Next Article in Journal
Tryptophan Reduces Intracohort Cannibalism Behavior in Tropical Gar (Atractosteus tropicus) Larvae
Previous Article in Journal
New Insights in Lifetime Migrations of Albacore Tuna (Thunnus alalunga, Bonnaterre, 1788) between the Southwest Indian and the Southeast Atlantic Oceans Using Otolith Microchemistry
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Bioeconomic Analysis of Snook Centropomus viridis, C. nigrescens, and C. medius for the Development of Mariculture in Northern Sinaloa

by
Celeste Osiris Montoya Ponce
1,
Apolinar Santamaría Miranda
2,*,
José Ángel Trigueros Salmerón
3,
Juan Pablo Apún Molina
2,*,
Francisco Guadalupe Valenzuela Orduño
4 and
Refugio Riquelmer Lugo Gamboa
2
1
Programa de Maestria en Recursos Naturales y Medio Ambiente, Centro Interdisciplinario de Investigación para el Desarrollo Integral Regional, Unidad Sinaloa, Instituto Politécnico Nacional, Guasave C.P. 81100, Sinaloa, Mexico
2
Centro Interdisciplinario de Investigación para el Desarrollo Integral Regional, Unidad Sinaloa, Instituto Politécnico Nacional, Guasave C.P. 81100, Sinaloa, Mexico
3
Departamento de biología, Universidad Autónoma de Occidente, Los Mochis C.P. 81223, Sinaloa, Mexico
4
Departameto de Finanzas, Universidad Autónoma de Sinaloa, Los Mochis C.P. 81210, Sinaloa, Mexico
*
Authors to whom correspondence should be addressed.
Fishes 2024, 9(1), 39; https://doi.org/10.3390/fishes9010039
Submission received: 8 December 2023 / Revised: 7 January 2024 / Accepted: 7 January 2024 / Published: 18 January 2024
(This article belongs to the Section Fishery Economics, Policy, and Management)

Abstract

:
The bioeconomy offers an opportunity to implement a truly sustainable global economy based on biological resources, which, thanks to biotechnologies, become renewable. In this study, we conducted a bioeconomic analysis of the three most important species of sea snook in northern Sinaloa using fishery and mathematical models to support the selection of the species with the highest growth and feasibility. Our results showed a condition factor lower than 1 (K < 1) for the three species. The size condition factor was higher in younger organisms for the three snook species. The growth rates were K = 0.320, K = 0.160, and K = 0.440 for C. viridis, C. nigrescens, and C. medius, respectively. Individual growth was 1.8 g/day for C. viridis, 1.47 g/day for C. nigrescens, and 0.91 g/day for C. medius. The length-to-weight ratio indicated negative allometric growth (b = 2.82, b = 2.72, and b = 2.73, respectively) for C. viridis, C. nigrescens, and C. medius. The simulation for possible commercial cultivation reflected varied sizes: 600 g for C. viridis and C. nigrescens and 400 g for C. medius. The financial projection of C. viridis produced IRRs of 14% and 48% in captured fishing and aquaculture models, respectively, with positive NPV. However, simulations for C. nigrescens and C. medius were not economically viable. We conclude that, according to the aquaculture model, the most financially feasible species to farm in the north of Sinaloa is C. viridis, which showed the highest growth based on fishery data compared to those for C. nigrescens and C. medius.
Key Contribution:
The bioeconomy offers an important opportunity to implement a truly sustainable global economy based on biological resources that, due to biotechnologies, become renewable. In this study, we conducted a bioeconomic analysis of the three most important species of sea snook in northern Sinaloa, using fishery data and mathematical models to support the selection of the species that will promote mariculture with the greatest chance of success.

1. Introduction

Fisheries and aquaculture are two of the most important economic activities in terms of global food production; in 2020, capture fisheries contributed 90 million tons and aquaculture contributed 88 million tons, with a total sale value of USD 406,000 million [1]. Importantly, aquaculture is contributing to the rapid increase in the fish supply by somewhat compensating for the reduction in natural fish populations, thus partially making up for the lack of products derived from the sea [2]. However, it cannot entirely counter the collapse of half of the existing fisheries in the Mexican Pacific [3].
As part of attempts to do so, one of the great challenges ahead in marine aquaculture in the near future is the selection of suitable candidate species. There are over 120 families of fishes but only two families with good aquaculture potential—Sciaenidae and Serranidae. A study prepared for the World Aquaculture Society reviewed the species of croakers of the family Sciaenidae [4], using Fishbase and other records, revealing that 60 species have aquaculture potential and a market future [5]. There are some markets already well established for certain members of the family Centropomidae, which is a species of the genus Centropomus, in the Pacific Ocean. However, there are many more species to explore in developing mariculture to avoid vulnerability due to the overproduction in fisheries, which is predicted in the region [6].
There are several other suitable candidate species to choose from, the selection of which depends on geographical location, cultural conditions, and seafood-marketing strategy. The criteria for potentially successful marine fish-farming candidate species are (1) product attributes—market demand, taste, texture, color, versatility, shelf life, freezing, and nutritional composition; (2) aquaculture performance—growth, survival, yield, and feed conversion ratio (FCR); (3) availability of complete production technology; (4) native distribution in warm–temperate to tropical oceans; (5) few existing commercial fisheries; and (6) reproduction, the technological development of juvenile mass production and its growth [7,8].
The genus Centropomus meets the criteria described, and some species have been studied to develop the technology for their cultivation, as in the cases of C. viridis in the Pacific [9] and C. undecimalis in the Atlantic [10,11,12,13,14]. Advances have mainly been made in reproductive biology, physiology, nutrition, and farming techniques. To extend these, the Fisheries Management Plan proposes carrying out bioeconomic studies of fisheries to avoid the stagnation of extraction, which is thought to have begun in 2015 and is expected to continue until 2030 [1].
In general, all species of snook are considered of high commercial value due to the flavor of their meat and the sizes reached in the adult stage [15,16]. In the Mexican Pacific Ocean, the state of Sinaloa occupies second place in fishery production, with 511 tons annually [17]. C. viridis is one of the most commercially important species, which generates important economic gains for fishermen in the coastal areas of the North Pacific [18].
Snook (Centropomus spp.) are among the most appreciated and best-valued species of marine fish in the American tropics, and some are being studied to develop the technology for their culture. Advances have been made in reproductive biology, physiology, nutrition, and cultural techniques, mainly for chucumite snook (Centropomus parallelus) [19] and common snook (C. undecimalis) in the Atlantic [12,13,14] and black snook (C. nigrescens) [20] and white snook (C. viridis) in the Pacific [9,21].
One of the mathematical models used to estimate the growth of marine species, in particular, is based on the age structure of a population, as reported by Beverton and Holt [22]. This model accurately describes the behavior of a fish population in which individuals experience changes related to population composition and usage [23]. The model predicts the consequences of management strategies, facilitating the evaluation of complex interactions (biological, environmental, technological, and economic) of fisheries and aquaculture systems [24,25,26].
The bioeconomy constitutes an opportunity to achieve a sustainable global economy for biological resources. Related research supports corresponding decision-making at the business level, including considerations of innovation, sustainability, economic growth, and employment [27,28,29]. Bioeconomic analyses are relevant in the study of species that are vulnerable to overexploitation, since inadequate fisheries management is likely to lead to the collapse of the fishing industry and put species in danger of extinction [6,30,31].
Consequently, it is necessary to recognize the species that have the greatest qualities within aquaculture, and research with a view to developing technological packages for their cultivation is required to optimize the efforts and resources available for this purpose [32]. In this work, the levels of financial potential of the three most important species of snook in northern Sinaloa, Mexico—Centropomus viridis, C. nigrescens, and C. medius—were evaluated through fishery analyses and financial models.

