Experimental fishing of the shrimp fleet of Rio Grande do Norte, northeastern Brazil; highlighting the population structure of Penaeus schmitti and Penaeus subtilis (Crustacea: Penaeidae)

ABSTRACT

This study aimed at defining the catch composition of the shrimp fishery off the coast of Rio Grande do Norte state (06°21’S/35°01’W) and estimating population parameters for Penaeus subtilis and P. schmitti in 2013-2018. Fish bycatch represented most of the biomass. The biomass of P. schmitti showed a weak positive correlation with maximum temperature. The biomass of P. subtilis showed a weak negative correlation with the average pH. An increase in the capture of P. subtilis corresponded to a decrease in P. schmitti. A total of 2,665 specimens of P. schmitti were analyzed, with a sex ratio of F:M=0.74. The carapace length (CL) of the females ranged from 5.70 to 43.20 mm and for males from 8.10 to 36.70 mm. The total weight (TW) of females ranged from 1.12 to 54.1 g (TW=0.0040CL^2.5229) and for males from 1.22 to 32.43 g (TW=0.0021CL^2.7444). A total of 1,404 specimens of P. subtilis were analyzed, with a sex ratio of F:M=1.42. The CL of females ranged from 5.30 to 29.71 mm and that of males, from 8.30 to 25.42 mm. The TW of females ranged from 0.46 to 20.75 g (TW=0.0028CL^2.5999) and that of males, from 0.43 to 13.09 g (TW=0.0026CL^2.6405). Continued monitoring of catch composition and population parameters is recommended for proper stock management.

Keywords:
Southern brown shrimp; Southern white shrimp; Populational biology; Relative growth; Bycatch

INTRODUCTION

Marine shrimp fishing is an activity of great importance in Brazil, with two families of major economic interest: Penaeidae and Solenoceridae (Dias-Neto, 2011). In northeastern Brazil, Penaeidae stands out in production, with four target species of commercial value: Xiphopenaeus kroyeri (Heller, 1862), Penaeus subtilis Pérez Farfante, 1967, Penaeus brasiliensis Latreille, 1817, and Penaeus schmitti Burkenroad, 1936, known as Atlantic seabob, Southern brown shrimp, Red spotted shrimp, and Southern white shrimp, respectively (FAO, 2026).

According to 2007 IBAMA data (the last year for which detailed data on fishery landings by species and state are available), the capture of marine crustaceans in Brazil exceeded 50,000 tonnes, with more than 35,000 tonnes attributed to shrimps (IBAMA, 2007). The shrimp species with the highest catch was X. kroyeri, followed by Penaeus spp., including the Southern brown shrimp, Red spotted shrimp, and Southern white shrimp (IBAMA, 2007). In 2007, crustacean fishery generated a revenue of 403 million reais for Brazil (1US$ = 2.15R$ in 2007), with the northeast region accounting for 65% of this amount (IBAMA, 2007). In that same year, approximately 273 tonnes of marine shrimps were caught off the state of Rio Grande do Norte, generating an ex-vessel value of 2.3 million reais (IBAMA, 2007), highlighting the economic importance of these resources. However, no study has locally evaluated the biology of these species due to the lack of shrimp fishing monitoring programs as they require high costs (Reis-Júnior et al., 2023).

Penaeus subtilis occurs from the Caribbean Sea (Cuba and Lesser Antilles) to Cabo Frio, in the state of Rio de Janeiro (Teodoro et al., 2016). Penaeus schmitti occurs in the southeastern Pacific and western Atlantic, from the southeast of the Gulf of Mexico and Greater Antilles, from Cuba to the Virgin Islands, and from Belize to the state of Rio Grande do Sul (southern Brazil) (Holthuis, 1980; Costa et al. 2003). These species usually spawn in the open sea, and their post-larvae migrate to estuaries, in which they remain sheltered during this period due to their small size and high risk of predation (Dall et al., 1990). In general, the life cycle of these species is short and mixed, estuarine and coastal, thus being characterized as type II (see Dall et al., 1990 for shrimp life cycle definitions).

It is essential to analyze the population biology of species exploited by fishing, such as their morphometric relationships, sex ratio, age and size at sexual maturity, fecundity, growth rate, natural mortality, and recruitment rate (King, 2007; Alencar et al., 2021). This information is crucial to ensure the sustainability of fishing activities and to preserve marine biodiversity (Pauly, 2019). Shrimp fishing is particularly concerning because it is unselective, capturing high volumes of bycatch (Alverson et al., 1994; Fransozo et al., 2016). Overfishing can reduce the abundance of target species, affecting the structure of marine communities and the quality of ecosystems (Scheffer et al., 2005). Knowledge of these parameters can estimate the biomass of a population, determine maximum yield without affecting its sustainability, and develop appropriate management strategies, such as conservation measures, fishing control, and the establishment of environmental protection areas (Pauly, 2019).

