accessed on 26 February 2025) was utilized in the present study.
The CLUSTER module of the PRIMER 6 software, based on the Bray–Curtis similarity matrix, was used for cluster analysis of the composition of fish communities (pre-treatment: standardize and square root transformation). The ANOSIM module was used to evaluate species similarities in the fish assemblage among the sampling points, and the SIMPER module was used to determine the species contributing the most to those differences [24]. The t-test in the SPSS 22.0 software was used to compare environmental parameters between the main stream and tributaries of the Emur River, with significance set at p < 0.05. Pearson’s correlation analysis was used to quantify the association among selected environmental parameters (correlation was higher when R > 0.8) [25]. Canonical correspondence analysis (CCA) was conducted using the vegan package in R 4.1.2 to examine relationships between species occurrence and environmental factors, omitting predictors with a variance inflation factor > 5. Model selection was carried out via detrended correspondence analysis [26].
The CLUSTER, ANOSIM, SIMPER, and CCA analyses were performed using quantitative data only from October 2022 and July 2023, which were the most comprehensive and typical, including all selected sites.

3. Results

3.1. Species Composition

From 2022 through 2024, 28 fish species (8 families of fishes and 1 family of lamprey) were identified in the Emur River Basin, comprising 26 species captured and 2 reported as presented by locals (Table 1). The species belonged to seven orders, nine families, and twenty-three genera. Cypriniformes (17 species) accounted for the majority, at 60.7% of the species, followed by Salmoniformes (5 species, 17.9%) and Scorpaeniformes (2 species, 7.1%). At the family level, Cyprinidae contained the most species (13 species, 46.4%), followed by Cobitidae (4 species, 14.3%), Salmonidae (3 species, 10.7%), Thymallidae (2 species, 7.9%), and Cottidae (2 species, 7.9%). We found a single species each of Gadidae, Petromyzontidae, Siluridae, and Odontobutidae, accounting for 3.6% of the total (Table 1). Twenty fish species, including those only reported, were common native species of the Emur River Basin. Phoxinus czekanowskii, Gnathopogon mantschuricus, Gobio tenuicorpus, Pseudorasbora parva, and, occasionally, Saurogobio dabryi, Silurus asotus, Pseudaspius leptocephalus, and Xenocypris argentea were only caught near the confluence with the Heilongjiang River and are primarily resident species of the Heilongjiang main stream and not endemic to the Emur River Basin. Perccottus glenii and G. tenuicorpus were found exclusively in the main Emur River, and Thymallus tugarinae was caught only in the upper reaches of the river. Lampetra reissneri, T. tugarinae, Hucho taimen, and Brachymystax lenok are endangered fish species in China [27].

3.2. Fish Assemblage

The 26 species captured were categorized as carnivorous, omnivorous, or herbivorous (Table 2). Throughout the Emur River Basin, omnivorous fish dominated (16 species, 57.1%), followed by carnivorous (11 species, 39.3%) fish, along with 1 herbivorous species, X. argentea (3.6%), which was found only at the confluence with the Heilongjiang River in the July 2023 survey. All groups found in the tributaries also occurred in the Emur main stream, but in October, native coldwater L. lota and T. grubii were significantly more abundant in the tributaries than in the main stream.
The CLUSTER analysis categorized the fish community in the Emur River Basin in October 2022 into three groups according to at least a 30% species similarity level: I (E1–E5, E7, E9, E11, Z1); II (E6, E8, Z2, Z3); and III (E10) (Figure 2). The SIMPER analysis showed the average species similarity in Group I to be 48.8%, with six species contributing more than 90% to the cumulative similarity, in the order of Phoxinus phoxinus (49.7%), Phoxinus lagowskii (19.4%), L. lota (11.4%), T. tugarinae (4.7%), T. grubii (4.5%), and Cottus poecilopus (3.4%). The average similarity in Group II was 48.7%, with L. lota (89.0%) and P. lagowskii (3.9%) contributing more than 90% to the cumulative similarity. Group III consisted of a single species.
The ANOSIM analysis showed a significant difference in the fish community composition of the Emur River Basin in October 2022 (Global R = 0.10, p < 0.05). The SIMPER analysis showed that the main stream fish assemblage was dominated by P. phoxinus (33.7%), L. lota (25.2%), and P. lagowskii (19.8%). In comparison, the tributary fish assemblage was dominated by L. lota (48.9%), C. poecilopus (20.2%), and T. grubii (18.1%). In July 2023, the fish community composition in the Emur River Basin was categorized into four groups according to at least a 30% similarity level: I (E1 and E3), II (E4 and E9), III (E7 and E10), and IV (E2, E5, E6, E8, E11 and Z1–Z3) (Figure 3). The SIMPER analysis showed the average similarity in Group I to be 36.1%, with T. tugarinae contributing 100% to the cumulative similarity. The average similarity in Group II was 41.6%, with P. lagowskii contributing 100%. The average similarity in Group III was 59.3%, with three species contributing more than 90% to the cumulative similarity: P. phoxinus (52.8%), Gobio cynocephalus (23.6%), and B. lenok (23.6%). The average similarity in Group IV was 40.8%, with eight species contributing more than 90% to the cumulative similarity, in the order of G. cynocephalus (23.2%), P. lagowskii (23.1%), L. lota (14.2%), P. phoxinus (10.8%), Barbatula nuda (9.9%), C. poecilopus (5.1%), Cobitis granoei (3.3%), and Ladislavia taczanowski (2.6%). There was no significant difference in the fish community composition of the main stream and tributaries in July 2023 (Global R < 0.50, p > 0.05).