2. Materials and Methods

2.1. Study Areas

The sampling area is located in the north of the state of Sinaloa, Mexico (25°54′43″ N, 109°10′26″ W and 25°34′28″ N, 108°28′16″ W) (Figure 1). During the period from December 2020 to December 2021, monthly biological sampling was carried out of 30 fish caught with drift nets (3.5-inch mesh bale of 100 × 50 m) by local fishermen at each site. The total length (TL, cm) and the eviscerated weight (Pe, g) were obtained for each organism. The obtained length frequencies were grouped in intervals of 7 cm according to Sturges’ Rule to describe the structure of the population extracted through fishing and to define the main population parameters: growth and natural mortality. The species were identified using the taxonomic keys of the FAO [33,34]. The length–weight relationship was analyzed to determine the type of growth [35], as follows:
Pt = a (Lt)b
where
  • Pt = Weight of the organism in grams.
  • Lt = Total length in centimeters.
  • a = Parameter of the ordinate to the origin related to the condition factor [36,37].
  • b = Slope of the exponential equation or allometric factor.

2.2. Growth Parameters

Growth parameters were estimated using the new Shepherd’s length-composition-analysis (NSLCA) method in the FISAT II (version 1.2.2) evaluation program [38] and using the empirical equation of Pauly [39,40]:
t0 = Log(−t0) = −0.3922 − [−0.2752(Log L)] − [1.038(Log k)]
The growth parameters were modeled by applying the following growth equation:
L t t = L k t t 0
where
  • Ltt = Total length at time t.
  • L= Infinite or asymptotic length.
  • k = Growth factor or speed at which the curve reaches the asymptote.
  • t0 = Theoretical length at age 0.
Natural mortality was estimated using the empirical equations of Pauly [40] and Rikhter and Efanov [41] included in FISAT II (version 1.2.2). Pauly’s equation includes temperature as a factor that influences natural mortality and the growth parameters L∞ and k:
Log M = −0.0066 − (0.279 Log L) + (0.6543 Log k) + (0.4634 Log T°)
where
  • M = Natural mortality.
  • L and k = Parameters of the growth equation.
  • T° = Sea surface temperature.
The factor or condition status was estimated using the Fulton index [42]:
K = (P/L3) × 100
The farming simulation was based on previous results [43] from fishery models in the three Centropomus species, such as natural mortality, estimation of growth parameters, and condition factor. We completed aquaculture performance projection in growth and survival in Excel spreadsheets. We integrated information on stocking density, survival rate, FCR, number and weight of organisms, and initial and final biomass. For growth performance, the following biological variables were simulated: specific growth (SG), defined as final weight minus initial weight divided by number of days; specific growth rate (SGR), defined as mean final weight minus mean initial weight and divided by the number of days multiplied by 100; and feed conversion ratio (FCR), defined as the total feed consumed divided by final biomass [7,43,44,45].
Stocking density: Fish number stocked per cubic meter.
S D = F i s h V o l u m e
Survival Rate: Fish harvested/stocked times 100.
S u r v i v a l % = F H F S × 100
Initial Biomass (kg): Fish stocked times the initial mean weight.
IB = (FS × MWi)
Final Biomass (kg): Fish harvested times the final mean weight.
FB = (FH × MWf)
Specific Growth Rate (%): Daily weight gained in percentage of individual biomass.
S G R % = L o g W f L o g W i t × 100
Specific Growth (g): Daily weight gained in individual biomass.
S G = W f W i t
Feed Conversion Rate (FCR): Total feed consumed divided by final biomass.
F C R = T F F B

2.3. Economic Analysis

A financial analysis was conducted for a complete production cycle. The investment of capital expenditure in infrastructure and operating costs in the simulation of a single fattening stage are presented in detail in Table 1. The same investment was assumed for the 3 snook species of the captured fishing and aquaculture models.
The difference between total projected revenues and operating costs was determined for a one-year period. The data were used to calculate the cash flow of the three species of snook.
The net cash flow equals total revenues minus total expenses and is represented by the following formula:
NCF = Total Income − Total Expenses
The net present value (NPV) is calculated as the sum of future cash flows discounted to the present value, minus the initial investment. The future value and present value were calculated using the following formula:
N P V = I 0 +   t = 1 n N C F 1 + k t
The indicators of financial viability in the captured fishing and aquaculture scenarios were calculated using the following economics formulas:
I R R =   t = 0 n F n 1 + I 0 = 0
where
  • IRR = Internal rate of return.
  • Fn = Cash flow in period n.
  • n = Number of periods.
  • I0 = Initial investment.
MARR = i + f + if
where
  • MARR = Minimum acceptable rate of return.
  • i = Risk–reward.
  • f = Inflation.
P a y b a c k = I 0 F
where
  • I0 = Initial investment in project.
  • F = Value of cash flow.

