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This study assessed the impact of tilapia farming on poverty in the States of Oaxaca, Guerrero, and Chiapas, which have the highest levels of poverty in Mexico. The study uses both 2018 data from a...

This quantitative risk assessment provided an analytical framework to estimate white spot syndrome virus (WSSV) transmission risks in the following different scenarios: (1) partial harvest from rearing ponds and (2) post-harvest transportation, assuming that the introduction of contaminated water with viral particles into shrimp culture ponds is the main source of viral transmission risk. Probabilities of infecting shrimp with waterborne WSSV were obtained by approaching the functional form that best fits (likelihood ratio test) published data on the dose-response relationship for WSSV orally inoculated through water into shrimp. Expert opinion defined the ranges for the following uncertain factors: (1) the concentrations of WSSV in the water spilled from the vehicles transporting the infected shrimp, (2) the total volume of these spills, and (3) the dilution into culture ponds. Multiple scenarios were analysed, starting with a viral load (VL) of 1 × 102 m L−1 in the contaminated water spilled that reached the culture pond, whose probability of infection of an individual shrimp (Pi) was negligible (1.7 × 10−7). Increasing the VL to 1 × 104.5 m L−1 and 1 × 107 m L−1 yielded results into very low (Pi = 5.3 × 10−5) and high risk (Pi = 1.6 × 10−2) categories, respectively. Furthermore, different pond stocking density (SD) scenarios (20 and 30 post-larvae [PL]/m2) were evaluated, and the probability of infection of at least one out of the total number of shrimp exposed (PN) was derived; for the scenarios with a low VL (1 × 102 m L−1), the PN remained at a negligible risk level (PN, 2.4 × 10−7 to 1.8 × 10−6). For most of the scenarios with the moderate VL (1 × 104.5 m L−1), the PN scaled up to a low risk category (PN, 1.1 × 10−4 to 5.6 × 10−4), whereas for the scenarios with a high VL (1 × 107 m L−1), the risk levels were high (PN, 2.3 × 10−2 to 3.5 × 10−2) or very high (PN, 1.1 × 10−1 to 1.6 × 10−1) depending on the volume of contaminated water spilled in the culture pond (VCWSCP, 4 or 20 L). In the sensitivity analysis, for a SD of 30 PL/m2, it was shown that starting with a VL of 1 × 105 m L−1 and a VCWSCP of 12 L, the PN was moderate (1.05 × 10−3). This was the threshold for greater risks, given the increase in either the VCWSCP or VL. These findings supported recommendations to prevent WSSV spread through more controlled transportation and partial harvesting practices.

In Mexico, marine finfish cage culture is envisioned as an economic alternative for coastal fishermen. Because research and outreach have not yet proved that this is profitable, assessing the inves...

Credit management (funding source with its specific interest rate, its timing, and amount) and its trade, affect feasibility of commercial shrimp farming. To analyze optimal trade credit management, an existing bioeconomic model of a semi-intensive shrimp farm (139 hectares with 44 earthen ponds) located in Sinaloa, Mexico, was extended to create a framework that assesses the decision-making problem related to funding from input suppliers (feed and postlarvae) during one culture cycle, integrating stochastic factors like shrimp mortality and pond water temperature. Through the application of Monte Carlo simulation and genetic algorithm-based optimization techniques, results show that the minimum funding cost is US$15,710 (for an operation budget of US$603,790), 27% lower than alternative funding scenarios (P-value

This article analyses the optimal selection of stocking density and date in semi-intensive culture of shrimp Litopenaeus vannamei (Boone, 1931). The empirical evaluation of productive and economic scenarios derived from the specific choice of these management variables is often unfeasible for decision makers. To overcome this limitation, the bioeconomic modelling is widely applicable in aquaculture systems. In the present study, profit maximization for a semi-intensive shrimp farm is obtained through the development of a bioeconomic model to analyse the combination of stocking density (range: 6–30 postlarvae (PL) m−2) and date (from March 1st to June 1st) as decision variables for a shrimp farm located in Sinaloa, Mexico. The results show that pond water temperatures prevailing during culture cycle when the stocking date is June 1st (temperature in 19-weeks culture period: 30.76 ± 0.87°C) and the stocking density is 20–24 PL m−2 produce a maximized Present Value Profit (PVπ) of US$−ha 10 350 and PVπ US$−ha 2526 for weekly mortality rates at low (2.1%) and medium (5.8%) levels respectively. The marginal change in the cost of feed (±1%) has the greatest effect on PVπ (−0.58% and 0.59% respectively). The discussion focuses on the combined effect of mortality rate, stocking density and especially, on the stocking date decision, for a given production planning framework, taking into account that the stocking date is the main management decision variable to cope with viral diseases outbreaks.

In Mexico shrimp farming is the most important aquaculture activity. However, its sustainable development has been threatened in recent years by the economic risk associated with low yields caused by outbreaks of viral diseases. A stochastic bioeconomic model was developed to analyze the economics of farm management adjustments as a response to disease risks, using pond-level data from a farm operating in the State of Sinaloa, Mexico, during the period 2001–2005. The data base analyzed included different combinations of stocking density (in the range 6–30 PL/m2) and culture time (from 12 to 31 weeks), which allows for wider application of the simulation results, even at the industry level. Results from this study indicate that operating costs would increase by 33% if the farmer would choose to market product directly. Scenarios with lower stocking densities and intermediate culture times generated the highest probabilities 6–9 PL/m2 16–19 weeks (76%/100%/70%), and 10–14 PL/m2 20–24 weeks (72%/99%) of achi...

El incremento en la escasez del agua y por otra parte las intensas precipitaciones pluviales en ciertas regiones geográficas son características de cambios en el modelo general de disponibilidad del agua como consecuencia del cambio climático. Este cambio genera una grave amenaza para la obtención de una producción acuícola estable. Aunado a esto, una amenaza secundaria es la pérdida de tierras productivas debido al aumento de aridez (y salinidad asociada), al agotamiento freático y al aumento del nivel del mar (FAO, 2008). El aumento en la producción acuícola a partir de la gestión del recurso agua será esencial en la consecución de las metas de sustentabilidad y seguridad alimentaria en el mundo, derivándose de ello la importancia de los sistemas de recirculación acuícola. Mediante un modelo bioeconómico, se evaluó la rentabilidad y escala de proyecto en el cultivo intensivo de tilapia en sistemas de recirculación de agua (SRA), utilizando como fuente primaria información de cultivo a nivel piloto efectuadas en el Centro de Investigación Científica y de Educación Superior de Ensenada (CICESE). El modelo bioeconómico utilizado consiste de tres submodelos: biológico, de manejo en producción y económico. En e submodelo biológico se simula el crecimiento semanal de la tilapia mediante un modelo Von Bertalanffy. En el submodelo de manejo en producción se determina el tiempo de cullivo, talla de cosecha, y densidad de cultivo. En el submodelo económico se determinan los costos de inversión, operación y fijos. Bajo escenarios de riesgo, las escalas de proyecto se evalúan a partir de un módulo - que se compone de un tanque de maternidad, tres de engorda de 6 metros de diámetro y un sistema invernadero-, el cual se escala a 5 y 10 módulos. Los proyectos se evaluaron tanto de la perspectiva de proyecto tipo privado como de proyecto tipo social (escenarios base). Posteriormente, para ambos tipos de proyecto se evaluó rentabilidad al incluir diferentes subsidios de la CONAPESCA-SAGARPA, específicamente a Activos Productivos y el subsidio parcial de la electricidad a granjas acuícolas