Maricell Armas1 , Hernán Ortega1, Aurea García-Vasquez2,3,†, Carmen García-Dávila2,3, Gladys Vargas2,3, Jesus Nuñez3,4, Jean-François Renno3,5 and Fabrice Duponchelle3,6
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Abstract
The doncella Pseudoplatystoma punctifer is an economically and ecologically important catfish in the Amazon basin. However, little is known about its age, growth and population dynamics parameters. This study aims to validate the formation of growth marks in vertebrae of individuals collected from two rivers systems of the Peruvian Amazon (Amazon-Marañón-Ucayali and Putumayo) and compare growth parameters using the von Bertalanffy growth function between sexes and systems. A total of 372 individuals from the Amazon-Marañón-Ucayali (AMU) system and 93 from the Putumayo River were analyzed. The formation of one growth ring per year was validated and the individual ages ranged from zero to nine years old. Females grew significantly larger than males in both systems. Both females and males grew significantly better in the AMU system than in the Putumayo River. Maximum observed length and size at maturity in the AMU system were lower than those reported in previous studies in the area, and together with an important proportion of juveniles in the catches, suggest that the species is heavily exploited. Further studies on the reproductive biology and population dynamics of the doncella are needed in order to implement management measures more in line with the current situation.
Keywords: Amazonas-Marañón-Ucayali, Catfish, Fisheries management, Putumayo, Vertebrae.
La doncella Pseudoplatystoma punctifer es un bagre de importancia económica y ecológica en la cuenca Amazonica. Pese a ello, poco se conoce acerca de parámetros de edad, crecimiento y dinámica poblacional. Este estudio tuvo como objetivo validar la formación de marcas de crecimiento en vértebras de individuos colectados en dos sistemas fluviales de la Amazonia Peruana (Amazonas-Marañón-Ucayali y Putumayo) y comparar los parámetros de crecimiento usando la función de von Bertalanffy entre sexos y sistemas. Fueron analizados 372 individuos del sistema Amazonas-Marañón-Ucayali (AMU) y 93 del Putumayo. Se validó la formación de un anillo de crecimiento por año, la edad osciló entre cero y nueve años. Las hembras fueron significativamente más grandes que los machos en ambos sistemas. Para ambos sexos el crecimiento fue significativamente mayor en el sistema AMU que en el Putumayo. Las máximas tallas y edades de primera madurez observadas en el sistema AMU fueron menores a las reportadas en estudios previos en el área, y junto con un considerable porcentaje de juveniles presentes en las capturas, se sugiere que la especie está siendo fuertemente explotada. Son necesarios estudios de biología reproductiva y dinámica poblacional de doncella para implementar medidas de manejo acordes a la situación actual.
Palabras chave: Amazonas-Marañón-Ucayali, Bagre, Manejo de pesquerías, Putumayo, Vértebra.
Introduction
The Amazon basin is home to the highest diversity of freshwater fish species on earth (Jézéquel et al., 2020). The order Siluriformes, fish with plates or bare skin, is one of the most diverse and widely distributed groups in the Amazon basin (Burgess, 1989). It is also one of the most exploited by fishing activity (Garcia et al., 2009; Barletta et al., 2016; Doria et al., 2018; García-Dávila et al., 2018). Within the order, the family Pimelodidae hosts many large and commercially important catfishes, such as the species Pseudoplatystoma punctifer (Castelnau, 1855), known as “doncella” in Peru and “surubim” in Brazil. The doncella has a wide distribution in the Amazon, being found in countries such as Peru, Colombia, Bolivia, Ecuador and Brazil, although it is rare or absent at the mouth of the Amazon. It inhabits the headwaters of rivers and is also frequent in areas protected by trunks, branches and vegetation of lotic environments (Reid, 1983; Loubens, Panfili, 2000). It has migratory habits and plays an important ecological role as an efficient predator (Barthem, Goulding, 1997, 2007). The species was formerly known as P. fasciatum (Linnaeus, 1766) before Buitrago-Suárez, Burr (2007), in a systematic review based on morphological characters, decided that P. fasciatum was restricted to the Guyana shield basins and that the species distributed in the rest of the Amazon basin was P. punctifer. This segregation, however, was not supported by subsequent molecular analyses, that could not differentiate between P. fasciatum and P. punctifer (Torrico et al., 2009; Carvalho-Costa et al., 2011). Furthermore, more recent molecular analyses evidenced the existence of two clearly separated species within what Buitrago-Suárez, Burr (2007) described as P. punctifer: a species with the typical black-and-white striping pattern of P. fasciatum and another, less common one lacking the black stripes and having a distinct mouth shape that closely resembles what Castelnau had described as Platystoma punctifer in 1855 (García-Dávila et al., 2013). Although a systematic revision of these species is clearly called for, for the sake of homogeneity, we will keep referring to Pseudoplatystoma punctifer in the rest of the text while talking about the typical black-and white-striped species.
Despite the species’ wide distribution, economic and ecological importance, little is known about its population dynamics, reproduction or age and growth patterns. As for many others fish of commercial importance, fishing has become one of the main threats to the species (de Jesus, Kohler, 2004; Barletta et al., 2016; Castello, Macedo, 2016; Duponchelle et al., 2021). Owing to its large size (>1 m) and few intra-muscular spines, this species is one of the main components in the fisheries landings of the Amazon (Barthem, Goulding 1997, 2007; Garcia et al., 2009; Barletta et al., 2016; Doria et al., 2018; García-Dávila et al., 2018). Young stages are also marketed for ornamental purposes (Padilla-Pérez et al., 2001; García-Dávila et al., 2018, 2021). The doncella has been a major component of fisheries landings of the Peruvian Amazon since the early nineties (Garcia et al., 2009) and its extraction was 562 tons in 2019, representing 3.2% of the Amazonian fish landings (PRODUCE, 2020).