3.3. Association of Fish Communities and Selected Environmental Factors

In the surveys conducted in October 2022 and July 2023, the transparency of the main stream and tributaries showed significant differences in July (t-test, p < 0.05, Table 3 and Table 4), while the remaining environmental indicators did not differ at either sampling time (Table 3 and Table 4). In October 2022, the Pearson correlation analysis revealed the water temperature of the main Emur River to be significantly negatively correlated with pH (R = −0.603, p < 0.05) and elevation (R = −0.714, p < 0.05). In contrast, the water temperature of the tributaries was not correlated with other indicators (p > 0.05), while transparency was significantly negatively correlated with water depth (R = −1.0, p < 0.01). In July, the water temperature of the main part of the Emur River was significantly positively correlated with conductivity (R = 0.816, p < 0.01) and total dissolved solids (R = 0.793, p < 0.01) and negatively correlated with elevation (R = −0.928, p < 0.01). Similar to the October results, the water temperature of the tributaries was not correlated with any other indicator (p > 0.05).
In October, the CCA1 and CCA2 axes explained 55.2% of the variation in species structure, with pH and elevation being positively correlated with the occurrence of P. lagowskii, T. tugarinae, B. nuda, P. phoxinus, and P. czekanowskii and negatively correlated with the occurrence of L. reissneri, G. cynocephalus, L. lota, S. dabryi, S. asotus, G. mantschuricus, and Cobitis lutheri. Conversely, total dissolved solids, dissolved oxygen, water temperature, and conductivity showed an opposite trend in terms of the impact on the species distribution. Water depth appeared to have a low influence on the species distribution (Figure 4). In July, CCA showed that the first two axes combined explained 54.8% of variation, with water depth, temperature, and total dissolved solids being positively correlated with P. leptocephalus, X. argentea, Rhodeus sericeus, L. taczanowski, Leuciscus waleckii, P. parva, and G. mantschuricus and negatively correlated with T. grubii, C. poecilopus, and T. tugarinae. Elevation showed a negative correlation with P. leptocephalus, X. argentea, R. sericeus, L. taczanowski, L. waleckii, P. parva, and G. mantschuricus. Flow velocity was negatively correlated with P. lagowskii, B. nuda, P. glenii, C. granoei, and L. reissneri. In comparison, pH and dissolved solids had a lesser impact on the species distribution (Figure 5). Overall, environmental conditions have a considerable impact on the distribution of fish species in the Emur River Basin.