3. Results

The growth values of the three snook species were estimated and compared using the von Bertalanffy method (Table 2), obtaining a growth rate for C. viridis of k = 0.320 year−1, an asymptotic length L = 77.70 cm of Lt, a zero size t0 = −0.218, and a growth of 1.8 g/day. For C. nigrescens, an asymptotic length L = 81.90 cm of Lt, a growth rate of k = 0.160 year−1, a zero size t0 = −0.90, and a growth of 1.47 g/day were found. Considering the above, the maximum asymptotic growth of white (C. viridis) and black snook (C. nigrescens) was estimated at six years of age (Figure 2 and Figure 3). The growth of C. medius resulted in an asymptotic length L = 52.50 cm of Lt, obtaining a growth rate of k = 0.440 year−1, a zero size t0 = −0.180, and a growth of 0.91 g/day. It can be observed that the maximum asymptotic growth of this species is at five years of age (Table 2).
The condition index varied throughout the year, with us obtaining the maximum values for the three species in spring and the lowest for C. nigrescens and C. viridis in summer, while for C. medius, the lowest values were recorded in autumn and winter. There was a significantly lower condition index in summer compared to spring (p < 0.05) (Figure 3).
Condition factor by sizes: n = 243 organisms were analyzed (n = 69 C. nigrescens, n = 115 C. viridis, and n = 59 C. medius) with an average TL of 52.46 cm and a structure length between 43 and 79 cm TL for C viridis, from 39 to 78 cm for C. nigrescens, and from 25 to 51 cm for C. medius. The morpho-physiological values for C. viridis were the highest between 43 and 49 cm and the lowest between 71 and 79 cm. C. nigrescens presented the highest values between 39 and 54 cm and the lowest between 71 and 78 cm. For C. medius, the condition factor was the highest between 32 and 39 cm and the lowest between 48 and 55 cm. Paired with the previous results, we surmised that the condition of the individuals decreases with age (Figure 4).
Length–weight ratio: The potential model of the length–weight relationship of C. viridis was Pt = 0.0164Lt2.8163, of C. nigrescens was Pt = 0.0236Lt2.7188, and of C. medius was Pt = 0.0231Lt2.7256. The three species of snook showed negative allometric growth (b = 2.82, b = 2.72, and b = 2.73, respectively), which, biologically, means that the species tend to become slimmer as they increase in length (Figure 5).
Farming simulation: After generating an investment model with aquaculture based on the statistics established in the fisheries biological analysis, two analyses were performed for the first and second scenarios with the captured fisheries and aquaculture data, respectively, in a single production cycle until the fattening stage. A density of 234 organisms per cubic meter, initial weight of 1 g, feed ration of 3%, and survival of 55 or 60% were assumed. The aquaculture model was simulated in floating cages of 225 m3. We found the following results for the three snook species (Table 3 and Table 4) [43].
The production costs incurred in the project correspond to inputs for production (juveniles and feed). Sales expenses correspond to the commercialization of snook (salaries, benefits, electricity, water, depreciation, etc.), as well as administrative expenses (water, electricity, rent, benefits, salaries, etc.) and financial expenses. The latter corresponded to financing that will be used as part of the initial investment of USD 2,427,000.00 with an annual interest rate of 15% for five years, to acquire inputs and infrastructure that will be used to conduct the operations.
The difference between the total projected income and the operating costs was determined for a one-year period. The data were used to calculate the cash flow of the three species of snook; however, only the species with the best economic feasibility in the captured fishing and aquaculture models is shown, in this case, C. viridis (Table 5 and Table 6).
A sensitivity analysis was executed to calculate the economic viability of the project in two different scenarios: (1) the model based on captured fishing data and (2) the simulation of aquaculture farming based on daily growth and survival. A final sale price for whole fish of 8.55 USD/kg was considered based on real market prices in Mexico. The same price was used in the two models for the three species of snook to evaluate the influence on the internal rate of return (IRR) and the net present value (NPV) of the initial investment [46].
The financial results of this study, according to the sensitivity analysis of the two models, showed a more favorable NPV for the aquaculture model, with a value of USD 177,353.30 and an IRR of 48%, compared with the captured fishing model, which yielded a value of USD 5025.98 and an IRR of 14% (Table 7). In both scenarios, a final sale price of USD 8.55 was established, showing the economic feasibility of the project. Meanwhile, the financial projections made for C. nigrescens and C. medius in the captured fishing and aquaculture models were not profitable.