Age and growth studies are important tools for the interpretation of population dynamics in fish and provide the basis for establishing resource management strategies (Campana, Thorrold, 2001; Hutchinson, TenBrink, 2011). Counting growth marks on calcareous structures, such as otoliths, vertebrae or scales, is a widely used method for age estimation in fish and its effectiveness requires that the results are validated (Campana, 2001). In the Amazon basin, counting growth marks in calcareous structures has been successfully carried out in different species (e.g., Loubens, Panfili, 1992, 1997, 2001; Loubens, 2003; Cutrim, Batista, 2005; Silva, Stewart, 2006; Duponchelle et al., 2007; Pérez, Fabré, 2009; Duponchelle et al., 2012; Hauser et al., 2018), including the genus Pseudoplatystoma Bleeker, 1862 in the Mamoré River basin in Bolivia, where the formation of a single annual growth mark was validated using vertebrae (Loubens, Panfili, 2000). In the Peruvian Amazon, where the doncella is among the most commercially important species (Garcia et al., 2009), information regarding age and growth parameters of this species are lacking. The current fishing regulations impose a minimum size of capture for the entire Peruvian Amazon (Ministerial Resolution N° 147-2001-PE and Supreme Decree N° 015-2009-PRODUCE) without considering that, in widely distributed species such as the doncella, populations of the same species could have different growth rates, hence different size at maturity (Vazzoler, 1982) and might therefore require different management measures. Previous studies have reported a slower growth in populations of Osteoglossum bicirrhosum (Cuvier, 1829) (Duponchelle et al., 2012) and Prochilodus nigricans Spix & Agassiz, 1829 (Bonilla-Castillo et al., 2018) in the Putumayo River when compared to populations of the Amazon-Ucayali-Marañón system. The aim of this study was to validate the formation of growth marks in doncella vertebrae from two different river systems (Amazon-Marañón-Ucayali and Putumayo) of the Peruvian Amazon, and investigate the potential existence of age and growth differences between river systems, hypothesising that as for the previously mentioned species, P. punctifer would have a slower growth in the Putumayo River.
Material and methods
Fish sampling and study area. Vertebrae of the typical black-and-white-striped doncella were collected between July 2008 and July 2010 at landing sites in the Amazonas (Caballococha), Ucayali (Jenaro Herrera, Requena and Pucallpa), Marañón (Nauta) and Putumayo rivers (San Antonio del Estrecho) (Fig. 1). The Marañón and Ucayali are white-water rivers born in the Andean Piedmont in Perú and their confluence form the Amazonas River. These rivers carry suspended solids (both organic and inorganic) and rich nutrients from the Andes. Their network is characterized by meanders, oxbows, and streams, many of which flood annually during the rainy season (Hales, Petry, 2008). The Marañón River has a length of 1707 km (ANA, 2011), its average velocity on the lower portion is 1.65 m.s-1 with flow ranging between 7000 to 25000 m3.s-1 (IRD et al., 2011). The Ucayali River has a length of 2670 km, its average velocity is between 1.5 to 2.5 m.s-1 (MTC, 2005) with a flow ranging from 2700 to 20000 m3.s-1 in the lower portion (IRD et al., 2011). From the confluence of these two rivers in Peru to the Atlantic Ocean in Brazil, the Amazon River is approximately 3750 km long representing the largest river system on earth (Hales, Petry, 2008) with an average velocity of 1.48 m.s-1 and flow between 10000 to 46000 m3.s-1 in the Peruvian portion (IRD et al., 2011). In the estuary, the discharge is estimated at 209000 m3.s-1 (Guyot et al., 2007). The Putumayo River is one of the two major affluents of Colombia flowing into the Amazon River, with a length of 2000 km, of which ~1500 travels the Colombian, Ecuadorian and Peruvian territories (in high and median altitudes) whereas the last 450 km are in Brazil (González et al., 2006). It is also a white-water river and its origin is in the Andes mountains of Colombia. Due to its equatorial latitudinal position, the Putumayo River basin is a region with particularly abundant rainfall throughout the year (Salazar et al., 2006). The average velocity of the Putumayo River is between 0.5 to 1.0 m.s-1 with a flow ranging from 250 to 7000 m3.s-1 (IDEAM, 2004).
Fish vertebrae were acquired directly from known traders with whom previous agreement was made to ensure the geographic origin of the individuals. The collected individuals were measured at the landing sites to the nearest mm, recording standard length (LS), total length (LT), and body mass with a digital handheld scale of 20 kg capacity and 0.01 kg sensitivity. The stage of gonadal maturity was determined by direct observation according to the scale of Núñez, Duponchelle (2009). The first five vertebrae were extracted from each individual and taken to the facilities of the Quistococha Experimental Centre of the Peruvian Amazon Research Institute (IIAP) for processing. In addition, a collection was made in the Ucayali River (Pucallpa) in November 2017 to complete the size range of small individuals and improve data modelling. This material was processed in the Ichthyology Department of Museo de Historia Natural of Universidad Nacional Mayor de San Marcos (MHN-UNMSM). Specimens were deposited at the Ichthyological Collection of MHN-UNMSM under the catalog numbers: MUSM 46080, 50947, 69601–69604.