Studies with P. subtilis and P. schmitti in northeastern Brazil are so far restricted to a few states, such as Sergipe (Santos et al., 2017; Freire et al., 2019; Santos et al., 2020; Reis-Júnior et al., 2023), Alagoas (Santos, 2010; Barros et al., 2021; Barros et al., 2022), and Pernambuco (Silva et al., 2019). For the state of Rio Grande do Norte, the abundance and production of marine shrimps, without determining the species, has been evaluated regarding the influence of the coastal current (Araújo et al., 2021), but no study has evaluated the population parameters of each penaeid. Thus, this study aimed at determining the specific composition of shrimp fishing catches on the coast of the state of Rio Grande do Norte and at estimating the population parameters for P. subtilis and P. schmitti. The population dynamics of X. kroyeri will be analyzed separately in future studies and, thus, was ignored in this study.

METHODS

STUDY AREA

The study area comprised the coastal zone of the municipality of Baía Formosa in southern Rio Grande do Norte, northeastern Brazil (06°21’S and 35°01’W) (Figure 1). Baía Formosa borders the state of Paraíba and encompasses part of the hydrographic basins of the rivers Curimataú and Guaiú. It has an average rainfall ranging from 800 to 1,600 mm per year (Pinheiro et al., 2010) and a rainy tropical climate (CPRM, 2005). Commercial fishing contributes to the local economy, involving approximately 1,000 fishers, of which 832 are registered in the João Tomé da Silva Colony - Z11, in Baía Formosa, founded in 1949 (Govindin and Miller, 2015). This activity yields more than 350 tonnes/year in the region, including fishes, lobsters, shrimps, and other fishing resources (IDEMA, 2008), showing its economic importance for the municipality and the state.

Figure 1
Location of the shrimp sampling area on the coast of Rio Grande do Norte, northeastern Brazil. The green dots mark the beginning of each trawl, the red dots mark their end, the lines connecting the dots show the trawl paths, and the dashed lines represent the main isobaths.

SAMPLING AND PROCESSING

The samples in this study were collected in three projects under varying durations. The first project was carried out with monthly samplings from February 2013 to February 2015. The second sampling was carried out monthly from January to December 2016, except in February, June, and September. The last period spanned from January 2017 to May 2018, with approximately bimonthly collections. Bottom trawls were carried out with artisanal boats on an experimental basis from 10- to 20-m isobaths in a region frequently used by local fishers during their shrimp fishing (Figure 1). All trawls were carried out using a motorized boat equipped with a single net and a constant speed of approximately 1.9 knots for 20 minutes. During each project, abiotic data were also collected: pH, salinity, temperature (°C), and depth (m) using a multiparameter sonde. The biological samples were stored in ice-packed coolers and taken to the laboratory for further procedures. The shrimp species were identified based on Farfante (1988) and Costa et al. (2003). Each shrimp specimen was sexed based on their external morphology (presence of thelycum in females and petasma in males) (Costa et al., 2003).

The total biomass of each shrimp species was determined for all samples, with each specimen being measured with a digital caliper (carapace length, CL; precision: 0.01 mm) and weighed with an analytical balance (total weight, TW; precision: 0.01 g). Additionally, the total biomass of fishes captured as bycatch during shrimp trawls was determined only during the 2017-2018 project. For more details on the sampling procedure, see Araújo et al. (2021).

DATA ANALYSIS

COMPOSITION OF SHRIMP FISHING

The proportion of each shrimp species (Xiphopenaeus kroyeri, Penaeus schmitti, and Penaeus subtilis) was estimated in relation to the total biomass of shrimps captured during the three projects carried out from 2013 to 2018. Moreover, the biomass of each species was compared with the biomass of the bycatch (represented by fishes) from 2017 to 2018. Since trawling effort (duration, vessel, and gear configuration) was standardized throughout the sampling period, the percentage of catch (biomass) was used to assess the relationship between species dominance and abiotic variables, enabling direct temporal comparison of relative biomass contributions.

While X. kroyeri, P. schmitti, and P. subtilis are the main target species in the regional shrimp fishery, most analyses in this study were restricted to P. schmitti and P. subtilis, for which data were available. The proportions of P. schmitti and P. subtilis were evaluated comparatively and in relation to abiotic factors such as pH, salinity, depth, and temperature (minimum, mean, and maximum). The abiotic data matrix contained missing data due to problems during in situ collections, and this information was imputed using the ‘imputeTS’ package (Moritz and Bartz-Beielstein, 2017), resulting in approximately 9% of the data being imputed for each variable. To observe the relations between the two shrimp species and between each species and abiotic variables, the Pearson correlation coefficient (r) was calculated.

The Cox-Stuart test was used to evaluate an increasing or decreasing trend for the time series of percentage of biomass of P. schmitti and P. subtilis (Mateus and Caeiro, 2014). Subsequently, trend change was analyzed using binary segmentation considering the Bayesian information criterion as a penalty, in which the entire data set is searched until a change point is detected. Once a change point is detected, the data are divided into two subsegments. A similar search is then performed on any subsegment, possibly resulting in more divisions. The division continues until no more changes in the penalty criterion are detected (Fryzlewicz, 2014). This analysis was performed using the ‘changepoint’ package (Killick and Eckley, 2014).