4. Discussion

The condition-factor analysis of the three snook species studied in the present work presented a value of K < 1. This result differs from that reported by Tapia Varela et al. [47], who showed results for C. viridis indicating a value of K ≥ 1 in males, while the females presented a condition lower than 1 (0.98 < 1). Our results may indicate that fishing efforts could be generating variations in the fishing conditions of the populations of the three species in the study areas.
The size range obtained in this study for C. viridis is similar to that reported by Labastida-che et al. [48] in Chiapas, with an average length of 47.02 cm TL and a maximum of 78.5 cm TL. However, the results are lower than those reported by Briones Avila et al. [49], where the frequency distribution of white-snook C. viridis in the Teacapán–Agua Brava lagoon system, south of Sinaloa and north of Nayarit, covered sizes from 31 to 91 cm with a measurement of 55.37 cm TL.
Other snook studies focused specifically on C. viridis, the species with the greatest presence on the north coast of Sinaloa and Nayarit, and a maximum length of 131 cm was reported for this species [47], 11 cm longer than the previous length reported [34]. Such a variation in size structure can arise due to the selectivity of the fishing gear, its size, and the fishing technique used [50,51,52]. The size distribution can also vary from one region to another and even within the same region [53,54] because growth is affected by food availability.
The negative allometric growth for C. viridis reported in the present study is similar to that estimated by Tapia Varela et al. [47] on the north coast of Nayarit (in the general analysis of length and weight for males and females, b = 2.958 was reported). However, Labastida-che et al. reported isometric growth for both sexes of white snook in the lagoon systems of the state of Chiapas (b = 2.99) [48]. The allometry coefficient (b) has great biological importance, since it indicates the weight gain in relation to the growth in length. Variations in the estimate of b could reflect changes in the condition of individuals related to food availability, reproductive seasons, or migratory activities [55].
The estimation of the growth parameters, according to Shepherd’s method in the present work, produced values of K = 0.320 for C. viridis, K = 0.160 for C. nigrescens, and K = 0.440 for C. medius and thus growth rates of 1.8, 1.47, and 0.91 g/day, respectively. The results regarding the value of K are lower than those reported by Labastida-che et al. [48] with white bass in Chiapas, who obtained a value of K = 0.57. However, the authors’ report of a maximum estimated age for this species of six years corresponded with our results for C. viridis and C. nigrescens.
The growth rate of C. nigrescens in this study was 1.47 g/day according to fishery data, which was similar to that reported by Barreno [56], who established that this species could reach commercial sizes of 500 g in 6 months of cultivation, with rates of growth between 1.5 and 3.2 g/day. However, both growth rates are lower than the result obtained by Escárcega [32] for the same species cultivated in ponds on the coast of Michoacán (1.84 g/day). Furthermore, a growth value by Álvarez [57] exceeds those for other species of marine fish of commercial interest, such as spotted snapper (Lutjanus guttatus), yellow snapper (L. argentiventris), sea bream (Sparus aurata), sea bass (Dicentrarchus Labrax) (these last two from the Mediterranean Sea), goliath grouper (Epinephelus itajara), and sand cabrilla (Paralabrax maculatofasciatus).
According to the method of Rikhter and Efanov, the populations of white snook (C. viridis M = 0.529; C. nigrescens M = 0.626) and brown fin snook (C. medius M = 0.674) presented a natural mortality. These results are lower than those [48] for the species C. viridis in Chiapas (M = 0.94); however, the high natural-mortality rates in the latter case are suggested to be due to events such as disease, migration, or predation and due to recommendations for aquaculture in Latin America [9,21]. Therefore, the culture of C. viridis is suggested, given the results of our analysis of natural mortality, to support the recovery of natural stocks and also generate alternatives for the management of its fishery.
Snook is one of the fastest-growing capture fisheries in Mexico, with production doubling from 8000 tons in 2013 to more than 18,000 tons in 2017. This rapid growth in demand has placed snook at number 16 in terms of catch volume and number 7 in terms of value [21].
The normal market price for white snook is 10 USD/kg in whole ungutted presentation (from 800 g to 1.5 kg) and 28.52 USD/kg in fillet presentation. These prices are suggested by the federal government but are subject to fluctuations in supply and demand [17]. Accordingly, in our study, for the culture of snook, economic viability was tested with a final sale price of 8.69 USD/kg. However, a final price of 11 to 13 USD/kg could be established, since it is an aquaculture product that will be available upon request by the client, guaranteeing quality, freshness, and sustainability in the product and production process [17].
This aquaculture model is based on previous work [17] where an investigation into the viability of cultivating C. viridis in floating cages revealed a net present value (NPV) of USD 40,291.83 (MXN 811,074.54 exchange rate on 7 March 2022) in a conservative scenario and USD 165,822.63 (MXN 3,338,009.54 exchange rate as of 7 March 2022) in an optimistic scenario, at final sale prices of 7.5 and 10 USD/kg and IRRs of 39% and 99%, respectively. However, in the present study, we obtained a higher IRR of 48% and an NPV of MXN 3,625,101.50 for C. viridis in the aquaculture-model scenario [17]. Our findings were comparable to the results of the inversion analysis of Martinez-Cordero et al. [58] for the culture of the snapper Lutjanus guttatus in sea cages, where an NPV of USD 119,360 was obtained in a 10-year scheme.

5. Conclusions

This study concludes that the three fish species show negative allometric growth, which indicates that the growth in body weight is slower than the growth in length. In addition, the best biological condition for the three species occurs in summer and the worst in winter due to the higher water temperature in summer, which favors the growth and development of the fish. The economic viability was ascertained, with a final sale price of (8.55 USD/kg), which revealed a positive net present value (NPV) at the end of the 5 years projected and an internal rate of return (IRR) of 48%. Therefore, the project can generate profits and provide an attractive return on investment. Regarding natural mortality, a high rate was observed in all three species, suggesting events such as disease, migration, or predation. It is important to conduct further research to determine the specific causes of natural mortality in these species and to identify appropriate measures to prevent them. The culture of C. viridis is suggested, given the conclusions obtained in our analysis of natural mortality, to support the recovery of natural stocks and also generate alternatives for the management of its fishery. This work shows that C. viridis is the most financially feasible species to cultivate according to the aquaculture model in northern Sinaloa, since based on a captured fishing model, it has better growth in culture within a shorter time compared to C. nigrescens and C. medius, resulting in a profitability of USD 177,253.30 and recovery in 2 years and 8 months.

Author Contributions

Conceptualization, C.O.M.P., A.S.M., J.Á.T.S. and J.P.A.M.; methodology, C.O.M.P., A.S.M., J.Á.T.S. and J.P.A.M.; software, C.O.M.P., A.S.M. and J.Á.T.S.; validation, A.S.M. and J.Á.T.S.; formal analysis, C.O.M.P., A.S.M., J.Á.T.S. and F.G.V.O.; investigation, C.O.M.P., A.S.M., J.Á.T.S. and J.P.A.M.; resources, A.S.M. and J.P.A.M.; data curation, C.O.M.P., A.S.M., J.Á.T.S. and J.P.A.M.; writing—original draft preparation, C.O.M.P., A.S.M., J.Á.T.S. and R.R.L.G.; writing—review and editing, C.O.M.P., A.S.M., J.Á.T.S. and R.R.L.G.; visualization, C.O.M.P., A.S.M., J.Á.T.S., F.G.V.O. and R.R.L.G.; supervision, A.S.M., J.Á.T.S. and J.P.A.M.; project administration, A.S.M. and J.P.A.M.; funding acquisition, A.S.M. and J.P.A.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was financially supported with grants from the National Polytechnic Institute (project SIP 20220539: Analysis of the culture of snook Centropomus viridis and white shrimp Litopenaeus vannamei in a system of floating cages for the development of mariculture in northwestern Mexico).