Vertebrae processing and analysis. The processing followed the guidelines of Loubens, Panfili (2000). The vertebrae were boiled in water until most of the adhering soft tissue was released and the remaining tissue was removed with a soft-bristled brush. They were then placed in an oven at 40 °C for approximately 48 hours until they were completely dry to be stored in individual packaging duly labelled. The vertebrae were observed in frontal section and with light reflected on a dark background with a Leica MZ16 stereoscopic microscope with a built-in camera connected to a computer, from which a photographic record was made. Each vertebrae was then cross-sectioned (transversal section) with a slow-speed electric cutter to confirm the readings on the corpus calcareum (Loubens, Panfili, 2000). The images obtained were analysed with the software AxioVision v4.8.
FIGURE 1| Map of sampling sites of Pseudoplatystoma punctifer in the Peruvian Amazon River systems. Sampling sites are symbolized by red dots.
Growth marks were identified by their formation around the centre of the vertebra, under reflected light, following Loubens, Panfili (2000): broad light bands (opaque zones) alternating with thin dark bands (hyaline rings) were observed. The set of a light band and a dark band corresponds to a growth ring, the distance between the light bands becoming shorter as they move away from the centre of the vertebra. Light, broad bands form during the fast growth stages of the fish, while dark, thin bands form during the slow growth stages; when fish are very old, the light and dark bands can become very thin, making it difficult to identify growth rings (Panfili et al., 2002). The identification of the growth marks was carried out independently by two separate observers, at a 90° angle in order to more reliably compare individual results. When the two independent lectures were in disagreement, the vertebrae were re-interpretated by the observers, this time together. When the disagreement remained, the vertebrae were discarded. All the interpretation were finally agreed by the two observers, so, there were no discarded vertebrae. Distance in mm, on a known scale, were taken from the centre of the vertebrae to each hyaline ring and to the edge or the vertebrae.
Given the relative proximity of the areas sampled in the Marañón, Ucayali and Amazon systems (Fig. 1), their similarity in hydrological dynamics, and considering the migratory habits of the species, vertebrae from these rivers were pooled for the analyses in order to obtain a better coverage of length for growth curves and of months for the validation process. We will there after refer to the Amazon, Marañón and Ucayali rivers as AMU system. Vertebrae from the Putumayo River were analysed independently.
Validation of ring formation and hydrological data. The period of growth ring formation was determined by the Relative Marginal Increment (RMI) method:
RMI = [(Rt – Rn) / (Rn – Rn-1)]x100
where Rt is the total radius of the vertebra, Rn is the distance from the core to the last ring (hyaline ring) and Rn-1 is the distance from the core to the penultimate ring (Haimovici, Reis, 1984; Fabré, Saint-Paul, 1988). The sudden significant decrease in monthly mean RMI values followed by a gradual increase in it was interpreted as the period of hyaline ring formation. The RMI values for each month during the entire collection period were averaged to obtain data for all possible months in both the AMU system and the Putumayo River.
Water levels were obtained from ORE-HYBAM (Observatoire régional, Hydrologie du bassin Amazonien) and SENAMHI (Servicio Nacional de Meteorología e Hidrología, Perú) from the Tamshiyacu station for the AMU system due to its location in an area where the three rivers converge, with hydrological data from years 2008–2010 with daily values average per month. For the Putumayo River, water levels were obtained from IDEAM (Instituto de Hidrología, Meteorología y Estudios Ambientales) with hydrological data from the El Estrecho station with daily values averaged per month from years 2008–2010.
Individual age in months was calculated by taking into account the month of capture, the number of growth rings and the month of birth (Panfili et al., 2002). The month of birth was considered to be the month with the highest proportion of breeding females: February in the AMU system (García et al., 2001; Deza-Taboada et al., 2005) and April in the Putumayo River (Camacho et al., 2006). The following formulae were applied:
- for individuals captured before the month of birth: E = (12 x A) + 12 + C – N
- for those captured after the month of birth: E = (12 x A) + C – N,
where E is the age of each individual in months, A is the number of growth rings, C is the month of capture and N is the month of birth.
Statistical Analyses. The growth parameters were calculated by the Von Bertalanffy Growth Function (VBGF) using a non-linear estimation (quasi-Newton method) according to the following equation:
Lt = L∞ (1 – e-K(t-t0))
where Lt is the length at age t, L∞ is the infinite length, K is the growth rate, t is the age of the fish at Lt, t0 is the theoretical age of the fish at length 0.
RMI mean monthly values were compared using one-way-ANOVA with Tukey’s post hoc test. A significant decrease followed by an increase in RMI values was interpreted as the formation of a seasonal translucent ring (Panfili et al., 2002).
Length at first maturity (L50, average length at which 50% of individuals are able to breed) was estimated by fitting the percentage of mature individuals, from stage 2 onwards using the maturity scale of Núñez, Duponchelle (2009), at 5 cm LS intervals to a logistic function, using non-linear regression, weighted by the number of individuals in each length class (Duponchelle, Panfili, 1998):
%MF = 1/[1+e(-ax(L-L50))]
where %MF is the percentage of mature individuals per standard length class, L is the central value of each length class, a is a constant and L50 is estimated by the model.