POPULATION STRUCTURE OF P. SCHMITTI AND P. SUBTILIS

Deviations from the expected 1:1 sex ratio were tested using the chi-squared test (χ²) with Yates’ correction. Differences between sexes in the mean CL and TW were separately assessed for each species using Student’s t-tests (Zar, 2010).

The relationships between CL and TW were modeled using the power function TW = aCLᵇ, applied separately for females and males of P. schmitti each year, and for the entire sampling period for P. subtilis given the smaller number of individuals collected for the later species. The significance of the fitted models was evaluated via analysis of variance (ANOVA) (Zar, 2010). The assumption of isometric growth (b=3) was tested using the Student’s t-test (Froese, 2006; Zar, 2010). Weight-length relationships between the sexes of each species were compared using all years grouped via analyses of covariance (ANCOVA) (Zar, 2010). Additionally, ANCOVAs were separately used to compare weight-length relationships between sexes by year only for P. schmitti due to its large sample size. Annual variation in parameters ‘a’ and ‘b’ was also examined only for P. schmitti. CL and TW data were only log-transformed (Zar, 2010) to estimate confidence intervals and apply the ANCOVA.

All statistical analyses of biotic and abiotic data were performed on R (R Core Team, 2024).

RESULTS

COMPOSITION OF THE SHRIMP FISHING

During most analyzed months from 2013 to 2018, X. kroyeri was the most representative species among shrimps (Figure 2A). Penaeus subtilis dominated from November/2016 to March/2017 and February/2018, whereas P. schmitti was clearly dominant in May/2016 (Figure 2A).

Figure 2
Catch composition of the shrimp trawls on the coast of Rio Grande do Norte, northeastern Brazil. (A) Percentage of shrimp biomass captured in trawls from 2013 to 2018. (B) Percentage of biomass including shrimp and fish bycatch from 2017 to 2018.

The ichthyofauna accounted for the largest share of the total biomass (fish + shrimp) in every month of the period analyzed for bycatch, i.e., from 2017 to 2018 (>60%; Figure 2B). In February 2018, the ichthyofauna reached its peak of dominance, corresponding to more than 90% of the total biomass, whereas it reached its lowest proportion in September 2017 (around 60% of the biomass) (Figure 2B).

When evaluating the correlation matrix between the proportion of P. schmitti biomass and the abiotic variables (Table 1), a significant positive correlation was only observed with maximum temperature (r=0.346; p<0.05). In contrast, the correlation between the proportion of P. subtilis biomass and the abiotic variables (Table 1) was statistically insignificant, except for a marginal negative correlation with pH (r=-0.230; p>0.10). The biomass of P. schmitti was significantly negatively correlated with the percentage of P. subtilis biomass (r = -0.247; p<0.05).

Table 1
Correlation coefficients between the proportions of P. schmitti and P. subtilis biomass and abiotic factors (pH, salinity, and temperature). *Corresponds to significant correlations (p<0.05); †Corresponds to marginal significance (0.05≤p<0.10).

Species	Mean pH	Mean salinity	Min. Temperature	Mean Temperature	Max. Temperature
P. schmitti	-0.185 (p=0.286)	-0.033 (p=0.852)	0.207 (p=0.234)	0.270 (p=0.117)	0.346 (p=0.041)*
P. subtilis	-0.230 (p=0.053)†	0.136 (p=0.250)	-0.022 (p=0.853)	0.000 (p=0.999)	0.005 (p=0.966)

The Cox-Stuart test indicated a random behavior of the percentage series of biomass of P. schmitti (T=8.00; p-value=1.00) and P. subtilis (T=12.00; p-value=0.14). Using binary segmentation, two points of behavior change of the P. schmitti series were identified: in November 2013 and December 2016 (Figure 3). For the P. subtilis series, two points of change were also identified: in October 2016 and January 2017 (Figure 3).

Figure 3
Detection of change points using binary segmentation for the percentage of biomass for P. schmitti and P. subtilis on the coast of the state of Rio Grande do Norte, northeastern Brazil, from 2013 to 2018.

POPULATIONAL STRUCTURE OF PENAEUS SCHMITTI

From 2013 to 2018, 2,665 specimens of P. schmitti were collected and analyzed, of which 1,228 were females and 1,437 were males. For the entire period, the sex ratio showed a higher occurrence of males (F:M = 0.85:1; p<0.01; Table 2). When the years were analyzed individually, the sex ratio was approximately balanced between females and males, except in 2016, when males were significantly more abundant (0.74:1; p<0.01; Table 2).

Table 2
Proportion of females and males of P. schmitti and P. subtilis captured off the municipality of Baía Formosa in the state of Rio Grande do Norte (northeastern Brazil) from 2013 to 2018. nF, sample size for females; nM, sample size for males; χ², calculated chi-squared value; ^∗Corresponds to the statistically significant difference (χ²>3.84; α=0.05). Data for P. subtilis are not available for 2013 and 2015.

