The study was conducted in the Bamingui-Bangoran watershed (Figure 1), located in the north of the Central African Republic, a region characterized by a tropical Sudano-Sahelian climate with a marked dry season (November-March) and a rainy season (April-October). The hydrographic network consists of permanent and temporary rivers and streams, exhibiting a diversity of habitats (fast-flowing areas, riffles, slow-moving areas, and varied substrates). The eight sampling stations were selected along the watercourses based on hydromorphological criteria (width, depth, current velocity), accessibility, and potential environmental gradients (upstream-downstream, anthropogenic influence) [9].

Figure 1. Sample collection stations (Moalbaye, 2025).

A range of materials and equipment was deployed for the collection and recording of fisheries data at the various sampling stations. Fish were caught using gillnets of varying mesh sizes and hooks, which were deployed and retrieved using a dugout canoe. Furthermore, the biological and environmental data associated with the specimens were recorded on inventory sheets and then digitally entered using the KoboCollect application.

The physicochemical parameters of the water were measured in situ at each sampling station, concurrently with the fish capture campaigns, to reduce biases related to the temporal variability of environmental conditions. The variables measured included water temperature (˚C), potential of hydrogen (pH), total dissolved solids (TDS, mg·L⁻¹), and electrical conductivity (µS·cm⁻¹), using a multiparameter pH/conductivity instrument (WTW Xylem Analytics, Germany). Dissolved oxygen concentration (DO, mg·L⁻¹) and percentage oxygen saturation (%) were determined using a multiparameter oximeter (Mettler Toledo, Deutscher SAS), equipped with a dissolved oxygen-specific electrochemical probe and a combined pH and temperature probe.

Temperature and pH measurements were performed by immersing the electrode probe at the water surface (≈1 cm depth), with direct reading of the stabilized values on the instrument’s screen. Electrical conductivity, used as an indirect indicator of mineralization and total ionic charge of the water, was measured directly using a conductivity meter, reflecting the total concentration of dissolved ions and the salinity of the medium [10]. Dissolved oxygen was measured by an electrochemical sensor calibrated before each sampling campaign, providing concentrations in mg·L⁻¹ as well as relative oxygen saturation values (%).

Water turbidity was estimated from the transparency depth measured using a Secchi disk, a two-colored (black/white) circular disk attached to a graduated string. The disk was submerged vertically until it disappeared completely from view, and the corresponding depth (Secchi depth) was recorded. This measurement provides an optical indicator of water transparency and has an inverse relationship with turbidity [11].

Fish were collected using a combination of passive and active fishing techniques. Initially, gillnets were deployed upstream and downstream of the site to define a capture zone a few meters wide. These nets were deployed vertically and horizontally at a depth adapted to the characteristics of the watercourse. Subsequently, an active fishing session of approximately one hour was conducted using cast nets. In cases of low catches, a disturbance operation was performed by beating the water surface (1 to 2 minutes using wooden sticks) to dislodge fish from their hiding places and optimize capture. The captured specimens were immediately kept in a cooler placed at the water’s edge to preserve their biological integrity. They were then sorted and identified to the species level using appropriate taxonomic keys.

As part of a fish biodiversity study conducted in the Bamingui-Bangoran region, fish sorting was an essential preliminary step to biological analyses. It was carried out immediately after capture to prevent any alteration of the specimens. Individuals were grouped according to their morphological characteristics, including body shape, fins, scales, coloration, and the presence of barbels, using reference identification guides. A count by species allowed for the estimation of abundance, relative frequency, and species dominance. Taxonomic identification relied on the use of dichotomous keys adapted to the ichthyofauna of Central Africa. This took into account various morphological criteria such as fin arrangement, scale type, ray formula, and mouth morphology. The specimens were then classified by morphotype and coded according to their site of origin. They were weighed precisely and then preserved in 95% alcohol. This rigorous protocol ensured the reliability of the collected data. It thus allowed for an accurate assessment of the species richness and structure of the fish communities.