For comparison of length at maturity with previous studies in the Peruvian Amazon (in the discussion section), where the L50 is given in fork length (LF), values were converted using the following equation: LS = 0.9776*LF – 1.8379, R² = 0.9984, P<0.001 (Garcia Vasquez et al., unpublished data).
The age at first sexual maturity (A50, average age at which 50% of individuals are able to breed) was calculated form the VBGF as follows (Duponchelle et al., 2007):
A50 = {-ln[1-(L50/L∞)]K-1} + t0
where L50 is the size at first sexual maturity and L∞, K, and t0are parameters from the VBGF.
Growth curves were compared between sexes and geographical populations using the maximum likelihood test (Tomassone et al., 1993) and applying Kimura (1980) sum of squares. For k populations the maximum likelihood test (SML) was compared with the X2 test with 3 degrees of freedom (3 parameters):
SML = Σk i = nix[ln(SC2) – ln(SK2)]
where n is the number of individuals in the kthpopulation, SC2 is the residual variance of the overall model, SK2 is the residual variance of the k populations. The same test was used for comparisons of growth curves among sexes within a geographical population and between geographical population. Statistical modelling and analyses were performed with Statistica 12.5 software (StatSoft Inc.) (Weiß, 2007).
Results
Vertebrae were collected from 465 individuals of P. punctifer during the study period (19.5–92.5 cm LS): 372 from the AMU system and 93 from the Putumayo River (Tab. 1). In both systems females predominated between 40–60 cm LS (Figs. 2A, C) and males between 30–50 cm LS (Figs. 2B, D). All vertebrae were interpreted and included in the analyses for age and growth estimates.
TABLE 1 | Standard length and mass ranges, mean ± standard deviation (SD) and number (N) of Pseudoplatystoma punctifer females and males analyzed in AMU system and Putumayo River.
River system | Sex | N | Mean length ± SD (cm) | Length range (cm) | Mean mass ± SD (g) | Mass range (g) |
AMU | Females | 205 | 51.4 ± 17.5 | 21.0–92.5 | 2329 ± 2318 | 80–12000 |
Males | 167 | 45.1 ± 13.4 | 19.5–83.0 | 1417 ± 1278 | 80–7700 | |
Putumayo | Females | 49 | 50.8 ± 12.2 | 23.5–74.0 | 1715 ± 1118 | 120–4990 |
Males | 44 | 45.7 ± 8.8 | 23.5–58.0 | 1119 ± 532 | 150–2240 |
FIGURE 2| Standard length frequency distributions of Pseudoplatystoma punctifer females (left) and males (right) in the A–B. AMU system and C–D. Putumayo River.
Interpretation of growth rings and validation. Single (a dark band), double (two dark bands close together) and multiple (several dark bands close together) hyaline rings were identified in the vertebrae of P. punctifer from the Peruvian Amazon (Figs. 3A–B). Double or multiple rings were occasionally observed only in the first growth marks and occurred before the single rings. In some cases, in the frontal view of the vertebrae, similar but thinner and less intense bands were identified between the hyaline rings, making the identification of growth rings difficult. These marks, however, were differentiated from the hyaline rings in the transversal sections, where the difference in intensity between the two zones was more clearly distinguished; these less intense bands were interpreted as intermediate marks (Figs. 3C–D). Similarly, before the formation of the first ring, very thin and less intense bands were identified very close to the center of the vertebrae and were easily differentiated from the hyaline rings in the transversal section; these bands were interpreted as pre-marks (Figs. 3E–F).
In the AMU system, the first growth ring formed on mean ± SD of 5.34 ± 0.807 mm from the core of the vertebra, the second at 8.75 ± 1.131 mm, the third at 11.55 ± 1.506 mm with a trend of increasing standard deviation as growth rings increased (Fig. 4A). In the Putumayo River the first growth ring formed at 5.01 ± 0.785 mm, the second at 8.44 ± 1.179 mm, the third at 10.77 ± 1.930 mm with little variation in standard deviation thereafter as growth rings increased (Fig. 4B).
FIGURE 3| Pseudoplatystoma punctifer vertebrae showing A–B. Five growth rings: the first one is multiple, the second one double and the third, fourth and fifth are simple, C–D. Two growth rings and E–F. One growth ring. Vertebrae center (ctr), hyaline rings (red lines), intermediate mark (i), pre mark (p). Left images: vertebrae frontal view. Right images: vertebrae cross section view with the confirmation of the rings on the corpus calcareum.
In the AMU system, RMI (carried out on 217 individuals) significantly varied among months (one-way ANOVA, F9,207 = 7.45, P<0.001) (details describe in Tab. S1) with lowest mean monthly value (17.28 ± 8.31%, mean ± SD) observed in September, after a high value in August (59.70 ± 25.26%), this lower value coinciding with the lowest water level (Fig. 5A). In the Putumayo River, the RMI (carried out on 69 individuals) also significantly varied among months (one-way ANOVA, F6,62 = 14.32, P<0.001) (details described in Tab. S2) with lowest mean monthly value occurred in November (9.65 ± 3.12%) after a high value in October (41.01 ± 16.58%), also coinciding with a period of low water level (Fig. 5B). In both cases, although samples could not be obtained at some months, the sudden significant drop in monthly mean RMI values (Tabs. S1 and S2) followed by gradually rising values occurred only once over an annual cycle, suggesting the formation of a single hyaline ring (dark band) and thus the formation of one growth ring per year. The broad light bands correspond to fast growth zones related to high metabolic rates and form during the high-water period, while the narrow dark bands correspond to slow growth zones and are related to low metabolic rates that form during the low water period. The formation of the slow-growth (dark) bands occurred in a slightly shorter time than the fast-growth (clear) bands during an annual cycle in both groups (Fig. 5).