	Year	nF	nM	F:M	χ²	p
P. schmitti	2013	429	487	0.88	3.67	0.05
	2014	327	369	0.89	2.53	0.11
	2015	45	58	0.78	1.64	0.20
	2016	271	364	0.74	13.62	<0.01*
	2017	74	82	0.90	0.41	0.52
	2018	82	77	1.06	0.16	0.69
	All years	1228	1437	0.85	16.40	<0.01*
P. subtilis	2013	-	-	-	-	-
	2014	28	6	4.67	14.23	<0.01*
	2015	-	-	-	-	-
	2016	407	343	1.19	5.46	0.02*
	2017	298	165	1.81	38.20	<0.01*
	2018	90	67	1.34	3.37	0.07
	All years	823	581	1.42	41.71	<0.01*

The frequency distribution of CL of P. schmitti was unimodal for both females and males. CL of females ranged from 5.70 to 43.20 mm (24.55±5.21 mm) (Figure 4A) and that of males, from 8.10 to 36.70 mm (23.39±3.33 mm) (Figure 4C). Considering all years, a statistically significant difference was observed in mean CL between females and males, with females being larger than males (t=6.74; p<0.001; Table 3). When analyzed by year, a significant difference in mean CL between females and males was observed in all years except 2018 (Table 3).

Figure 4
Frequency distribution of carapace length for P. schmitti and P. subtilis on the coast of the state of Rio Grande do Norte, northeastern Brazil, from 2013 to 2018. A, C = females and males of P. schmitti, respectively. B, D = females and males of P. subtilis, respectively.

Table 3
Biological data for P. schmitti and P. subtilis captured off the municipality of Baía Formosa, state of Rio Grande do Norte (northeastern Brazil) from 2013 to 2018. n, sample size; CL, carapace length; TW, total weight; t, Student’s t-test value; ^∗Corresponds to statistically significant differences between sexes (α = 0.05).

P. schmitti
Year	Sex	n	CL (mm)		t; p	TW (g)		t; p
			Min-Max	Mean±SD		Min-Max	Mean±SD
2013	F	429	10.50-39.40	24.08±4.52	2.97; <0.010*	1.12-40.03	12.89±6.09	1.82; 0.070
	M	487	12.00-36.70	23.31±3.23		1.66-32.28	12.24±4.30
2014	F	327	7.40-41.80	24.73±5.98	2.60*; <0.010*	1.78-47.32	14.86±8.43	3.16; <0.010*
	M	369	8.10-34.90	23.73±3.82		1.22-28.61	13.18±4.84
2015	F	45	15.90-31.40	24.22±2.71	2.68; <0.010 *	3.60-23.85	12.99±3.89	1.65; 0.103
	M	58	13.90-28.30	22.78±2.72		2.81-19.90	11.79±3.41
2016	F	271	5.70-40.00	25.18±5.38	4.85; <0.001*	1.83-47.45	15.18±7.74	4.03; <0.001*
	M	364	10.80-32.30	23.40±3.27		3.23-28.24	13.05±4.55
2017	F	74	13.80-43.20	25.23±6.46	2.49; 0.014*	3.14-54.10	16.52±11.34	2.64; <0.010*
	M	82	14.60-33.20	12.10±2.81		3.90-32.43	12.84±4.19
2018	F	82	13.19-39.20	23.78±4.27	1.67; 0.097	2.27-42.88	13.32±6.74	2.06; 0.042*
	M	77	17.40-29.98	22.86±2.45		4.90-22.72	11.59±3.44
All years	F	1228	5.70-43.20	24.55±5.21	6.74; <0.001*	1.12-54.1	14.16±7.59	6.06; <0.001*
	M	1437	8.10-36.70	23.39±3.33		1.22-32.43	12.67±4.45
P. subtilis
All years	F	823	5.30-29.71	17.05±3.69	11.17; <0.001*	0.46-20.75	4.97±3.08	10.81; <0.001*
	M	581	8.30-25.42	15.18±2.59		0.43-13.09	3.60±1.76

TW ranged from 1.12 to 54.10 g (14.16±7.59 g) for females of P. schmitti and from 1.22 to 32.43 g for males (12.67±4.45 g). Considering all years together, a statistically significant difference in the mean of TW was observed between females and males, with females weighing more than males (t=6.06; p<0.001; Table 3). When analyzed by year, significant differences in mean TW between females and males were found in all years except 2013 and 2015 (Table 3).

For all years combined, the weight-length relationships (Figure 5) differed between P. schmitti females (TW=0.0040CL^2.5229; r²=0.948; n=1,218; Figure 5A) and males (TW=0.0021CL^2.7444; r²=0.945; n=1,429; Figure 5C) (ANCOVA; F=77.23; p<0.001; Table 4). The ANOVA results indicated a significant relationship between TW and CL for P. schmitti (p<0.05; Table 4) for all analyzed years. Analyzing year by year, these relationships only showed a statistically significant difference between sexes in 2014 and 2016 (ANCOVA; p<0.05; Table 4). Most years showed a negative allometry pattern (b<3) for both sexes (except for females in 2015 and for males in 2018; Table 4). The relationship between log(a) and b in the weight-length equations for P. schmitti showed an annual variation in these parameters for both sexes (Figure 6).