4. Discussion

The Emur River Basin encompasses a unique ecological environment with high biodiversity, including several coldwater fish endemic to the Heilongjiang region. The identified species may be dependent on specific climatic and hydrological conditions, highlighting the importance of conservation of the Emur River Basin. The population of the endangered species L. reissneri, T. tugarinae, H. taimen, and B. lenok might have sharply declined due to changes in habitat [19]. The size observed in some of the identified fish species was smaller than expected. The body length of mature T. grubii has previously been reported as 173–184 mm [19], but the body length of the mature fish in our study was 122.0–168.0 mm, possibly the result of differences in sampling sites and methods. According to Audzijonyte et al. [28], a reduction in fish size can amplify the impact of human activity on ecosystems through positive feedback mechanisms, leading to changes in interspecies interactions, biomass, and catch yields. Decreases in fish populations may result from multiple factors, including habitat destruction, water pollution, overfishing, and climate change [29,30]. Long-term monitoring is needed in the Emur River in the future. Esox reicherti was not captured in this study, possibly because it preferentially inhabits areas of shallow slow-flowing waters with dense aquatic vegetation [19], and most of the sampling sites in this study were open shoals with gravel substrate in the main course of the Emur River. Omnivorous fish species were the most frequent, and herbivores were rare. This does not conform to the River Continuum Concept [31] which suggests that predominant upstream fish trophic guilds are herbivorous, insectivorous, and frugivorous and predominant downstream guilds are omnivorous, detritivorous, and piscivorous. Omnivorous fish can access a variety of food sources, including phytoplankton, zooplankton, and benthic organisms, and their dominance reflects the diversity and richness of food resources in the Emur River Basin [32]. Studies have shown that an increase in the proportion of omnivorous fish species may be a sign of declining water quality [33]. In this study, carnivorous fish were not the dominant taxa, and the low number of species at high trophic levels affects the entire ecosystem [34]. Rivers are characterized by the presence of indigenous fish species, as was the case in this study [35]. The cluster analysis showed a significant difference (p < 0.05) in the fish community composition of the main stream and tributaries in the Emur River Basin in October. In the main stream, P. phoxinus, L. lota, and P. lagowskii showed higher relative rates of contribution to the population than in the tributary samples. This was a factor of small-size fish dominating the samples collected, suggesting a need for the exploration of deeper waters. As the iced-over period approaches, larger fish tend to move to deeper waters for overwintering [19]. We collected greater numbers of L. waleckii and G. cynocephalus with a larger size in the lower reaches. Thymallus tugarinae, a rare and endangered coldwater species [36], is mainly distributed in the upper reaches of the Emur River. In the tributaries, L. lota and C. poecilopus, both of which prefer a gravel substrate, were the highest contributors to the community. Cottus poecilopus exemplifies a typical mountain coldwater bottom-dwelling fish that primarily inhabits cool sandy or gravel riverbeds with a rapid current, sheltering under rocks and moving short-distances [37]. In this survey, C. poecilopus was mainly concentrated in the upstream reaches and all the sampled tributaries. With the approach of winter, the upper reaches (mean temperature 0.73 °C) and their tributaries (mean temperature 1.57 °C) will be the first to freeze over, making them suitable for overwintering for L. lota and C. poecilopus.
There were no significant differences in the fish community composition of the main stream and tributary sampling points in July. During summer, coldwater fish may migrate from the main course to deeper waters of the colder upper reaches and mountain tributaries [38]. This pattern of migration led to greater numbers of G. cynocephalus, P. lagowskii, and P. phoxinus in the tributary samples in July compared to October, with an inter-group average similarity of 83.7% in the upstream and downstream areas in July. P. phoxinus, P. lagowskii, and G. cynocephalus dominated throughout the studied watershed.
Coldwater fish species are highly sensitive to environmental change, particularly temperature and water quality [39]. Increases in temperature as a consequence of climate change may lead to contraction of their habitat range, affecting their distribution and population structure. Some coldwater fish may migrate into colder regions as temperatures rise [39]. Erosion from increased rainfall can bring about changes in flow velocity and substrate properties, affecting fish distribution and survival [40]. In this study, the impact of water depth on the species community in October was less than the other environmental factors, likely because water temperature usually increases with depth. It will be necessary to expand the monitoring of deep water in the future. In winter, coldwater fish tend to congregate in deep water, which reduces their metabolic rate and lipid reserve consumption [41]. While elevation also has an impact on fish distribution, the decrease in elevation from upstream to downstream in the Emur River Basin was not great enough to be a factor. Throughout the Emur River Basin, the fish species composition shifted from typical coldwater fish in Autumn, including T. tugarinae, T. grubii, P. lagowskii, P. Phoxinus, and C. poecilopus, to species more commonly found in summer in the Heilongjiang River and species only occasionally observed in the Emur River Basin (P. leptocephalus, S. asotus, R. sericeus, and X. argentea). These findings reflect the characteristics of fish distribution in rivers of extremely cold regions. As expected, water temperature showed a significant negative correlation with some coldwater fish species. Changes in water temperature can lead to adjustments in fish community structure, impacting species diversity and stability within ecosystems [42], and an increase in the summer water temperature can directly reduce the habitat available for many coldwater fish populations. Flow velocity exhibited a negative correlation with P. lagowskii, B. nuda, and P. glenii, indicating that these species are better adapted to living and reproducing in still or slow-flowing environments.