FIGURE 4| Mean and standard deviation (SD) of each growth ring radius in vertebrae of Pseudoplatystoma punctifer from the A. AMU system and B. Putumayo River.
Growth and age. In both river systems, individuals below 4 years old and between 20.0 and 60.0 cm LS predominated, with very few specimens older than 8.0 years and/or larger than 80.0 cm LS (Fig. 6). The largest and oldest individuals were captured in the AMU system: the oldest individual was a female of 9.4 years and 91.1 cm LS; while the largest individuals were two females, both of 92.5 cm LS and 6.3 and 8.0 years old (Fig. 6A). In the Putumayo River, the largest and oldest individuals were also females of 74.0 and 72.0 cm LS and 8.2 and 6.3 years old, respectively (Fig. 6B). In contrast with the situation observed in the Putumayo River, the growth curves in the AMU system did not reach the asymptote, despite a larger sample size.
FIGURE 5| Mean monthly relative marginal increment (RMI ± SD) of Pseudoplatystoma punctifer vertebrae in relation to the hydrological cycle in the A. AMU system and B. Putumayo River. The illustrated hydrological cycles represent the average monthly values from the period 2008–2010.
The growth parameters estimated with the von Bertalanffy function are presented in Tab. 2. As observed in Fig. 6, after two or three years old, females had a significantly better growth than males in both the AMU system (SML = 8.919, P<0.05) and the Putumayo River (SML = 9.317, P<0.05).
FIGURE 6| Von Bertalanffy growth curves for Pseudoplatystoma punctifer females (pink triangles) and males (blue circles) in the A. AMU system and B. Putumayo River.
Growth was very similar during the first two to three years in the AMU system and in the Putumayo River for both females and males, then it progressively started to diverge. Overall, fish from the AMU system had largest length-at-age than fish from the Putumayo River, hence a better growth (Fig. 6; Tab. 3). The difference was significant for both females (SML = 31.773, P<0.0125) and males (SML = 25.978, P<0.0125): it reached almost 20.0 cm for females and 27.0 cm for males at 9.0 years old (the largest observed age in our sampling, Tab. 3).
TABLE 2 | Von Bertalanffy growth parameters for Pseudoplatystoma punctifer females and males in the AMU system and Putumayo River.
River system | L∞ (cm) | K | t0 | |||
Females | Males | Females | Males | Females | Males | |
AMU | 97.3 | 99.5 | 0.20 | 0.16 | -1.23 | -1.59 |
Putumayo | 68.1 | 55.3 | 0.38 | 0.71 | -0.97 | -0.64 |
TABLE 3 | Standard length-at-age for females and males of Pseudoplatystoma punctifer in the AMU system and Putumayo River.
Age
(years) | Females
length-at-age (cm) | Males
length-at-age (cm) | ||
AMU | Putumayo | AMU | Putumayo | |
1 | 35.3 | 35.8 | 34.4 | 38.2 |
2 | 46.6 | 46.0 | 44.2 | 46.9 |
3 | 55.9 | 52.9 | 52.6 | 51.2 |
4 | 63.5 | 57.7 | 59.7 | 53.3 |
5 | 69.6 | 61.0 | 65.7 | 54.3 |
6 | 74.7 | 63.2 | 70.8 | 54.8 |
7 | 78.8 | 64.7 | 75.1 | 55.0 |
8 | 82.2 | 65.8 | 78.8 | 55.2 |
9 | 85.0 | 66.5 | 81.9 | 55.2 |
10 | 87.2 | 67.0 | 84.6 | 55.3 |
Sexual maturation. In the AMU system, females were slightly larger (49.5 ± 9.2 cm SD vs. 41.0 ± 9.9 cm) and older (2.4 vs. 1.7 years old) at sexual maturity than males (Figs. 7 A, B), although differences were not statistically significant (t = 0.63, P = 0.53). The same was observed in the Putumayo River: 42.0 ± 0.2 cm at 1.6 years old for females and 39.0 ± 0.2 cm at 1.1 years old for males (Figs. 7C, D). Owing to the better growth of fishes from the AMU system, both females and males tended to reach maturity at larger sizes in the AMU system than in the Putumayo River, although the differences were not statistically significant (t = 0.82, P = 0.42 and t = 0.20, P = 0.84, for females and males, respectively).
The proportion of immature individuals sampled during the study was higher in the AMU system (50.5%) than in the Putumayo River (18.4%) for females, and for males: 40.2% and 22.7% for in the AMU system and Putumayo River, respectively (Tab. 4).