Figure 5
Relationship between total weight and carapace length for P. schmitti and P. subtilis on the coast of the state of Rio Grande do Norte, northeastern Brazil, from 2013 to 2018. A, C = females and males of P. schmitti, respectively. B, D = females and males of P. subtilis, respectively.

Table 4
Weight-length relationships for females and males of P. schmitti and P. subtilis captured off Baía Formosa, state of Rio Grande do Norte (northeastern Brazil), from 2013 to 2018. a and b are parameters of the linearized potential regression (TW = a CL^b); r², coefficient of determination; CI, confidence interval; F_ANOVA, F-test value for analysis of variance; t, Student’s t-test value; A, allometry: +, positive; -, negative; and =, isometric; F_ANCOVA, F-test value for analysis of covariance; ^∗Corresponds to a statistically significant difference (α = 0.05).

P. schmitti
Year	Sex	n	log a (CI 95%)	b (CI 95%)	r²	FANOVA	t; p	A	FANCOVA; p
2013	F	427	-6.0168(-6.1874- -5.8463)	2.6730 (2.6191-2.7268)	0.957	9521.2*	11.9; <0.001	-	4.2; 0.414
	M	486	-6.1975(-6.3476--6.0473)	2.7494 (2.7016-2.7972)	0.963	12775.9*	10.3; <0.001	-
2014	F	327	-4.7978(-5.0231- -4.5724)	2.3055 (2.2347-2.3762)	0.927	4113.6*	19.3; <0.001	-	65.9; <0.001*
	M	365	-6.0846(-6.2684- -5.9008)	2.7177 (2.6595-2.7758)	0.959	8440.4*	9.5; <0.001	-
2015	F	45	-6.4197(-7.2647- -5.5746)	2.8085 (2.5430-3.0740)	0.914	455.0*	1.4; 0.153	=	0.03; 0.873
	M	58	-6.2666(-6.8558- -5.6775)	2.7831 (2.5943-2.9719)	0.940	872.1*	2.3; 0.025	-
2016	F	263	-5.7912(-5.9387- -5.6436)	2.6101 (2.5642-2.6560)	0.980	12540.7*	16.7; <0.001	-	13.3; <0.001*
	M	362	-6.2443(-6.4992- -5.9895)	2.7800 (2.6991-2.8609)	0.927	4562.0*	5.3; <0.001	-
2017	F	74	-5.7835(-6.1347- -5.4323)	2.6202 (2.5106-2.7297)	0.969	2274.2*	6.9; <0.001	-	0.02; 0.889
	M	82	-5.7779(-6.5074- -5.0485)	2.6377 (2.4053-2.8701)	0.864	510.2*	3.1; 0.002	-
2018	F	82	-6.1507(-6.4708- -5.8307)	2.7350 (2.6336-2.8363)	0.973	2883.8*	5.2; <0.001	-	1.3; 0.254
	M	76	-6.4961(-7.0383- -5.9538)	2.8532 (2.6795-3.0269)	0.935	1071.3*	1.7; 0.096	=
All years	F	1218	-5.5116(-5.6178- -5.4054)	2.5229 (2.4895-2.5562)	0.948	22044.0*	28.1; <0.001	-	77.2; <0.001*
	M	1429	-6.1593(-6.2678- -6.0509)	2.7444 (2.7100-2.7789)	0.945	24387.0*	4.5; <0.001	-
P. subtilis
All years	F	821	-5.8633(-5.9981- -5.7285)	2.5999 (2.5521-2.6476)	0.933	11409.0*	16.4; <0.001	-	0.9; 0.354
	M	580	-5.9693(-6.1641- -5.7745)	2.6405 (2.5686-2.7124)	0.900	5208.0*	9.8; <0.001	-

Figure 6
Relationship between b and log(a) from the weight-length equation for P. schmitti on the coast of the state of Rio Grande do Norte, northeastern Brazil, from 2013 to 2018. The left panel shows the dispersion of the parameters log(a) and b for males (blue triangles) and females (red circles) across years, illustrating their inverse relationship and interannual variation. The right panel illustrates the distribution of b values for each sex, indicating that males tend to show slightly higher coefficients than females.

POPULATIONAL STRUCTURE OF PENAEUS SUBTILIS

A total of 1,404 specimens of P. subtilis were collected and analyzed from 2014 to 2018, of which 823 were females and 581 were males (Table 2). Due to the reduced number of specimens in some years, the weight-length relationship and size-related analyses for this species were performed using data pooled across all years, whereas sex ratio was analyzed separately by year whenever the sample size was sufficient. For the entire period, sex ratio showed a higher occurrence of females of P. subtilis (F:M = 1.42:1; p<0.01; Table 2). When the years were analyzed individually, females were significantly more abundant in 2014 (4.67:1; p<0.01), 2016 (1.19:1; p=0.02), and 2017 (1.81:1; p<0.01), whereas the sex ratio remained approximately balanced in 2018 (1.34:1; p=0.07; Table 2).