5. Conclusions

A total of 28 species were found in the Emur River basin, indicating the richness of the fisheries resources in the area. The Emur River Basin is a habitat for a variety of typical coldwater fish species and endangered fish, and the fish community composition varies between upstream and downstream. Environmental factors, including water temperature, pH, and elevation, may influence the distribution of species in the study area. Protecting these unique coldwater fish resources and their habitats is crucial for maintaining biodiversity and responding to the impacts of climate change. However, this requires monitoring over a long period of time to accumulate data. The results of this study provide a basis for fish conservation and the development of management strategies for mountain rivers in extremely cold regions. Future research should involve investigation into the relationships among factors such as land use/cover types and fishing intensity with fish communities in the Emur River Basin.

Author Contributions

Conceptualization, Z.Z.; methodology, Z.Z., L.L. and S.L.; software, Z.Z.; validation, Z.Z., S.L. and L.P.; formal analysis, Z.Z.; investigation, Z.Z., H.W., H.J. and W.L.; data curation, L.P. and W.L.; writing—original draft preparation, Z.Z.; writing—review and editing, Z.Z. and L.L.; visualization, Z.Z., S.L. and L.P.; supervision, L.L.; project administration, L.L.; funding acquisition, L.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the special project on agricultural financial fund from the Ministry of Agricultural and Rural Affairs of China titled “Regular monitoring of fishery resources and environment in key waters of Northeast China”, Central Public-Interest Scientific Institution Basal Research Fund, CAFS (NO. 2024GH01, 2023TD07) and Assessment of the effectiveness of fish stocking in Heilongjiang Province.

Institutional Review Board Statement

The animal study protocol was approved by the Ethics Committee of Heilongjiang River Fisheries Research Institute of CAFS; the protocol code is 20220930-001, and the application date is 30 September 2022.

Data Availability Statement

The information provided in this research can be obtained from the corresponding author upon request.