Institutional Review Board Statement

Approval from the ethics committee or the institutional review board was not necessary, as we did not manipulate, cultivate, or sacrifice; instead, our measures were taken in captured organisms from commercial fishing by fishermen’s groups, which have CONAPESCA-01-068 commercial fishing regulatory permits administered in Mexico.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within this article.

Acknowledgments

The authors thank the staff and students of CIIDIR-Sinaloa for providing the facilities to support this research. One of the authors was a recipient of the CONAHCYT graduate fellowship as well as a fellow of COFAA-IPN and EDI-IPN.

Conflicts of Interest

The authors declare they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

  1. FAO. The State of World Fisheries and Aquaculture 2022; FAO: Rome, Italy, 2022. [Google Scholar]
  2. Longo, S.B.; Clark, B.; York, R.; Jorgenson, A.K. Aquaculture and the displacement of fisheries captures. Conserv. Biol. 2019, 33, 832–841. [Google Scholar] [CrossRef]
  3. Cerdernares, G.; Ramírez, E.; Ramos, S.; González, G.; Anislado, V.; López, D.; Karam, S. Impacto de la Actividad Pesquera sobre la Diversidad Biológica. Iberoam. Cienc. 2014, 1, 96–114. [Google Scholar]
  4. Benetti, D.D.; Matera, J.A.; Stevens, O.M.; Alarcon, J.F.; Feeley, M.W.; Rotman, F.J.; Minemoto, Y.; Banner-Stevens, G.; Fanke, J.; Zimmerman, S.; et al. Growth, survival, and feed conversion rates of hatchery-reared mutton snapper Lutjanus analis cultured in floating net cages. J. World Aquac. Soc. 2002, 33, 349–357. [Google Scholar] [CrossRef]
  5. Froehlich, H.E.; Gentry, R.R.; Halpern, B.S. Global change in marine aquaculture production potential under climate change. Nat. Ecol. Evol. 2018, 2, 1745–1750. [Google Scholar] [CrossRef]
  6. Cheung, W.W.L.; Sumaila, U.R. Economic incentives and overfishing: A bioeconomic vulnerability index. Mar. Ecol. Prog. Ser. 2015, 530, 223–232. [Google Scholar] [CrossRef]
  7. Chávez, E.A.; Santamaría-Miranda, A.; Ponce-Palafox, J.T. Bioeconomic Analysis of three west American snappers (Lutjanus spp.) with aquaculture potential. Mitteilungen Klosterneubg. 2014, 64, 253–267. [Google Scholar]
  8. Alvarez-Lajonchère, L.; Ibarra-Castro, L. Aquaculture species selection method applied to marine fish in the Caribbean. Aquaculture 2013, 408–409, 20–29. [Google Scholar] [CrossRef]
  9. Ibarra-Castro, L.; Navarro-Flores, J.; Sánchez-Téllez, J.L.; Martínez-Brown, J.M.; Ochoa-Bojórquez, L.A.; Rojo-Cebreros, A.H. Hatchery production of Pacific White Snook at CIAD-Unity Mazatlan, Mexico. J. World Aquacult. 2017, 48, 25–29. [Google Scholar]
  10. Taylor, R.G.; Whittington, J.A.; Grier, H.J.; Crabtree, R.E. Age, growth, maturation, and protandric sex reversal in common snook, Centropomus undecimalis, from the east and west coasts of South Florida. Fish. Bull. 2000, 98, 612–624. [Google Scholar]
  11. Yanes-Roca, C.; Rhody, N.; Nystrom, M.; Main, K.L. Effects of fatty acid composition and spawning season patterns on egg quality and larval survival in common snook (Centropomus undecimalis). Aquaculture 2009, 287, 335–340. [Google Scholar] [CrossRef]
  12. Ibarra-Castro, L.; Alvarez-Lajonchère, L.; Rosas, C.; Palomino-Albarrán, I.G.; Holt, G.J.; Sanchez-Zamora, A. GnRHa-induced spawning with natural fertilization and pilot-scale juvenile mass production of common snook, Centropomus undecimalis (Bloch, 1792). Aquaculture 2011, 319, 479–483. [Google Scholar] [CrossRef]
  13. Rhody, N.R.; Davie, A.; Zmora, N.; Zohar, Y.; Main, K.L.; Migaud, H. Influence of tidal cycles on the endocrine control of reproductive activity in common snook (Centropomus undecimalis). Gen. Comp. Endocrinol. 2015, 224, 247–259. [Google Scholar] [CrossRef]
  14. Passini, G.; Carvalho, C.V.A.; Sterzelecki, F.C.; Baloi, M.F.; Cerqueira, V.R. Spermatogenesis and steroid hormone profile in puberty of laboratory-reared common snook (Centropomus undecimalis). Aquaculture 2019, 500, 622–630. [Google Scholar] [CrossRef]
  15. Isabel, M.; Parra, A.; Rodríguez-ibarra, L.E.; Ibarra-castro, L. Effects of frequency and feeding time on growth, food utilization, somatic indexes, and survival of juvenile white snook Centropomus viridis. Cienc. Mar. 2020, 46, 155–163. [Google Scholar]
  16. Álvarez-González, C.A.; Ramírez Martínez, C.; Martínez-García, R.; Darias, M.J.; Vissio, P.; Peña-Marín, E.S.; Tovar-Ramírez, D.; Oliva-Arriagada, M.; Hernández Martínez, M.; Gisbert, E. Carta Acuícola Iberoamericana; UANL-Universidad Juárez Autónoma de Tabasco (UJAT)-Red CYTED LARVAPlus-IRTA: Villahermosa, Mexico, 2023; ISBN 978-607-27-1800-5. [Google Scholar]
  17. Conapesca Anuario Estadístico de Acuacultura y Pesca. 2017. Available online: https://nube.conapesca.gob.mx/sites/cona/dgppe/2017/ANUARIO_ESTADISTICO_2017.pdf (accessed on 14 April 2023).
  18. Rodríguez-Madrigal, J.A.; Flores-Ortega, J.R.; Torrescano-castro, C.G.; Cortes-Hernandez, M. Actualización de los Aspectos Biológicos-Pesqueros de Robalo Garabato (Centropomus viridis) en la Reserva de la Biósfera Marismas Nacionales Nayarit, y su zona de Influencia; Pronatura: Tepic, Mexico, 2020. [Google Scholar]
  19. Cerqueira, V.R.; Tsuzuki, M.Y. A review of spawning induction, larviculture, and juvenile rearing of the fat snook, Centropomus parallelus. Fish Physiol. Biochem. 2009, 35, 17–28. [Google Scholar] [CrossRef] [PubMed]
  20. Resley, M.J.; Nystrom, M.; Yanes-Roca, C.; Leber, K.M.; Main, K.L. Controlled Maturation and Spawning of Captive Black Snook. World Aquac. 2014, 45, 29–34. [Google Scholar]
  21. Alvarez-Lajonchère, L.; Tsuzuki, M.Y. A review of methods for Centropomus spp. (snooks) aquaculture and recommendations for the establishment of their culture in Latin America. Aquac. Res. 2008, 39, 684–700. [Google Scholar] [CrossRef]
  22. Beverton, R.J.H.; Holt, S.J. On the Dynamics of Exploited Fish Populations; Softcover; Springer Science & Business Media: Dordrecht, The Netherlands, 1957; ISBN 978-94-010-4934-4. [Google Scholar]
  23. Parra, E.; Gordillo, W.; Pinzón, W.J. Models of population growth: Teaching-learning from recursive equations. Form. Univ. 2019, 12, 25–34. [Google Scholar] [CrossRef]
  24. Pomeroy, R.; Bravo-Ureta, B.E.; Solís, D.; Johnston, R.J. Bioeconomic modelling and salmon aquaculture: An overview of the literature. Int. J. Environ. Pollut. 2008, 33, 485–500. [Google Scholar] [CrossRef]