The CL of P. subtilis females ranged from 5.30 to 29.71 mm (17.05±3.69 mm) (Figure 4B) and that of males, from 8.30 to 25.42 mm (15.18±2.59 mm) (Figure 4D), with a statistically significant difference between the mean of CL of males and females, with females being larger than males (t=11.17; p<0.001; Table 3; Figure 4). The TW of females ranged from 0.46 to 20.75 g (4.97±3.08 g) whereas that of males, from 0.43 to 13.09 g (3.60±1.76 g), with a statistically significant difference between the mean of TW of males and females, with females being heavier (t=10.81; p<0.001; Table 3).

The weight-length relationship did not differ between females (TW = 0.0028 CL^2.5999; r² = 0.933; n = 821; Figure 5B) and males (TW=0.0026 CL^2.6405; r²=0.900; n=580; Figure 5D) of P. subtilis (ANCOVA; F=0.86; p=0.35; Table 4). The ANOVA results indicated a significant relationship between TW and CL for P. subtilis (p<0.05; Table 4). The weight-length relationship showed a negative allometry pattern (b<3) for both sexes (Table 4).

DISCUSSION

This study provided, for the first time, an integrated analysis of the catch composition and populational parameters of P. schmitti and P. subtilis along the coast of Rio Grande do Norte, northeastern Brazil. Although X. kroyeri dominated the shrimp biomass throughout most of the sampling period (Figure 2A), the proportion among the three species changed during the sampling period. In fact, a temporal shift was detected between P. schmitti and P. subtilis, with a negative correlation in their proportions of biomass (Figure 3). These species differed in sex ratio, magnitude of the size-related sexual dimorphism, and weight-length relationships, indicating distinct demographic structures and potentially different ecological strategies. The high proportion of fish bycatch further highlights the ecological implications of shrimp trawling in the region (Figure 2B). Together, these findings provide important biological and ecological information to support regional fisheries management under changing environmental conditions.

Xiphopenaeus kroyeri was the most frequently caught species in experimental trawls in Rio Grande do Norte: over 50% of total shrimp biomass in most sampling months (Figure 2A). This predominance can be attributed to characteristics such as its broad tolerance to salinity and temperature variations, continuous reproductive cycle, and migratory movements between shallow coastal areas and adjacent deeper zones (Dall et al., 1990; Sanchez, 1997; Costa et al., 2007). Due to its high abundance, several authors highlight the dominance of this genus in coastal areas characterized by shallow waters, well-oxygenated environments, and fine or sandy sediments (Fransozo et al., 2002; Silva et al., 2014; Marques et al., 2025). As proposed by McNaughton and Wolf (1970), dominance can be interpreted in two ways: dominant species may be generalists (well-adapted to a wide range of environmental conditions) or specialists (associated with certain habitat features). The distribution pattern of X. kroyeri in previous studies suggests a predominantly generalist behavior as this species occurs in various coastal environments and tolerates different substrate types (Fransozo et al., 2002; Silva et al., 2014; Marques et al., 2025). However, its frequent occurrence in areas with fine sediments indicates a certain preference for these habitats, in which burying behavior and morphological adaptations (Moraes et al., 2018) provide protection against predators and facilitate access to organic matter (Dall et al., 1990; Freire et al., 2011; Fransozo et al., 2012; Furlan et al., 2013).

The lower proportion of X. kroyeri in some months (May and November 2016, as well as in January 2017) may be related to the entry of recruits of other species into the fishery, such as P. schmitti and P. subtilis (Figure 2A). Penaeus schmitti has a type II life cycle, with adults living offshore and their juveniles initially inhabiting estuaries (Dall et al., 1990; Capparelli et al., 2012; Bauer, 2023). Then, they migrate to coastal areas due to reduced physiological tolerance, mainly to salinity (Barioto et al., 2017; Rocha-Gomes et al., 2024). Thus, the shrimps captured in our study are probably juveniles seeking protected areas for their development until they reach adulthood. Penaeus subtilis has a life cycle resembling that of P. schmitti (Dall et al., 1990; Bauer, 2023), and our study may have also targeted juveniles of this species. This fact can be corroborated by the mean CL values of 17.05 and 15.18 mm for females and males, respectively (Figure 4; Table 3). Reis-Júnior et al. (2023) estimated the size at first maturity for this species in the state of Sergipe (19.0 mm for females and 15.0 mm for males), corroborating this fact. Furthermore, Miazaki et al. (2018) consider that individuals of P. schmitti with CL below 25.0 mm may be juveniles or subadults. Such hypotheses can be corroborated in future studies on the reproduction and recruitment of both species off the state of Rio Grande do Norte. In fact, in a recent survey of a coastal lagoon in a sea-estuary interface on Rio Grande do Norte coast by Rocha-Gomes et al. (2024), Penaeus juveniles were the most abundant taxon on a seasonal basis (January to May), indicating a temporary use of that area for nursery and shelter against potential predators. Further studies will also be needed to assess the impacts of fishing on juveniles of these two species.