Acknowledgments

We extend our gratitude to the crews involved in the survey for their efforts in collecting the data.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Karr, J.R. Assessment of biotic integrity using fish community. Fisheries 1981, 6, 21–27. [Google Scholar] [CrossRef]
  2. Simon, T.P.; Lyons, J. (Eds.) Application of the Index of Biotic Integrity to Evaluate Water Resource Integrity in Freshwater Ecosystems; CRC Press: Boca Raton, FL, USA, 1995; pp. 245–262. [Google Scholar]
  3. Zhang, P.; Qiao, Y.; Grenouillet, G.; Lek, S.; Cai, L.; Chang, J. Responses of spawning thermal suitability to climate change and hydropower operation for typical fishes below the Three Gorges Dam. Ecol. Indic. 2021, 121, 121107186. [Google Scholar] [CrossRef]
  4. Couto, T.B.A.; Rezende, R.S.; Aquino, P.P.U.D.D.; Costa-Pereira, R.; Campos, G.L.D.; Occhi, T.V.; Vitule, J.; Espírito-Santo, H.M.; Soares, Y.F.F.; Olden, J. Effects of small hydropower dams on macroinvertebrate and fish assemblages in southern Brazil. Freshw. Biol. 2023, 68, 956–971. [Google Scholar] [CrossRef]
  5. Yuan, S.Y.; Qiu, J.J.; Tang, H.W.; Xu, L.; Xiao, Y.; Liu, M.Y.; Rennie, C.; Gualtieri, C. Fish community traits near a large confluence: Implications for its nodal effects in the river ecosystem. J. Hydrol. 2023, 626 Pt B, 130335. [Google Scholar] [CrossRef]
  6. Marchetti, M.P.; Moyle, P.B. Effects of flow regime on fish assemblages in a regulated California stream. Ecol. Appl. 2001, 11, 530–539. [Google Scholar]
  7. Casatti, L.; Langeani, F.; Ferreira, C.P. Effects of physical habitat degradation on the stream fish assemblage structure in a pasture region. Environ. Manag. 2006, 38, 974–982. [Google Scholar] [CrossRef]
  8. Xu, L.L.; Kang, H.Y.; Pan, M.X.; Han, F.Q.; Shen, Y.Z.; Yu, W.B.; Zhang, X.H. Characteristics analysis of extremely cold weather in the Greater Khingan Mountains region. J. Glaciol. Geocryol. 2022, 44, 1748–1756. [Google Scholar]
  9. Zhan, Q.H.; Sun, F.R.; Zhao, X.J. Countermeasures and genesis of water and soil erosion at Emur River Valley. J. Heilongjiang Water Conserv. Coll. 2005, 32, 91–92. [Google Scholar]
  10. Jia, M.H.; Yu, C.G.; Chen, L.; Dai, C.L. Study on Runoff Variation and Influencing Factors in the Ermur River Basin. Gansu Water Resour. Hydropower Technol. 2023, 59, 1–5. [Google Scholar]
  11. Liu, B.; Zhang, Y.; Qu, X.D.; Liu, S.S.; Meng, W.; Ding, S. Community structure and diversity of fishes in the Liao River Nature Reserve. Freshw. Fish. 2013, 43, 49–55. [Google Scholar]
  12. Qin, Q.; Xu, J.H.Y.; Zhang, F.B.; He, S.; Zhou, T.; Li, S.Y.; Zeng, Y. Length-Weight Relationships and Diversity Status of Fishes in the Midstream of the Jialing River, a Tributary of the Upper Yangtze River, China. Diversity 2023, 15, 561. [Google Scholar] [CrossRef]
  13. Wang, Y.P.; Deng, Y.M.; Liu, S.L.; Li, P.J.; Liu, K. Status analysis of fish community in the lower reaches of the Yangtze River at the beginning of 10-year fishing ban and assessment of fishing ban effect. J. Fish. China 2023, 47, 206–218. [Google Scholar]
  14. Li, Z.W.; Zhang, Z.L. Current Status and Major Countermeasures for Fish Stock Enhancement and Release Work in Heilongjiang Province. Heilongjiang Water Resour. 2020, 39, 8–11. [Google Scholar]
  15. Shao, H.L.; Zhang, Z.P.; Jin, H.Y.; Chi, M.; Xing, Y.; Li, S.H.; Li, L. Feeding Ecology of Burbot (Lota lota) in the Ermur River in Autumn. Chin. J. Fish. 2023, 36, 101–108. [Google Scholar]
  16. Ma, B.; Huo, T.; Jiang, Z.F. A New Record Species Of The Genus Thymallus (Salmoniformes, Thymallidae) In China. Acta Zool. Syst. Sin. 2007, 23, 986–988. [Google Scholar]
  17. Sarkar, T. Cold water fish diversity and their conservation status in Teesta, Jaldhak, Torsa, Kaljani and Sankosh Rivers of the Dooars region, West Bengal, India. Asian J. Conserv. Biol. 2021, 10, 146–152. [Google Scholar]
  18. Singh, A.K. Advances in Indian Cold Water Fisheries and Aquaculture. J. Fisheriessciences.com 2015, 9, 48–54. [Google Scholar]