  25. Cuenco, M.L. Aquaculture Systems Modeling: An Introduction with Emphasis on Warmwater Aquaculture; International Center for Living Aquatic Resources Management: Manila, Philippines, 1989; ISBN 971-1022-77-X. [Google Scholar]
  26. Araneda, M.E.; Miranda, R. Análisis y modelación bioeconómica: Una herramienta de gestión para decisiones de producción e inversión en acuicultura. Aquainnovo 2013, 2013, 5. [Google Scholar]
  27. Hodson de Jaramillo, E. Bioeconomy and circular economy: The sustainable future. Rev. Acad. Colomb. Cienc. Exactas Físicas Nat. 2018, 42, 188. [Google Scholar] [CrossRef]
  28. Summit, G.B. Innovation in the Global Bioeconomy for Sustainable and Inclusive Transformation and Wellbeing. In Proceedings of the Global Bioeconomy Summit 2018, Berlin, Germany, 19–20 April 2018. [Google Scholar]
  29. Rodríguez, A.G.; Rodrigues, M.; Sotomayor, O. Hacia una Bioeconomía Sostenible en América Latina y el Caribe Elementos para una Visión Regional; serie Recu.; Comisión Económica para América Latina y el Caribe (CEPAL): Santiago de Chile, Chile, 2019; ISBN 2664-4541. [Google Scholar]
  30. Clark, C.W. Profit Maximization and the Extinction of Animal Species. J. Polit. Econ. 1973, 81, 950–961. [Google Scholar] [CrossRef]
  31. Seijo, J.C.; Pérez, E.P.; Cabrera, M.A.; Hernández, D. Riesgo e Incertidumbre en el Manejo de Recursos Vivos: Un Enfoque Bioeconómico Precautorio; Universidad de Concepción: Concepción, Chile, 1997. [Google Scholar]
  32. Escárcega Rodríguez, S. Preselección de especies para la piscicultura marina en el Pacífico Sur de México. Cienc. Ergo Sum 2018, 25, e6-1–e6-17. [Google Scholar] [CrossRef]
  33. Fischer, W.; Krupp, F.; Schneider, W.; Sommer, C.; Carpenter, K.E.; Niem, V.H. Guía FAO para la Identificación de Especies para los Fines de la Pesca- Pacífico Centro Oriental; Organizacion de las Naciones Unidad para la Agricultura y la Alimentación: Roma, Italy, 1995; ISBN 92-5-303408-4. [Google Scholar]
  34. Allen, G.R.; Robertson, D.R. Peces del Pacifico Oriental Tropical; Conabio, Agrupación Sierra Madre y Cemex: Mexico City, Mexico, 1998; ISBN 9789696397557. [Google Scholar]
  35. Sparre, P.; Venema, S.C. Introduction to Tropical Fish Atock Assessment; Rev. 2; Organización de las Naciones Unidas para la Agricultura y la Alimentación (FAO): Rome, Italy, 1997; ISBN 92-5-303995-7. [Google Scholar]
  36. Ricker, W.E. Computation and Interpretation of Biological Statistics of Fish Populations. Fish. Res. Board Can. Bull. 1975, 191, 1–382. [Google Scholar]
  37. Safran, P. Theoretical analysis of the weight-length relationship in fish juveniles. Mar. Biol. 1992, 112, 545–551. [Google Scholar] [CrossRef]
  38. Gayanilo, F.; Sparre, P.; Pauly, D. FAO-ICLARM Stock Assessment Tools II (FiSAT II) User’s Guide; Food and Agriculture Organization of the United Nations: Rome, Italy, 2005; p. 168. [Google Scholar]
  39. Pauly, D. Gill Size and Temperature as Governing Factors in Fish Growth: A Generalization of Von Bertalanffy’s Growth Formula; Institut für Meereskunde: Kiel, Germany, 1979. [Google Scholar]
  40. Pauly, D. On the interrelationships between natural mortality, growth parameters, and mean environmental temperature in 175 fish stocks. ICES J. Mar. Sci. 1980, 39, 175–192. [Google Scholar] [CrossRef]
  41. Rikhter, V.A.; Efanov, V.N. On one of the approaches to estimation of natural mortality of fish populations. Int. Comm. Northwest Atl. Fish. 1976, 76, 2–13. [Google Scholar]
  42. Froese, R. Cube law, condition factor and weight–length relationships: History, meta-analysis and recommendations. J. Appl. Ichthyol. 2006, 22, 241–253. [Google Scholar] [CrossRef]
  43. Conapesca Robalo, un Producto Pesquero y Acuícola en Incremento. Available online: https://www.gob.mx/conapesca/articulos/robalo-un-producto-pesquero-y-acuicola-en-incremento?idiom=es (accessed on 7 March 2023).
  44. Giovanni, B.; Apolinar, S.M.; Manuel, M.B.J.; Leonardo, I.C. Technical-economic viability of white snook Centropomus viridis culture in floating cages in a coastal lagoon in northwestern Mexico. Aquac. Rep. 2022, 23, 101048. [Google Scholar] [CrossRef]
  45. Apún-Molina, J.P.; Santamaría-Miranda, A.; Luna-González, A.; Ibarra-Gámez, J.C.; Medina-Alcantar, V.; Racotta, I.S. Growth and metabolic responses of whiteleg shrimp Litopenaeus vannamei and Nile tilapia Oreochromis niloticus in polyculture fed with potential probiotic microorganisms on different schedules. Lat. Am. J. Aquat. Res. 2015, 43, 435–445. [Google Scholar] [CrossRef]
  46. Zugarramurdi, A.; Parin, M.A.; Lupin, H.M. Economic Engineering Applied to the Fishery Industry; FAO documento técnico de pesca; Food and Agriculture Organization of the United Nations: Washington, DC, USA, 1995; ISBN 9789251037386. [Google Scholar]
  47. Tapia Varela, J.R.; Palacios Salgado, D.S.; Romero-Bañuelos, C.A.; Ruiz Bernés, S.; Nieto Navarro, J.T. Length-weight relationship and condition factor of Centropomus viridis (Actinopterygii: Perciforms: Centropomidae) in the north coast of Nayarit. Acta Univ. 2020, 30, 1–7. [Google Scholar] [CrossRef]
  48. Labastida-che, A.; Núñez-Orozco, A.L.; Oviedo-Piamonte, J.A. Aspectos biológicos del robalo hocicudo Centropomus viridis, en el sistema lagunar. Cienc. Pesq. 2013, 21, 21–28. [Google Scholar]
  49. Briones Avila, E.; Green Ruiz, Y.A.; Morales Bojorquez, E. Edad y Crecimiento de Centropomus viridis del Sistema Lagunar de Teacapán-Agua Brava, sur de Sinaloa y Norte de Nayarit. In III Foro Científico de Pesca Ribereña; Barr, D.E.E., Carrasco Águila, M.Á., Eds.; Sagarpa: Puerto Vallarta, Jalisco, 2006; p. 2. [Google Scholar]
  50. Grimes, C.B. Fishery Production and the Mississippi River Discharge. Fisheries 2001, 26, 17–26. [Google Scholar] [CrossRef]
  51. Watson, R.; Pauly, D. Systematic distortions in world fisheries catch trends. Nature 2001, 414, 534–536. [Google Scholar] [CrossRef]
  52. Hernandez, A.; Kempton, W. Changes in fisheries management in Mexico: Effects of increasing scientific input and public participation. Ocean Coast. Manag. 2003, 46, 507–526. [Google Scholar] [CrossRef]
  53. Matsuyama, M.; Matsuura, S.; Ouchi, Y.; Hidaka, T. Marine Maturity classification and group maturity. Mar. Biol. 1987, 96, 163–168. [Google Scholar] [CrossRef]