This study found a negative correlation between the proportion biomass of P. schmitti and P. subtilis (Figure 3). Such variations in abundance can be explained by environmental variables and by physiological responses associated with reproductive behavior (Castilho et al., 2008). In northern Brazil, Aragão et al. (2021) found that P. subtilis individuals are recruited from September to January, whereas Stoner (1988) observed that recruitment occurs from June to November in Puerto Rico, relating it to the rainy season. The information from these authors serves as a basis for future studies in the region relating biological recruitment events to rainfall. Freire et al. (2020) had noted a predominance of P. subtilis over P. schmitti in waters off the coast of Sergipe from 2015 to 2016, although they were unable to assess possible temporal changes in this proportion since no catches are recorded in statistical bulletins by species; instead, catches are recorded by common name associated with size, i.e., ‘espigão’ (Brazilian term for smaller specimens), ‘escolha’ (medium size), and ‘pistola’ (large size). The temporal shift detected by change-point analysis (Figure 3) likely reflects ecological processes influencing species turnover in the fishery, reinforcing the need for the continuous monitoring of environmental and biological drivers. In times of climate change, these compositional changes in fisheries must be better understood (Cheung et al., 2010).

Our results show a clear trend that bycatch represents most of the biomass in all trawling from June 2017 to May 2018, ranging from 60 to 90% of the all-captured biomass (Figure 2B). In several shrimp fleets from around the world, bycatch is discarded due to its small size or lack of commercial value. Therefore, shrimp fishing strongly impacts these populations (Alverson et al., 1994). This also occurs in Brazil (see, e.g., Pina and Chaves, 2009; Silva-Júnior et al., 2019). The high proportion of bycatch from trawling highlights the importance of more selective fishing gear to reduce the capture of non-target species and mitigate ecological impacts (Madhu, 2018). Understanding the complexity of shrimp catch dynamics and the importance of the bycatch from trawling, its variations and underlying causes, is crucial for the sustainable management of marine resources and for minimizing the environmental impacts of fishing (Silva-Junior et al., 2013). Future research should focus on identifying the specific factors that influence these variations and on developing fishing practices that can increase selectivity and reduce the catch of non-targeted species (see, e.g., Nascimento, 2018). Additionally, the use of exclusion devices that minimize economic losses for the shrimp fleet should be encouraged or mandated.

The population structure of P. schmitti and P. subtilis showed marked differences, with a higher abundance of males and females, respectively. According to Grabowski et al. (2014), “male-biased” X. kroyeri populations may be associated with migration patterns of females offshore during reproductive periods, whereas “female-biased” situations may be explained by the high mortality of males. Such behavioral characteristics were also observed by Gomes et al. (2013) while evaluating congeneric species, Penaeus brasiliensis Latreille, 1817 and Penaeus paulensis Pérez Farfante, 1967. These authors suggest that this strategy aims at ensuring reproduction, with males reaching adulthood before females and migrating to deeper areas. Reis-Júnior et al. (2023) hypothesized that females may be more susceptible to fishing gear for being larger and are therefore more represented in catches. The “male-biased” condition for P. schmitti can be explained by the physiological and behavioral changes of individuals in this population in addition to differential growth. Barioto et al. (2017) and Rocha-Gomes et al. (2024) commented that this species, which inhabits mangroves in its post-larval stage, migrates to coastal areas due to its reduced tolerance to water with low salinity. As a result, juveniles or subadult males can reach this condition more quickly and be captured by fishing more frequently. This suggests that the “male-biased” pattern in P. schmitti may be partly driven by the spatial and temporal overlap between fishing grounds and areas predominantly occupied by juveniles or subadults. Such overlap increases the probability of males being caught before reaching full maturity, potentially altering the natural sex ratio of the population. In contrast, Santos et al. (2020) observed a sex ratio compatible with Fisher’s 1:1 sex allocation theory (Fisher, 1930), although they recognized that the pattern for many penaeids is “female-biased.” This divergence reinforces that local environmental conditions, fishing pressure, and ontogenetic migrations can strongly influence the sex composition of shrimp populations, leading to temporary deviations from the expected theoretical equilibrium under natural conditions.