Discussion
The annual formation of growth marks in calcareous structures is composed of fast and slow growth zones, related to high and low metabolic rates (Panfili et al., 2002). The timing of mark formation usually depends on food availability, which is closely linked to the hydrological cycle of rivers in the Amazon basin (Junk et al., 1989). The seasonality of the water pulse or “flood pulse concept” is the main driver of the performance of organisms and patterns of ecological processes (Junk et al., 1989; Junk, Wantzen, 2004). The number of marks and period of formation of the fast and slow growth zones will depend on each species and their ecological patterns. Fish species usually form one yearly growth ring during the low water season in the western and southern parts of the Amazon basin, such as in the order Osteoglossiformes: Osteoglossum bicirrhosum in Peru (Duponchelle et al., 2012); Characiformes: Pygocentrus nattereri Kner, 1858 in Bolivia (Duponchelle et al., 2007), Prochilodus nigricans in Bolivia (Loubens, Panfili, 1992) and Ecuador (Silva, Stewart, 2006), Colossoma macropomum (Cuvier, 1816) (Loubens, Panfili, 1997) and Piaractus brachypomus (Cuvier, 1818) (Loubens, Panfili, 2001) in Bolivia; and Perciformes: Plagioscion squamosissimus (Heckel, 1840) in Bolivia (Loubens, 2003). On the other hand, many related species tend to form two growth marks per year in the Central Brazilian Amazonia such as the Siluriformes: Brachyplatystoma rousseauxii (Castelnau, 1855) (Hauser et al., 2018), Hypophthalmus marginatus Valenciennes, 1840 (Cutrim, Batista, 2005) and Calophysus macropterus (Lichtenstein, 1819) (Pérez, Fabré, 2009); and Osteoglossiformes: Arapaima sp. (Arantes et al., 2010).
Despite insufficient data at some months in our results, it was possible to determinate that the hyaline rings were formed during the dry season (lower water levels) and early wet season (onset of increased water levels due to increased rainfall intensity) in both, the AMU system and the Putumayo River, indicating the formation of one growth ring per year. These results are consistent with those of Loubens, Panfili (2000) in P. punctifer and P. tigrinum (Valenciennes, 1840) in the Bolivian Amazon: the zones of slow growth were formed during the dry season and the beginning of the rainy season, coinciding with difficulties in capturing prey and the beginning of the reproductive stage of the species. During the dry season the species would have greater difficulties in capturing prey due to high densities and competition with other predators such as larger catfish and/or dolphins (Barthem, Goulding, 1997; Loubens, Panfili, 2000). Low growth rates in fish due to competition and high densities among predators have been reported in Amazonian catfish (Nuñez et al., 2008; Hauser et al., 2018) and salmonids (Mazur et al., 1993; Taniguchi, Nakano, 2000; Vollestad, 2002; Puffer et al., 2017). The reproductive period of a species usually entails great metabolic expenditure for gonadal maturation at the expense of growth rate (Giesel, 1976; Panfili et al., 2002). The breeding period of P. punctifer starts in November in the AMU system (García et al., 2001; Deza-Taboada et al., 2005) and in March-April in the Putumayo River (Camacho et al., 2006), coinciding with the rising-water period in both systems. In both river systems, growth mark formation may therefore be related to competition – density factors and reproduction. The rapid growth period corresponds to the receding water period, when fish that were sheltered in flooded forests would return to the main river channels and become prey for predators that would strategically wait for capture during this process (Wantzen et al., 2002; McKey et al., 2016) as described for the doncella by Loubens, Panfili (2000). Using otoliths, a recent study on another species, P. metaense Buitrago-Suárez & Burr, 2007 in the Orinoco basin also revealed the formation of a single annual growth mark during the low water period (Pérez, Fabré, 2018). The presence of intermediate and pre-marks, could be attributed to stress conditions that were not necessarily regular during the life history of the individual (Panfili et al., 2002), possibly related to feeding competition with other predators.
The observed sexual dimorphism, in which females are larger than males, is common in Amazonian catfish (e.g., Alonso, 2002; García Vásquez et al., 2009; Córdoba et al., 2013; Hauser et al., 2018) and has even been reported for the genus Pseudoplatystoma in other regions such as in the Bolivian Amazon (Loubens, Panfili, 2000) and in the Orinoco basin (Barbarino, 2005; Pérez, Fabré, 2018). In our results, females were the largest and oldest individuals in both river systems and predominated over males from 60 cm LS onwards (Fig. 6). Similarly, Loubens, Panfili (2000) in the Mamoré River basin in Bolivia found that the largest individuals of doncella were females, with males rarely exceeding 80 cm LS while females reached up to 104.5 cm and the oldest individual was a female of 8.7 years. Inturias (2008), also in the Bolivian Amazon, recorded females up to 90.0 cm LS and 9.9 years of age, while males did not exceed 66.0 cm LS and 7.8 years. García et al. (2001) and Deza-Toboada (2005) also found that females reached larger sizes than males. The maximum sizes of doncella captured in the present study corresponded to two females from the AMU system, both with 92.5 cm LS. These sizes were below those previously reported in the same region by García et al. (2001) and Deza-Taboada et al. (2005) with individuals of ~120.0 cm LS. In the Putumayo River, the largest size was a female of 74 cm LS, being smaller than that previously reported by Camacho et al. (2006) in the same region where individuals exceeding 100.0 cm LS were sometimes captured.