  54. Vazzoler, A.E. Biologia da Reprodução de Peixes Teleósteos: Teoria e Prática; Sociedade Brasileira de Ictiologia: São Paulo, Brazil, 1996; ISBN 85-85545-16-X. [Google Scholar]
  55. Frota, L.O.; Costa, P.A.S.; Braga, A.C. Length-weight relationships of marine fi shes from the central Brazilian coast. NAGA WorldFish Cent. Q. 2004, 27, 20–26. [Google Scholar]
  56. Barreno Coba, J.R. Crecimiento de Robalo en Jaulas a Diferentes Densidades de Siembra Alimentados con Dieta Artificial y Alimento Vivo Mediante tres Tratamientos en la Camaronera Camcomarca SA Comuna Palmar. Bachelor’s Thesis, Universidad Estatal Península de Santa Elena Facultad, La Libertad, El Salvador, 2015. [Google Scholar]
  57. Álvarez-Lajonchère, L.S. La selección de especies de peces marinos nativos en el Caribe y avances en México. In Proceedings of the Primera Conferencia Latinoamericana Sobre Cultivo de Peces Nativos; 2006. Available online: https://docplayer.es/7794831-La-seleccion-n-de-especies-de-peces-marinos-nativas-en-el-caribe-y-avances-en-mexicom.html (accessed on 7 January 2023).
  58. Martínez-Cordero, F.J.; Sanchez-Zazueta, E.; Hernández, C. Investment analysis of marine cage culture by applying bioeconomic reference points: A case study of the spotted rose snapper (Lutjanus guttatus) in Mexico. Aquac. Econ. Manag. 2017, 22, 209–228. [Google Scholar] [CrossRef]
Figure 1. Locations of the study areas in the north of Sinaloa, Mexico.
Figure 1. Locations of the study areas in the north of Sinaloa, Mexico.
Fishes 09 00039 g001
Figure 2. Growth curves of white-snook C. viridis, C. nigrescens, and C. medius in northern Sinaloa.
Figure 2. Growth curves of white-snook C. viridis, C. nigrescens, and C. medius in northern Sinaloa.
Fishes 09 00039 g002
Figure 3. Condition factors of C. viridis, C. nigrescens, and C. medius during the four seasons of the year in northern Sinaloa (Different letters explain the group differences).
Figure 3. Condition factors of C. viridis, C. nigrescens, and C. medius during the four seasons of the year in northern Sinaloa (Different letters explain the group differences).
Fishes 09 00039 g003
Figure 4. Condition factors by length interval of white-snook C. viridis, C. nigrescens, and C. medius in northern Sinaloa (Different letters explain the group differences).
Figure 4. Condition factors by length interval of white-snook C. viridis, C. nigrescens, and C. medius in northern Sinaloa (Different letters explain the group differences).
Fishes 09 00039 g004
Figure 5. Analysis of the length–weight relationship of white-snook C. viridis, C. nigrescens, and C. medius in northern Sinaloa.
Figure 5. Analysis of the length–weight relationship of white-snook C. viridis, C. nigrescens, and C. medius in northern Sinaloa.
Fishes 09 00039 g005
Table 1. Investment of capital concepts for total production in USD.
Table 1. Investment of capital concepts for total production in USD.
ConceptOriginal Amount of Investment (OAI) 2023
Initial cash6115.46
Guarantee deposit3140.90
Initial inventory65,958.90
Production equipment55,332.19
Furniture and equipment1806.38
Transportation equipment4187.87
Computer equipment759.57
Materials inventory532.78
Installation team2617.42
Total investment148,451.48
Table 2. Comparison of growth rates of the three snook species.
Table 2. Comparison of growth rates of the three snook species.
Growth RateC. viridisC. nigrescensC. medius
L77.7081.9052.50
k0.3200.1600.440
t0−0.218−0.90−0.180
Table 3. Farming simulation of C. viridis, C. nigrescens, and C. medius in a single stage of production (fattening), according to data from the fishing model.
Table 3. Farming simulation of C. viridis, C. nigrescens, and C. medius in a single stage of production (fattening), according to data from the fishing model.
VariableC. viridisC. nigrescensC. medius
Stocking density (fish/m3)234234234
Culture days336413364
Initial weight (g)1.01.01.0
Final weight (g)600600330
Initial biomass (kg)181818
Final biomass (kg)632554733289
Specific growth rate (%)17814590
Weight gained per day (g)1.81.470.91
Feed conversion ratio (FCR)3.163.153.19
Survival (%)605555
Table 4. Farming simulation of C. viridis, C. nigrescens, and C. medius in a single stage of production (fattening), according to aquaculture model.
Table 4. Farming simulation of C. viridis, C. nigrescens, and C. medius in a single stage of production (fattening), according to aquaculture model.
VariableC. viridisC. nigrescensC. medius
Stoking density (fish/m3)234234234
Culture days273364364
Initial weight (g)1.01.01.0
Final weight (g)600600400
Initial biomass (kg)181818
Final biomass (kg)736459563974
Specific growth rate (%)219164109
Weight gained per day (g)2.201.651.10
Feed conversion ratio (FCR)2.843.193.19
Survival (%)605555
Table 5. Cash flow of captured fishing model of C. viridis (USD).
Table 5. Cash flow of captured fishing model of C. viridis (USD).
Income StreamExpense FlowFuture ValuePresent Value
Initial investment−148,451.48−148 451.48−148,451.48−148,451.48
2023270,761.99227,544.5643,217.4338,255.00
2024309,995.40308,447.161548.231213.10
2025354,913.73325,748.3729,165.3620,228.12
2026406,340.73343,976.1162,364.6238,287.39
2027465,219.50363,102.50102,117.0055,493.85
Table 6. Aquaculture-model cash flow for C. viridis.
Table 6. Aquaculture-model cash flow for C. viridis.
Income StreamExpense FlowFuture ValuePresent Value
Initial investment−148,451.48−148,451.48−148,451.48−148,451.48
2023315,239.73235,050.1680,189.5670,981.83
2024360,917.96316,478.1644,439.8034,820.17
2025413,214.98334,341.5378,873.4454,703.97
2026473,089.82353,170.80119,919.0273,621.65
2027541,640.54372,940.82168,699.7291,677.16
Table 7. Indicators of financial viability in the captured fishing and aquaculture scenarios of C. viridis.
Table 7. Indicators of financial viability in the captured fishing and aquaculture scenarios of C. viridis.
Financial IndicatorC. viridis
ScenarioCaptured fishing modelAquaculture model
MARR26%26%
IRR14%48%
NPV (USD)5025.98177,353.30
Pay-back5 years 3 months2 years 8 months
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Montoya Ponce, C.O.; Santamaría Miranda, A.; Trigueros Salmerón, J.Á.; Apún Molina, J.P.; Valenzuela Orduño, F.G.; Lugo Gamboa, R.R. Bioeconomic Analysis of Snook Centropomus viridis, C. nigrescens, and C. medius for the Development of Mariculture in Northern Sinaloa. Fishes 2024, 9, 39. https://doi.org/10.3390/fishes9010039