According to Dall et al. (1990), the growth of penaeids is a discontinuous process regulated by their molting cycle, which, in turn, can be short with rapid growth or long with slower growth. These variations can be influenced by sex, development stage (Dall et al., 1990), and environmental factors such as food availability, water quality, pH, salinity (Lemos et al., 2001), and temperature (Wyban et al., 1995; López-Martínez et al., 2003). This study observed a significant positive correlation between P. schmitti and maximum temperature and a negative correlation between P. subtilis and mean pH (Table 1). These results suggest that P. schmitti may benefit from higher temperatures, which can accelerate metabolic activity and molting frequency, increasing growth and catchability in warmer conditions (see, e.g., Vijayan and Diwan, 1995; Kienzle and Sterling, 2017). Conversely, the negative correlation of P. subtilis with mean pH indicates a possible sensitivity to acidic environments, in which fluctuations in pH may impair osmoregulation and reduce survival or recruitment success (see Allan and Maguire, 1992; Vijayan and Diwan, 1995; McLuckie et al., 2021). The observed decrease in the biomass proportion of P. schmitti accompanied by an increase in P. subtilis may therefore reflect species-specific physiological tolerances and temporal shifts in environmental suitability, potentially influenced by seasonal changes or differences in habitat preference. A detailed analysis of the abiotic factors of the region, including rainfall, and of the more recent population structure is recommended to test the hypothesis of species replacement. Castilho et al. (2008) pointed out that penaeids of different species may show different correlations with environmental factors, and that low correlations may mean that species respond differently to environmental variations, with no generalized response at the community level. Thus, other factors, such as intraspecific migration patterns, may also influence the observed abundance patterns (Pantaleão et al., 2016).

In both species in this study, females reached a larger size than males (Figure 4; Table 3). As observed by Boschi (1969), sexual dimorphism in size is a distinctive characteristic of penaeids, with females tending to larger dimensions than males. According to Gab-Alla et al. (1990), the larger size of the cephalothorax and abdomen of females may be related to the greater development of the ovaries, resulting in greater oocyte production and fertility. The same pattern was observed by other authors (e.g., Santos et al., 2020; Rosa et al., 2021; Reis-Júnior et al., 2023).

The negative allometry in both evaluated species can be interpreted as the way in which weight increases with shrimp length, with weight increasing at a proportionally lower rate (Figure 5; Table 4). This observed condition suggests that, as body size increases, growth rate and survival may be compromised due to selective pressures, such as predation and competition for resources. This dynamic implies that energy allocation must be strategically balanced between somatic growth and energy storage to maximize survival in challenging environments (Post and Parkinson, 2001). Similar values were also observed by other researchers for penaeids: X. kroyeri (Lopes et al., 2014; Reis-Júnior et al., 2019) and P. brasiliensis and P. paulensis (Mello, 1973; Branco and Verani, 1998; Albertoni et al., 2003). The ‘b’ value of the weight-length relationship of P. schmitti (Figure 6) reflects annual changes in the biologic characteristics of the population. Similar results were found seasonally for X. kroyeri in the state of Sergipe (see Reis-Júnior et al., 2019). The slightly higher b values in males suggest that they may show a proportionally faster weight increase relative to their length than females, possibly linked to differences in energy allocation or growth strategies between sexes, a pattern also described for other penaeids (e.g., Grabowski et al., 2014). Such interannual variation in both parameters may also reflect environmental influences, such as temperature and food availability, affecting growth dynamics.

CONCLUSION

Shrimp trawling off Baía Formosa (Rio Grande do Norte) targets three species of penaeids: X. kroyeri, with the largest biomass, followed by P. schmitti and P. subtilis. However, it also captures a large biomass of fishes. Changes in the proportion of the biomass of P. schmitti and P. subtilis have been observed over time, with the former decreasing and the latter increasing. Biological parameters suggest population differences in both species, such as sex ratio, sexual dimorphism in size, and biometric relationships. Moreover, some annual variations were observed for P. schmitti (2013-2018). The findings of this study offer relevant insights for regional fishery management by showing how environmental variability influences the relative biomass of P. schmitti and P. subtilis. Moreover, covering the gaps in biological information on these species is equally important in managing these resources. Understanding the biomass proportions of shrimp fisheries is essential for developing adaptive management measures, such as adjusting fishing periods or efforts according to environmental conditions that favor the predominance of one species over another. The observed temporal changes in species proportions may also reflect shifts in the ecosystem dynamics, reinforcing the importance of continuous monitoring to avoid overexploitation and to maintain ecological balance. Integrating biological and environmental information, as in this study, can therefore assist fisheries managers in implementing strategies to improve the sustainability of shrimp trawling in northeastern Brazil.

DATA AVAILABILITY STATEMENT

All data are available from the corresponding author upon reasonable request.

SUPPLEMENTARY MATERIAL

This article includes no supplementary materials.

ACKNOWLEDGMENTS

We would like to thank the National Council for Scientific and Technological Development - CNPq for the PIBIC/UFS scholarship granted to the first author and to anonymous reviewers for their valuable comments and corrections.

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• AI USE STATEMENT
  The authors declare that no generative artificial intelligence tools were used in preparing, writing, or editing this manuscript.
• FUNDING
  This work was funded by the Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPq through the following projects: CNPq-PPBio 2023-07/2023 - Linha 8: Rede Costeira Marinha - Proc. 442421/2023-0, Chamada CNPq/MPA Nº 42/2012 - Proc. 407046/2012-7, Bolsa de produtividade CNPq 313626/2018-9, and Projeto Cammarada MPA/CNPq 446224/2024-3.

Edited by

• Editor:
  Rubens Lopes

Publication Dates

• Publication in this collection
  17 July 2026
• Date of issue
  2026

History

• Received
  14 Mar 2025
• Accepted
  22 Mar 2026