The reduction in size and longevity in our results, compared to earlier studies, emphasizes the fact that it is becoming less and less feasible to obtain large individuals. As they are highly valued and marketed, they become scarce in the wild due to a strong fishing pressure, as observed in Cichla temensis Humbolt, 1821 in the Negro River (Lubich et al., 2021). This is reflected in the growth curves where the asymptotic phase of growth is not reached in the AMU system (Fig. 6A). High L∞ values often occur when there are not enough old, slow-growing individuals in the samples (Pauly, 1979), which was the case in our sampling in spite of a two years sampling effort. In large and commercially valuable species such as the doncella, the decrease of large and long-lived individuals in the wild and, therefore, in landings, is a documented effect of the intensification of fishing exploitation (Castello et al., 2013) and of the high selectivity of artisanal and commercial fisheries towards large preferred species, driven by large urban markets (Tregidgo et al., 2021). Similar conditions were found in the genus Pseudoplatystoma in the lower Paraná River basin (Resende, 2003), in P. metaense in the Orinoco River basin (Pérez, Fabré, 2018); in P. tigrinum and P. punctifer in the central Amazon (Isaac et al., 1998; Ruffino, Isaac, 1999); and in B. rousseauxii (Córdoba et al., 2013) in the Colombian Amazon, where the resource is overexploited. The high fishing pressure supported by doncella in the sampling area is attested by the relatively high proportion of immature individuals in the catches. Although our sampling was not meant to be representative of the landed size distribution, but rather of the entire length distribution available, it nevertheless reflected what the fishers caught, and immature individuals accounted for a large portion of our sampling, particularly is in the AMU system. Capturing fish that have not yet had the opportunity to reproduce, hence to contribute to future generations is an acknowledged source of stock depletion (Myers, Mertz, 1998; Froese, 2004).
Our results indicate important growth differences in doncella between the AMU system and Putumayo River. In addition, differences in size at sexual maturity, although not significant in the present study, were observed, suggesting the existence of different populations in the areas evaluated. These differences in doncella life history traits between watersheds could be due to both genetic and environmental factors (Giesel, 1976; Caswell, 1983; Partridge, Harvey, 1988; Stearns, 1992). Previous studies have shown that distances of ~200 km between geographical populations of P. punctifer in Central Amazonia could results in significantly different genetic populations using microsatellite markers (Telles et al., 2014). Pereira et al. (2009) have also demonstrated the existence of six genetically distinct groups of P. corruscans (Spix & Agassiz, 1829) in the Paraná-Paraguay system. The geographic distance between the sampling sites in the AMU system and Putumayo River were much larger than 200 km following the course of the river (Fig. 1) and a genetic differentiation resulting in a better growth in the AMU system can therefore not be excluded. Other studies, however, have reported a lower growth in fish species of the Putumayo River, when compared with the AMU system like in O. biccirhosum (Duponchelle et al., 2012) and in P. nigricans (Bonilla-Castillo et al., 2018). The fact that fish of different species tend to have a slower growth in the Putumayo River suggests that stochastic genetic variation (drift, mutations, etc.), which is supposed to be random (Hartl, Clarck, 2007), cannot account alone for the observed patterns and that less favourable environmental conditions in the Putumayo River, compared to other river basins, are a likely complementary explanation. Of course, life-history traits adjustment to local environmental condition could be achieve through phenotypic variation and/or genetic adaptation, i.e., progressive selection for genomes better adapted to the local environmental conditions (Partridge, Harvey, 1988; Stearns, 1992; Hartl, Clarck, 2007), but sorting out their relative importance is beyond the scope of this study.
The Putumayo River with its poorly fertile soils with low nutrients contents resulting in low pH, conductivity and chlorophyll-a values characteristics of oligotrophic waters, has previously been considered as less productive than other Amazonian rivers (González et al., 2006; Salazar et al., 2006). Additionally, chemical contamination resulting from the culture of coca, deforestation, illegal mining (Sierra et al., 2017) or high mercury levels in fish (Nuñez-Avellaneda et al., 2006) have been reported in the Putumayo, but there is no data yet to support the hypothesis that such contamination would be higher than in the AMU system. As previously pointed out by Bonilla-Castillo et al. (2018) a higher fishery exploitation in the Putumayo River than in the AMU system could also account for slower growth in fish populations of the Putumayo River, where the more heavily exploited populations tend to have smaller maximum sizes and slower growth. The available evidence, such as a higher proportion of immature individuals in the catches of the AMU system does not lend support to this hypothesis, nor does the fact that human population density is much higher around Iquitos, which should entail a higher fishing pressure. Nevertheless, further studies would need to be carried out to test these two alternatives and not mutually exclusive hypotheses. Yet, whatever the reasons underlying the observed differences in growth patterns, these have important implication for fisheries management.
In order to maintain the sustainability of a fishery resource, catches should consist of 100% mature individuals and 100% individuals at an optimum size that exceeds the size at first sexual maturity (Froese, 2004). In our results, the existence of immature individuals as part of the catch indicates that juveniles that have not had the opportunity to reproduce at least once in their lives are being harvested, putting the stability of the resource at risk (Myers, Mertz, 1998; Froese, 2004). Several studies have also shown that in large, long-lived fish species, large old female (“megaspawners”) provide a better quality of progeny and disproportionately contribute to future generations (Berkeley et al., 2004; Froese, 2004; Birkeland, Dayton, 2005; Venturelli et al., 2009; Arnold et al., 2018), so their permanence in the wild should be taken into account in management measures to ensure the stability and prevalence of the resource.