  19. Zhang, J.M. Fish Fauna of Heilongjiang Province; Heilongjiang Science and Technology Press: Harbin, China, 1995. [Google Scholar]
  20. Zhu, S.Q. Key to Freshwater Fishes of China; Jiangsu Science and Technology Press: Nanjing, China, 1995. [Google Scholar]
  21. Chen, Y.Y. Fauna of China: Osteichthyes: Cypriniformes (Vol. II); Science Press: Beijing, China, 1998. [Google Scholar]
  22. Dong, C.Z.; Li, H.M.; Mu, Z.B.; Zhan, P.R. Freshwater Cold Water Fishes of China; Heilongjiang Science and Technology Press: Harbin, China, 2001. [Google Scholar]
  23. Xie, Y.H. Freshwater Fishes of Northeast China; Liaoning Science and Technology Press: Shenyang, China, 2007. [Google Scholar]
  24. Clarke, K.R.; Warwick, R.M. Change in Marine Communities: An Approach to Statistical Analysis and Interpretation, 2nd ed.; PRIMER-E: Plymouth, UK, 2001. [Google Scholar]
  25. Cheek, B.D.; Grabowski, T.B.; Bean, P.T.; Groeschel, J.R.; Magnelia, S.J. Evaluating habitat associations of a fish assemblage at multiple spatial scales in a minimally disturbed stream using low-cost remote sensing. Aquat. Conserv. Mar. Freshw. Ecosyst. 2016, 26, 20–34. [Google Scholar]
  26. Hardoon, D.R.; Szedmak, S.; Shawe-Taylor, J. Canonical Correlation Analysis: An Overview with Application to Learning Methods. Neural Comput. 2004, 16, 2639–2664. [Google Scholar]
  27. Zhang, Z.P.; Jin, H.Y.; Lu, W.Q.; Chi, M.; Shao, H.L.; Li, L. Community structure analysis of macrobenthos in Jiayin to Luobei section of the Mid-reaches of Heilongjiang River in Summer. Chin. J. Fish. 2023, 36, 87–93. [Google Scholar]
  28. Audzijonyte, A.; Kuparinen, A.; Gorton, R.; Fulton, E.A. Ecological consequences of body size decline in harvested fish species: Positive feedback loops in trophic interactions amplify human impact. Biol. Lett. 2013, 9, 20121103. [Google Scholar]
  29. Xie, P. Biodiversity Crisis in the Yangtze River: Dams Are the Culprits, Overfishing Is the Accomplice. J. Lake Sci. 2017, 29, 1279–1299. [Google Scholar]
  30. Zhao, Y.H.; Xing, Y.C.; Lv, B.B.; Zhou, C.J.; Yang, W.B.; Zhao, K. Species diversity and conservation of freshwater fishes in the Yellow River basin. Biodivers. Sci. 2020, 28, 1496–1510. [Google Scholar]
  31. Vannote, R.L.; Minshall, G.W.; Cummins, K.W.; Sedell, J.R.; Cushing, C.E. The river continuum concept. Can. J. Fish. Aquat. Sci. 1980, 37, 130–137. [Google Scholar]
  32. Mei, X.Y.; Razlutskij, V.; Rudstam, L.G.; Jeppesen, E.; Tang, Y.L.; Zhang, X.F.; Liu, Z.W. Effects of omnivorous fish on benthic-pelagic habitats coupling in shallow aquatic ecosystems: A minireview. J. Lake Sci. 2021, 33, 667–674. [Google Scholar]
  33. Yue, F.; Luo, Z.K.; Wu, D.; Pei, E.L.; Wang, T.H. Species composition and biodiversity of fish community in Dalian Lake, Shanghai. Zool. Res. 2010, 31, 657–662. [Google Scholar]
  34. Shan, X.; Sun, P.; Jin, X.; Li, X.; Dai, F. Long-Term Changes in Fish Assemblage Structure in the Yellow River Estuary Ecosystem, China. Mar. Coast. Fish. 2013, 5, 65–78. [Google Scholar]
  35. Liu, F.; Li, M.; Wang, J.; Gong, Z.; Liu, M.; Liu, H.; Lin, P. Species composition and longitudinal patterns of fish assemblages in the middle and lower Yarlung Zangbo River, Tibetan Plateau, China. Ecol. Indic. 2021, 125, 107542. [Google Scholar]
  36. Ma, B.; Jiang, Z.F.; Huo, T.B. Analysis of genetic variation and geographic divergence of Thymallus tugarinae by microsatellite. J. Fish. Sci. China 2009, 16, 684–694. [Google Scholar]
  37. Nielsen, J.L.; Lisle, T.E.; Ozaki, V. Thermally Stratified Pools and Their Use by Steelhead in Northern California Streams. Trans. Am. Fish. Soc. 1994, 123, 613–626. [Google Scholar]
  38. Kotusz, J.; Krappe, M.; Kusznierz, J.; Propiolek, M.; Riel, P.; Waterstraat, A.; Witkowski, A. Distribution, density and habitat of Cottus poecilopus (Heckel, 1836) in Lake Hancza (North East Poland) as compared with the situation in the Luzin lakes (North East Germany). Verh. Ges. Ichthyol. 2004, 4, 91–105. [Google Scholar]
