The study was carried out in Gandiol, which straddles the Niayes of Senegal’s northern coastline and the Senegal River delta [6] . The area lies downstream of the Diama dam, south of the city of Saint-Louis. Located at 16˚15' north latitude and 16˚25' west longitude, Gandiol borders the commune of Saint-Louis to the east, the commune of Fass Ngom, National Road 2 and the Toube area, and to the south, the rural commune of Léona in the department of Louga ( Figure 1 ). It lies between the Senegal River and the Atlantic Ocean to the west, covering an area of around 360 km² [5] .

Sampling was conducted monthly from July 2017 to June 2018. A total of 9 sampling stations were selected ( Figure 1 ). In order to ensure a comprehensive sample, two sampling methods were used: the transect method and the dredging method. In the subtidal zone, the transect technique was used, while in the subtidal zone, the dredging method was applied. For the first technique, quadrats of 25 cm on each side, spaced 5 m apart, were placed perpendicular to the bank to a depth of approximately 70 cm. The number of quadrats varied between 2 and 5 depending on the width of the bank. For the second technique, a cylindrical-conical dredge was used in the deep areas (in the middle of the river bed). This dredge, with an opening diameter of 5 cm and equipped with a metal bar, is wrapped in a net with a mesh size of 1 cm. Once at the bottom, the dredge was towed by a strong rope attached to a canoe and collected the fauna that accumulated at the bottom of the net. The dredge was towed using a canoe, with a turn every 5 minutes to collect the S. senilis individuals collected.

The individuals from each surface unit explored by both the dredge and the quadrats were collected and placed in numbered bags. For data processing in this study, individuals collected using both methods were combined. Indeed, combining data obtained from both methods hardly constitutes a bias, since the study of morphometric relationships only uses individual lengths and weights. In the laboratory, the S. senilis individuals were measured and weighed respectively using a caliper and an electronic scale with a precision of 0.01 g. For each individual, the length, height and bulge were measured and the animal weight with its shell was weighed.

Size spectra are established from the total length of the sampled individuals. The study of the length frequency distribution provides an image of the exploited populations and the level of their recruitment, which can provide some information about the state of the exploited stocks [7] [8] . The frequencies were established with a length interval of 1 cm. The formula used to calculate length frequencies is as follows:

$F_i=\left(100\times n_i\right)/N$ (1)

where F_i = frequency, N_i = number of specimens for a given Length, N = total number of S. senilis specimens

The relationship between the total length and weight of S. senilis individuals is generally exponential. It is represented by the following relationship [9] :

$W=a\times L^b$ (2)

where W = total weight (g); L = total length of the fish (mm); a = exponent describing the rate of change of weight with length; b = slope of the regression line (also referred to as the allometric coefficient). The allometric coefficient b (slope of the regression line) varies between 2 and 4, but is often close to 3.

This coefficient (b) expresses the relative body shape of the species. When it is equal to 3, the growth of individuals of the species is said to be isometric. When it is less than or greater than 3, growth is said to be allometric.

If b > 3, allometry is positive, individuals gain weight faster than they grow in length; if b < 3, allometry is negative, individuals grow faster than they grow in length.

Condition factor provides information on the physical condition of a species [10] . It is a tool often used to compare the overall physiological state of populations over a seasonal cycle or between basins with similar or different ecological conditions [11] [12] . Largely influenced by environmental parameters (biotic and abiotic), the condition factor can be used as an index to assess the level of disturbance in an aquatic ecosystem [13] [14] .

The condition factor is obtained using the following formula:

$K=\left(100\times W\right)/L^3$ (3)

where K = condition factor; W = total weight (g), L = total length (mm).

Statistical and graphical processing was carried out using Microsoft Office Excel 2010 and R software. Student’s t-test was used to verify the significance of the results at the significance level α = 0.05.

In the present study, the size frequency distribution was established in Figure 2 . The length of the individuals varied between 1 mm and 82.17 mm with an average length of 24.27 ± 12.65. The length frequency distribution of S. Senilis was of a multimodal type with the appearance of three distinct groups. The first group was composed of individuals with a length between 5.27 and 20 mm. The individuals of the second group and third group had length between 21 - 50 mm and 51 - 80 mm respectively ( Figure 2 ).

The length-weight relationship of S. senilis was established in Figure 3 and the parameters of this relationship were recorded in Table 1 . The estimated value of the allometric rate (b = 2.7728) is significantly different from 3 (p < 0.05), thus illustrating a negative allometric growth for A. senilis.

The monthly evolution of the condition factor of S. senilis was relatively variable ( Figure 4 ). The overall average value of the condition factor was equal to 0.080 ± 0.008. The highest value was recorded during May (Kc = 0.101 ± 0.073) while the lowest value of Kc is obtained in August (Kc = 0.058 ± 0.025). Overall, the condition factor was higher in the cold season than in the warm season with values respectively equal to 0.085 ± 0.009 and 0.072 ± 0.007 with a non-significant difference (p < 0.05).