In the AMU system, very few individuals exceeded 80 cm LS, not reaching the lengths at first maturity determined by García et al. (2001) more than a decade earlier: 90 cm LF (~86 cm LS following equation: LS = 0.9776*LF – 1,8379, R² = 0.9984, P<0.001, Garcia Vasquez et al., unpublished data) for females and 82.5 cm LF (~79 cm LS) for males, and set at 86 cm LF (~82 cm LS) as minimum catch size in the fishing regulation of the Peruvian Amazon (Ministerial Resolution N° 147–2001–PE and Supreme Decree N° 015–2009–PRODUCE). Although the present study did not aim at precisely determining size at maturity, the results nevertheless suggest a strong decrease in the mean size at maturity of the doncella in the AMU system, from 86 cm LS in 1996–1997 (García et al., 2001) to ~50 cm LS in 2008–2010 (present study). The reduction in age and size at sexual maturity in a population is an indicator of a higher adult to juvenile mortality ratio (Reznick et al., 1990; Stearns, 1992), and is a sign of heavy exploitation of the resource. This and the observed decrease in maximum observed lengths suggest of a strong fishing pressure on the doncella, at least in the AMU system. These results warrant further studies to precisely estimate the state of exploitation of this important resource in the Peruvian Amazon. The existence of differences in the growth of doncella between river systems should be taken into account for the implementation of management measures, as well as the updating of minimum catch sizes based on the size at sexual maturity. Although part of the sampling occurred in Pucallpa, most samples of the AMU system where from the Loreto region around Iquitos. Further sampling and increased sample numbers in the upper portions of the Ucayali and Marañón systems could reveal growth and other life history traits variations within what we considered here as AMU system. The doncella, despite its ecological and economical importance remains understudied in the Peruvian Amazon. Our results provide evidence of strong fishing pressure on both adults and juveniles and of populations structuring. Further studies investigating the population structure (genetic and life history trait variations) of this important resource in the Peruvian Amazon are needed to provide a sound basis for the development of appropriate fisheries management and conservation measures to ensure the sustainability of the resource.
Acknowledgments
This study was financed by the partnership between the Institut de Recherche pour le Développment (IRD) from France and the Programa de Investigación para el Uso y Conservación del Agua y sus Recursos (AQUAREC) of the Instituto de Investigaciones de la Amazonía Peruana (IIAP). In addition, this study was part of the M. Armas master thesis supported by the Amazonian Fishes and Climate Change Project (203–2015 FONDECYT–UNMSM). †This study is dedicated to the memory of Aurea García-Vasquez, dearest colleague and friend who sucumbed to covid-19. We miss you.
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Authors
Maricell Armas1 , Hernán Ortega1, Aurea García-Vasquez2,3,†, Carmen García-Dávila2,3, Gladys Vargas2,3, Jesus Nuñez3,4, Jean-François Renno3,5 and Fabrice Duponchelle3,6
[1] Departamento de Ictiología, Museo de Historia Natural, Universidad Nacional Mayor de San Marcos, Av. Arenales, 1256, 14-0434 Lima, Peru. (MA) maricell.armas@gmail.com (corresponding author), (HO) hortega.musm@gmail.com.
[2] Instituto de Investigaciones de la Amazonia Peruana (IIAP), Av. José A. Quiñones, km 2.5, 784 Iquitos, Peru. (CGD) cgarcia@iiap.gob.pe, (GV) gladysvargasd@hotmail.com.
[3] Laboratoire Mixte International – Evolution et Domestication de l’Ichtyofaune Amazonienne (LMI-EDIA), IIAP, UAGRM, IRD, Montpellier, France. (JN) jesus.nunez@ird.fr, (JFR) jean-francois.renno@ird.fr, (FD) fabrice.duponchelle@ird.fr.
[4] Institut de Recherche pour le Développement (IRD), Laboratoire BOREA (MNHN, Univ. Caen, Sorbonne Univ., Univ. Antilles, CNRS, IRD), Paris, France.
[5] Institut de Recherche pour le Développement (IRD), UMR DIADE (Univ. Montpellier, IRD), Montpellier, France.
[6] Institut de Recherche pour le Développement (IRD), MARBEC (Univ. Montpellier, CNRS, Ifremer, IRD), Montpellier, France.
[†] In Memorian.
Authors’ Contribution
Maricell Armas: Conceptualization, Formal analysis, Investigation, Software, Validation, Visualization, Writing-original draft.
Hernán Ortega: Conceptualization, Funding acquisition, Supervision, Writing-review and editing.
Aurea Garcia-Vasquez: Data curation, Project administration, Resources, Writing-review and editing.
Carmen Garcia-Davila: Data curation, Methodology, Project administration, Resources, Writing-review and editing.
Gladys Vargas: Data curation, Funding acquisition, Resources, Writing-review and editing.
Jesus Nuñez: Conceptualization, Investigation, Methodology, Resources, Writing-review and editing.
Jean-François Renno: Conceptualization, Investigation, Methodology, Resources, Writing-review and editing.
Fabrice Duponchelle: Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing-review and editing.
Ethical Statement
Collection authorization according to the Ministerial Resolution N° 1497-2018 PRODUCE/DGPCHDI (3/Oct/2018).
Competing Interests
The authors declare no competing interests.
How to cite this article
Armas M, Ortega H, Garcia-Vasquez A, Garcia-Davila C, Vargas G, Nuñez J, Renno Jean-François, Duponchelle F. Age validation and contrasted growth performances of Pseudoplatystoma punctifer (Siluriformes: Pimelodidae) in two river systems of the Western Amazon. Neotrop Ichthyol. 2022; 20(1):e210099. https://doi.org/10.1590/1982-0224-2021-0099
Copyright
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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© 2022 The Authors.
Diversity and Distributions Published by SBI
Accepted January 5, 2022 by Fernando Pelicice
Submitted June 5, 2021
Epub March 28, 2022