  39. Perry, A.L.; Low, P.J.; Ellis, J.R.; Reynolds, J.D. Climate Change and Distribution Shifts in Marine Fishes. Science 2005, 308, 1912–1915. [Google Scholar] [PubMed]
  40. Toppo, S.; Rahman, H.; Haque, N. Fish Biodiversity as an Indicator of Riverine Status of Sikkim. 2010. Available online: http://sikkimforest.gov.in/Reports%20and%20Publications/Biodiveristy-of-Sikkim/12%20Fish_221-232%20web.pdf (accessed on 25 February 2025).
  41. Marsden, J.E.; Blanchfield, P.J.; Brooks, J.L.; Fernandes, T.; Fisk, A.T.; Futia, M.H.; Hlina, B.L.; Ivanova, S.V.; Johnson, T.B.; Klinard, N.V. Using untapped telemetry data to explore the winter biology of freshwater fish. Rev. Fish Biol. Fish. 2021, 31, 115–134. [Google Scholar]
  42. Pusey, B.J.; Arthington, A.H. Importance of the riparian zone to the conservation and management of freshwater fish: A review. Mar. Freshw. Res. 2003, 54, 1–16. [Google Scholar]
Diversity 17 00250 g001
Figure 1. Study area and sampling sites in the Emur River.
Figure 1. Study area and sampling sites in the Emur River.
Diversity 17 00250 g001
Diversity 17 00250 g002
Figure 2. Classification of fish assemblages in the Emur River based on the Bray–Curtis similarity of fish species at 14 sites in October 2022 (The dotted line indicates similarity of CLUSTER levels).
Figure 2. Classification of fish assemblages in the Emur River based on the Bray–Curtis similarity of fish species at 14 sites in October 2022 (The dotted line indicates similarity of CLUSTER levels).
Diversity 17 00250 g002
Diversity 17 00250 g003
Figure 3. Classification of fish assemblages in the Emur River based on the Bray–Curtis similarity of fish species at 14 sites in July 2023 (The dotted line indicates similarity of CLUSTER levels).
Figure 3. Classification of fish assemblages in the Emur River based on the Bray–Curtis similarity of fish species at 14 sites in July 2023 (The dotted line indicates similarity of CLUSTER levels).
Diversity 17 00250 g003
Diversity 17 00250 g004
Figure 4. Canonical correspondence analysis ordination plots depicting the relationships between fish assemblages and environmental variables in the Emur River in October 2022 (Red color for environmental factors and blue color for species).
Figure 4. Canonical correspondence analysis ordination plots depicting the relationships between fish assemblages and environmental variables in the Emur River in October 2022 (Red color for environmental factors and blue color for species).
Diversity 17 00250 g004
Diversity 17 00250 g005
Figure 5. Canonical correspondence analysis ordination plots depicting the relationships between fish assemblages and environmental variables in the Emur River in July 2023 (Red color for environmental factors and blue color for species).
Figure 5. Canonical correspondence analysis ordination plots depicting the relationships between fish assemblages and environmental variables in the Emur River in July 2023 (Red color for environmental factors and blue color for species).
Diversity 17 00250 g005
Table 1. Fish species collected in the Emur River from October 2022 through to October 2024.
Table 1. Fish species collected in the Emur River from October 2022 through to October 2024.
FamilySpeciesSpecies Coden
%		Main River Course
%		Tributaries
%		Length
mm		Weight
g		Ecological Type
PetromyzontidaeLampetra reissneriSP10.680.90097–1780.6–5.9OSD
GadidaeLota lotaSP214.6810.9226.14107–37210.0–372.4CMD
SiluridaeSilurus asotusSP30.110.150237–252117.9–170.3CSD
OdontobutidaePerccottus gleniiSP41.131.51038–1101.1–33.2CSD
CyprinidaeXenocypris argenteaSP50.060.08011623.1HSL
Phoxinus phoxinusSP633.9639.6116.7435–720.5–9.5OSD
Phoxinus czekanowskiiSP70.060.080552.8OSD
Phoxinus lagowskiiSP815.3612.8023.1735–1290.5–35.6OSD
Gnathopogon mantschuricusSP90.340.45057–664.0–5.0OSD
Gobio cynocephalusSP109.076.3317.4343–1921.1–49.5OSD
Gobio tenuicorpusSP110.340.45090–11310.6–22.1OSD