AMA Style

Montoya Ponce CO, Santamaría Miranda A, Trigueros Salmerón JÁ, Apún Molina JP, Valenzuela Orduño FG, Lugo Gamboa RR. Bioeconomic Analysis of Snook Centropomus viridis, C. nigrescens, and C. medius for the Development of Mariculture in Northern Sinaloa. Fishes. 2024; 9(1):39. https://doi.org/10.3390/fishes9010039

Chicago/Turabian Style

Montoya Ponce, Celeste Osiris, Apolinar Santamaría Miranda, José Ángel Trigueros Salmerón, Juan Pablo Apún Molina, Francisco Guadalupe Valenzuela Orduño, and Refugio Riquelmer Lugo Gamboa. 2024. "Bioeconomic Analysis of Snook Centropomus viridis, C. nigrescens, and C. medius for the Development of Mariculture in Northern Sinaloa" Fishes 9, no. 1: 39. https://doi.org/10.3390/fishes9010039

APA Style

Montoya Ponce, C. O., Santamaría Miranda, A., Trigueros Salmerón, J. Á., Apún Molina, J. P., Valenzuela Orduño, F. G., & Lugo Gamboa, R. R. (2024). Bioeconomic Analysis of Snook Centropomus viridis, C. nigrescens, and C. medius for the Development of Mariculture in Northern Sinaloa. Fishes, 9(1), 39. https://doi.org/10.3390/fishes9010039

Article Metrics

Back to TopTop