Taxonomic composition and richness were assessed based on the total number of taxa recorded, as well as the frequency and percentage of taxonomic units across all studied sites. The collected data allowed for the calculation of several biological indices commonly used in the study of aquatic biodiversity. The species diversity of the communities was estimated using the Shannon-Weaver index, which takes into account both the richness and the relative abundance of taxa. This index is expressed according to the following formula:

H' = −∑Ni/N∙Ln (Ni/N)

With H': Shannon-Weaver index, Ni: number of individuals of a given species, and N: total number of individuals. The Pielou Evenness Index [12], which reflects the degree of diversity achieved, was calculated to identify the balance of the stands according to the following formula:

E = H'/H_max = H'/Log2S

With S: number of species observed.

These indices were determined using the vegan package of the R software (version).

The similarity of fish populations between stations was assessed based on the average abundances of taxa. A distance matrix was constructed using the Euclidean method, allowing for the quantification of dissimilarities between stations. Community structure was analyzed using hierarchical clustering (McQuitty method), performed with the ade4 packages and stats using the R software. This approach made it possible to identify groupings of stations with similar populations.

Temperature: Station 2 (Bamingui) had the highest temperature (37.3˚C), due to its full sun exposure and lack of vegetation cover. The other stations, partially shaded by forest or wooded savanna, were cooler. Dissolved oxygen: Overall, higher levels were recorded at the Bamingui stations than at the Bangoran stations. The highest value was recorded at station 2 (6.2 mg/L), while station 6 (Bangoran) had the lowest level (3.8 mg/L), likely related to the density of aquatic vegetation.

Electrical conductivity: Measurement of the presence of ions in water, necessary for the transport of electric current. The conductivity varied between 95 and 110 µS/cm, except at station 2 (Bamingui) where it was low (53 µS/cm), indicating a low ion concentration.

pH: Characterizes the acidity or alkalinity of the water. Stations 2 and 4 were slightly alkaline with pH values of 7.3 and 7.4 respectively.

The variations observed between stations reflect the influence of sunlight, vegetation, and the chemical composition of the water on the physicochemical parameters. Bamingui had more oxygenated and slightly less ionized water, while Bangoran showed generally less oxygenated and turbid water (see Table 1).

Table 1.Physico-chemical parameters determined in situ at the surveyed stations in Bamingui and Bangoran.

Turbidity: Determined by the distance from Secchi. The shorter the distance, the more turbid the water. The most turbid stations were: station 2 (Bamingui) and stations 4 and 5 (Bangoran).

The hippopotamus pond (Bamingui 3) was the station with the highest number of fish collected, with 112 individuals collected out of 213, representing 52.11% (Figure 1). The second highest number of individuals was Bangoran 2 (station 5) with 37 caught, or 17.37%. The Bamingui 1 and 2 stations had the lowest numbers of individuals, with 5 and 6 individuals respectively (2.82% and 2.35%, respectively; Figure 2).

Figure 2. Frequency of fish caught (total = 213 individuals) in the surveyed aquatic environments.

Individuals from the Mormyridae family were the most abundant (80 individuals) and represented 37.56% of the fish caught. The Cichlidae (41 individuals), Cyprinidae (40 individuals), and Clacriidae (27 individuals) families represented approximately 19.25%, 18.78%, and 12.68% of the fish population caught during the survey, respectively. Some identified fish families are presented in Figure 3.

Figure 3. Frequency of fish caught per family (total = 213 individuals).

Table 2.Diversity indices of fish collected in Bamingui and Bangoran.

Fish populations were more diverse at Bangoran 2 (station 5, H' = 1.57) and Bangoran 1 (station 4, H' = 1.5), although these stations had lower numbers of individuals caught than Bamingui 3 (station 3, H' = 1.22). The station with the least diverse population was Bamingui 2 (station 1; Table 2).

The abundance of taxonomic groups at each surveyed station is around the average (E = 0.5) on the Pielou scale. This implies that the population is generally distributed across at least two taxa at each station, but the abundance of taxa is not identical at each station. Furthermore, at Bamingui 3, most of the fish collected (81/112) belonged to a single family (Mormyridae, sp.), which explains the lowest Pielou index (E = 0.33).

The fish population at the stations varied considerably from one station to another. The similarity rate between each pair of stations was less than 10%. Station 3 at Bamingui (where more than 50% of the fish were collected) was approximately 22% similar to all the other stations combined (Figure 4).

Figure 4. Dendrogram of similarity (hierarchical cluster analysis) between fish families in the surveyed stations.