The length–weight (LWR) and length–length (LLR) relations of 23 species of native freshwater fishes of six families and three orders collected from the Yuanjiang River in the upper reaches of the Red River were analyzed. From June 2023 to October 2024, specimens representing 23 freshwater fish were obtained: Cyprinus rubrofuscus Lacepède, 1803; Placocheilus caudofasciatus (Pellegrin et Chevey, 1936); Poropuntius krempfi (Pellegrin et Chevey, 1934); Microphysogobio yunnanensis (Yao et Yang, 1977); Abbottina rivularis (Basilewsky, 1855); Opsariichthys bidens Günther, 1873; Hemibarbus medius Yue, 1995; Onychostoma gerlachi (Peters, 1881); Rasbora atridorsalis Kottelat et Chu, 1988; Schistura macrotaenia (Yang, 1990); Schistura fasciolata (Nichols et Pope, 1927); Vanmanenia tetraloba (Mai, 1978); Beaufortia leveretti (Nichols et Pope, 1927); Sinogastromyzon tonkinensis Pellegrin et Chevey, 1935; Bagarius rutilus Ng et Kottelat, 2000; Glyptothorax quadriocellatus (Mai, 1978); Glyptothorax honghensis Li, 1984; Glyptothorax interspinalum (Mai, 1978); Hemibagrus pluriradiatus (Vaillant, 1892); Pseudobagrus kyphus Mai, 1978;Tachysurus fulvidraco (Richardson, 1846); Tachysurus virgatus (Oshima, 1926); and Channa gachua (Hamilton, 1822). The total length (TL), standard length (SL), and body weight (BW) were determined for each fish individual to the nearest 0.1 cm and 0.1 g, respectively. All LLR and LWR parameters of 23 fish species were statistically significant (P < 0.001). The length–weight relations of 17 species have not previously been available in FishBase. Moreover, we provided a new distribution record of fish (Rasbora atridorsalis). Our study provided LWR values for the first time, which will help validate the accuracy and predictability of Bayesian models in estimating species-specific growth parameters for data-poor species. The majority of the LWR relations obtained in this study are new to this region. The availability of species- and region-specific data on length–weight relations could help inform future research and management of these species.

Freshwater fishes, length–weight relations, new data, conservation, Yuanjiang River

Yuan Jiang–Red River originates from the eastern foot of Ailao Mountain in the western Yunnan Province of China., which flows into Vietnam where it is called the Red River (Chu and Chen 1989). The Yuanjiang River basin is complex in topography, which inclines from northwest to southeast, forming a landform of high mountains and deep valleys (Chu 1987). It is affected by the southwest monsoon and the southeast monsoon. In recent years, with the continuous intensification of human activities, such as water conservancy projects, water pollution, and overfishing, the fish populations and habitats of the Yuanjiang River have undergone significant changes. Studies have shown that air temperatures and changing precipitation patterns alter river water temperature and flow regimes, affecting fish habitat loops (Barbarossa et al. 2021). The Yuanjiang River sustains more than 120 native freshwater fish species, including many endemics such as Cyprinus rubrofuscus and endangered Bagarius rutilus (see Chu and Chen 1989; Zhang and Cao 2021). These ichthyofauna items constitute keystone components of aquatic trophic webs, with cyprinids regulating algal biomass through herbivory, while predatory silurids maintain prey population equilibrium (Chu 1987).

The length–weight relation in fish, commonly expressed by the power function

W = aL^b

where W is the total weight of a fish [g], L is the length [cm], a is the intercept and b is the coefficient/slope, has been extensively validated as a critical biometric model with substantial empirical support (Froese et al. 2011; Ma et al. 2017). The scaling exponent b serves as a pivotal allometric parameter that delineates distinct growth patterns: isometric growth (b = 3) indicates proportional dimensional scaling, while deviations (b ≠ 3) signify allometric growth trajectories characterized by differential tissue deposition rates. Notably, systematic variations in b-values have been empirically correlated with environmental quality gradients in aquatic habitats, rendering this parameter an effective bioindicator of ecosystem health and resource availability. Such functional relations constitute fundamental elements in contemporary fisheries stock assessment frameworks, as they enable robust biomass estimation, population dynamic modeling, and sustainable yield calculations - prerequisites for evidence-based resource management strategies (Vicky et al. 2000; Froese 2006). The operational integration of these allometric parameters into management protocols underscores their dual utility in both ecological diagnostics and fisheries governance applications.

The following 23 species, representing six families were investigated (Table 1), including: Cyprinus rubrofuscus Lacepède, 1803; Placocheilus caudofasciatus (Pellegrin et Chevey, 1936); Poropuntius krempfi (Pellegrin et Chevey, 1934); Microphysogobio yunnanensis (Yao et Yang, 1977); Abbottina rivularis (Basilewsky, 1855); Opsariichthys bidens Günther, 1873; Hemibarbus medius Yue, 1995; Onychostoma gerlachi (Peters, 1881); Rasbora atridorsalis Kottelat et Chu, 1988[Cyprinidae]; Schistura macrotaenia (Yang, 1990); Schistura fasciolata (Nichols et Pope, 1927)[Nemacheilidae]; Vanmanenia tetraloba (Mai, 1978); Beaufortia leveretti (Nichols et Pope, 1927); Sinogastromyzon tonkinensis Pellegrin et Chevey, 1935[Balitoridae]; Bagarius rutilus Ng et Kottelat, 2000; Glyptothorax quadriocellatus (Mai, 1978); Glyptothorax honghensis Li, 1984; Glyptothorax interspinalum (Mai, 1978)[Sisoridae]; Hemibagrus pluriradiatus (Vaillant, 1892); Pseudobagrus kyphus Mai, 1978; Tachysurus fulvidraco (Richardson, 1846); Tachysurus virgatus (Oshima, 1926)[Bagridae]; Channa gachua (Hamilton, 1822)[Channidae]. Fish samples were systematically collected from the Yuanjiang River Basin in Yunnan, China (Fig. 1), over a 2023–2024 timeframe, encompassing flood and dry seasons. Two fishing methodologies were employed: multipanel nylon gillnets (20–40 m long, 1–3 m high, mesh size 3–8 cm) and cage nets (0.2 m height, 0.3 m width, and 40 m long, mesh size 5 mm). To maintain standardization, fishing operations occurred primarily during the early morning hours, from 05:00 to 07:00. The taxonomic information (family, genus, and species) of all the samples was determined by examining their morphological features as described in the literature (Chu 1987; Chu and Chen 1989; Chen 1998a; Chen 1998b) and the obtained parameters were confronted with those available in FishBase (Froese and Pauly 2024).

Figure 1. 

Map of the study area: the location of the Yuanjiang River Basin, Yunnan, China.

The total length (TL), standard length (SL), and body weight (BW) of the fish individuals were determined on-site with an accuracy of 0.1 cm and 0.1 g, respectively. The length–weight relations were established for 23 fish species using the equation

BW = aTLb

which was log-transformed to the form:

Log(BW) = log(a) + blog(TL)

Here, BW represents the wet body weight [g], TL is the total length [cm], a is the intercept, and b is the slope. The 95% confidence intervals (CIs) and the coefficient of determination (R²) were calculated for the regression parameters a and b. Additionally, a linear regression analysis was performed to determine the length–length relations (LLR) using the equation

TL = aSL + b

For species where R² was less than 0.95, outliers were removed, and the regression was recalculated. This study assessed the significance of all regressions in the datasets using OriginPro 11.0.

The length–weight relations (LWR) and length–length relations (LLR) of 23 fish species were rigorously estimated and statistically analyzed. Table 1 presents data for LWR parameters. and Table 2 summarizes the LLR (TL vs. SL) data. The ranges of TL [cm] and BW [g], as well as the LWR parameters (a and b), the confidence of determination (R²), and 95% confidence intervals (CI) for a and b are shown in Table 1. The values of parameter b range from 2.431 to 3.367 for 23 fish LWRs, with R² values ranging from 0.911 to 0.996 for the LWR, indicating strong associations. Of the 23 species included, we contributed new insights by establishing 17 previously undocumented fish LWRs and LLRs with no existing records in FishBase. (Froese and Pauly 2024). Additionally, we provided two new distribution records of fish (Rasbora atridorsalis), which had never been reported in FishBase.

The Yuanjiang River features a wide altitude range, varying from 2625 to 115 m, which results in significant differences in environmental factors across its regions (Ye et al. 2008). Due to these environmental influences and their development, fish length and weight often grow at different rates. Additionally, factors such as the fish gender, growth, development, and living environment will all impact the values of the coefficient parameters a and b. For the 23 native fish species studied, all the P values were highly significant (P < 0.001), aligning with previous estimates (Froese et al. 2014). These results indicate that the models used have a high degree of explanatory power for estimating the variation in length–weight relations (LWR) and will serve as a reliable resource for the fish species in the Yuanjiang River available in FishBase.

Of the 23 fish species studied, nine species (39.1%) exhibited negative allometric growth, while 14 species (60.9%) showed positive allometric growth. This indicates that fish growth in the Yuanjiang River exhibits a degree of negative allometric growth, which may be attributed to human activities, such as overfishing, leading to younger ages for fish in the river (Froese et al. 2014; Li et al. 2016). The miniaturization of fish resources is a common issue within fisheries and fish ecology. This phenomenon reduces fishery productivity in aquatic environments and alters the composition of aquatic communities, subsequently affecting the structure and function of aquatic ecosystems. Various factors contribute to the miniaturization of fish stocks, including the construction of water conservancy projects, overfishing, and the reduction of habitats and spawning grounds (Froese et al. 2014). The deviation of the b-value in allometric growth is influenced by the fish growth environment and the biological productivity of available food. High productivity promotes positive allometry, whereas low productivity regions, such as deeper waters, tend to favor negative allometry. The 23 fish species studied were found to be allelic, with the dominant species in the Yuanjiang River including Cyprinus rubrofuscus, Onychostoma gerlachi, Opsariichthys bidens, Schistura fasciolata, Vanmanenia tetraloba, and Abbottina rivularis. This suggests that partial fish in the Yuanjiang River thrive in a highly productive environment. To protect fish resources and manage sustainable fishing practices effectively, it is recommended to implement long-term monitoring of fish resources, analyze community and population dynamics, and comprehensively evaluate the relation between the river’s ecological environment and its fishery resources.

This research was funded by the Finance Special Fund of Chinese Ministry of Agriculture and Rural Affairs of the People’s Republic of China (Fisheries resources and environment survey in the key water areas of Southwest China; Scientific Innovation Fund, PRFRI (2023CXYC6); Pearl River fishery resources investigation and evaluation innovation team project (2023TD10); This study was funded by Science and Technology Program of Guangzhou GrantNumber 202201010762;