Pseudorasbora parvaSP120.110.15040–440.7–1.2OSL
Pseudaspius leptocephalusSP130.110.150167–16851.8–53.0CSL
Rhodeus sericeusSP147.379.79035–790.8–5.8OSD
Ladislavia taczanowskiSP150.790.900.4658–952.6–18.2OSL
Saurogobio dabryiSP160.170.23055–741.5–4.1OSD
Leuciscus waleckiiSP172.563.310.23108–30219.9–535.2OSL
CobitidaeCobitis granoeiSP183.294.290.2345–950.7–4.6OSD
Cobitis lutheriSP190.060.080510.9OSD
Misgurnus mohoitySP200.110.150135–14014.6–17.6OSD
Barbatula nudaSP212.101.583.67510.9OSD
ThymallidaeThymallus grubiiSP222.661.516.1967–2236.8–168.0CSL
Thymallus tugarinaeSP231.642.18092–23512.9–206.1CSL
SalmonidaeBrachymystax lenokSP240.620.600.69128–27030.2–201.7CMD
* Hucho taimen------CMD
* Esox reicherti------CUS
CottidaeCottus poecilopusSP252.551.735.0527–930.1–15.1CSD
Mesocottus haitejSP260.060.0809419.3CSD
Notes: C = carnivorous; O = omnivorous; H = herbivorous; U = upper-to-middle layer; L = lower-to-middle layer; D = bottom layer; M = migratory; S = resident; * = occurrence reported.
Table 2. Seasonal species with respect to trophic guild in the watershed Emur River.
Table 2. Seasonal species with respect to trophic guild in the watershed Emur River.
River SectionOctober, 2022July, 2023
CarnivorousOmnivorousHerbivorousCarnivorousOmnivorousHerbivorous
Entire913010111
Main stream913010111
Tributaries440570
Table 3. Mean values of abiotic factors at 14 sites in the Emur River in October 2022, t-test.
Table 3. Mean values of abiotic factors at 14 sites in the Emur River in October 2022, t-test.
VariablesMain CourseTributariesp
Water temperature (°C)1.29 ± 1.18 a1.57 ± 1.50 a0.738
Transparency (m)0.73 ± 0.45 a0.50 ± 0.35 a0.435
Water depth (m)1.41 ± 0.25 a1.53 ± 0.46 a0.528
pH8.63 ± 0.22 a8.56 ± 0.17 a0.666
Conductivity (μS/cm)77.88 ± 10.59 a81.23 ± 19.27 a0.687
Total dissolved solids (mg/L)40.82 ± 7.04 a46.60 ± 18.76 a0.649
Dissolved oxygen (mg/L)9.05 ± 1.60 a10.23 ± 0.38 a0.238
Elevation (masl)375.05 ± 92.47 a391.33 ± 75.81 a0.786
Note: Superscripts indicate significant differences for t-test (p < 0.05).
Table 4. Mean values of abiotic factors at 14 sites in the Emur River and its tributaries in July 2023.
Table 4. Mean values of abiotic factors at 14 sites in the Emur River and its tributaries in July 2023.
VariablesMain CourseTributariesp
Water temperature (°C)19.70 ± 3.16 a19.67 ± 2.86 a0.987
Transparency (m)1.37 ± 0.22 a0.98 ± 0.15 b0.013
Water depth (m)2.32 ± 0.53 a1.67 ± 0.29 a0.069
pH7.99 ± 0.26 a8.19 ± 0.25 a0.247
Conductivity (μS/cm)92.06 ± 14.45 a103.37 ± 28.46 a0.342
Total dissolved solids (mg/L)46.48 ± 7.17 a51.70 ± 14.22 a0.378
Dissolved oxygen (mg/L)9.99 ± 1.49 a11.17 ± 1.12 a0.233
Elevation (m)377.69 ± 92.96 a382.00 ± 87.73 a0.944
Channel width (m)87.55 ± 65.47 a83.33 ± 58.59 a0.922
Velocity (m/s)0.63 ± 0.36 a0.27 ± 0.21 a0.127
Note: Superscripts indicate significant differences for t-test (p < 0.05).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Zhang, Z.; Li, S.; Pan, L.; Wang, H.; Jin, H.; Lu, W.; Li, L. Fish Community Composition in the Emur River, a Tributary of the Upper Heilongjiang (Amur) Basin in China. Diversity 2025, 17, 250. https://doi.org/10.3390/d17040250

AMA Style

Zhang Z, Li S, Pan L, Wang H, Jin H, Lu W, Li L. Fish Community Composition in the Emur River, a Tributary of the Upper Heilongjiang (Amur) Basin in China. Diversity. 2025; 17(4):250. https://doi.org/10.3390/d17040250

Chicago/Turabian Style

Zhang, Zepeng, Shenhui Li, Lianghan Pan, Haipeng Wang, Hongyu Jin, Wanqiao Lu, and Lei Li. 2025. "Fish Community Composition in the Emur River, a Tributary of the Upper Heilongjiang (Amur) Basin in China" Diversity 17, no. 4: 250. https://doi.org/10.3390/d17040250

APA Style

Zhang, Z., Li, S., Pan, L., Wang, H., Jin, H., Lu, W., & Li, L. (2025). Fish Community Composition in the Emur River, a Tributary of the Upper Heilongjiang (Amur) Basin in China. Diversity, 17(4), 250. https://doi.org/10.3390/d17040250

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop