No abstract

We used a bio-economic model to analyze the role that alternative seeding-harvesting schedules, temperature, dissolved oxygen, stocking density, and duration of cultivation play in the economic performance of semi-intensive shrimp cultivation in Mexico. The highest production was predicted for the May-August schedule (1130-2300 kg ha-1), while the lowest yields were obtained for the March-June schedule (949-1300 kg ha-1). The highest net revenues were projected for the August-November schedule (US$354-1444 ha-1), while the lowest was projected for the May-August schedule (US$330-923 ha-1). The highest annual net revenues were predicted for the combination of the March-June and August-November schedules (US$1432-2562 ha-1). Sensitivity analysis indicated temperature and dissolved oxygen were the most important factors determining net revenues in March-June schedule. For the May-August and August-November schedules, stocking density was the most important factor. Duration of cultivation was the least sensitive variable. Break-even production analysis confirmed that the combination of the March-June and August-November schedules were more efficient from an economic perspective. We recommend test some ponds with higher stocking density in the March-June and August-November schedules, and in the latter case, seeding in June or July rather than August.

We used stochastic models for analysis of the uncertainty involved in semi-intensive production of shrimp in Nayarit state, Mexico, incorporating partial harvests.Analysis of the database showed that increasing the number of harvests was associated with lower stocking densities, the use of larger ponds, longer cultivation periods, larger final weight of shrimp and total production. Equivalence tests showed that the models adequately fitted the primary data. Monte Carlo simulations indicated that improving management by controlling stocking density and the duration of cultivation increased mean production from 981 to 2573 kg/ha (one partial harvest), from 1808 to 3602 kg/ha (two partial harvests) and from 1364 to 3834 kg/ha (three partial harvests), closely approaching the yields reported in the database. When conducting one and three partial harvests, improved management increased production and the certainty in obtaining the crops, as indicated by diminishing values of the coefficient of variation in output probability distributions.When conducting two partial harvests, however, improved management increased yields, but also increased uncertainty because there was a lower control on production parameters. This does not necessarily imply more uncertainty when conducting two harvests, but that at this stage of knowledge, the primary data only allows detecting limited control on production. Results of a preliminary economic evaluation showed that net revenues ranged from USD$ 2361.1-3488.9, the benefit-cost ratio from 1.47 to 1.62 and that the best and worse results were obtained by conducting two and one partial harvests. We conclude that the models are useful for analysing uncertainty of semi-intensive shrimp production incorporating partial harvesting.

This study uses a stochastic bioeconomic approach to estimate the COVID-19 pandemic economic impact on shrimp farming in Mexico. Seeding-harvesting schedules — March–June, May–August, and August–November — were analyzed using shrimp prices and production costs corresponding to 2017–2019 (pre-pandemic) and 2020 (pandemic). The analyses estimated net revenue varied within 597.97–2758.88 USD$ ha −1 and 1262.40–1701.32 USD$ ha −1 under the pre-pandemic and pandemic scenarios, respectively. Significant decreases (38%) were estimated in net revenue values in March–June and May–August under the pandemic scenario. However, probability distributions estimated that uncertainty on the expected net revenues was not affected by the pandemic conditions, and the probability of losing was null or negligible in all the cases. Unfavorable conditions under the pandemic also required significantly higher break-even production for March–June (25.7%) and May–August (28.5%) schedules. The cost of post-larvae was the most important economic factor influencing net revenue. To conclude, although the operating conditions during the pandemic were conducive to worsening the economic outcome, no evidence still exists that uncertainty and economic risk increased compared with pre-pandemic conditions.

An analysis was conducted on semi-intensive production of a commercial farm of white shrimp (Litopenaeus vannamei) to establish recommendations for production improvement, considering the influence of environmental and management variables on growth and survival. For this purpose the records obtained of a production cycle. A variance analysis was conducted to confirm significant differences in environmental variables among ponds. The following relationships were determined: 1) environmental variables with management variables and 2) environmental and management variables with the production parameters (final weight and final survival). Subsequently, simple linear regression models were estimated between the variables related to the production parameters to conduct sensibility analysis by simulation. The analysis of variance showed statistically significant differences (P < 0.05) in temperature and dissolved oxygen concentrations among ponds. The correlation analyses between environmental and management variables showed that the final weight was positively related to temperature and dissolved oxygen and inversely proportional to the stocking density and duration of cultivation (P < 0.05). Survival was negatively correlated with pond size (P < 0.05). Sensibility analysis by simulation showed that variability of dissolved oxygen affected the final production more than other variables, as it increased from 1.521 kg ha-1 to 2.429 kg ha-1. The remainder variables in order of importance were: temperature, duration of cultivation, amount of feed, stocking density and pond size, respectively. Within the ranges tested, higher levels of dissolved oxygen, appropriate stocking densities and small pond size could substantially improve the production in semi-intensive Litopenaeus vannamei shrimp farms.