A stochastic approach for analysis of the influence of white spot disease, zootechnical parameters, water quality, and management factors on the variability of production of shrimp Litopenaeus vannamei cultivated under intensive commercial conditions

Abstract

We investigated the variability of shrimp Litopenaeus vannamei production by incorporating stochastic elements into deterministic stock models and determined the contribution that white spot disease, zootechnical parameters, water quality, and alternative management strategies have on variability. The model was calibrated for intensive shrimp cultivation in the State of Nayarit, Mexico. Mean annual production increased as a consequence of improved management from 8000 kg ha−1 to 22,000 kg ha−1 when cultivation was not affected by the disease and from 3200 kg ha−1 to 10,400 kg ha−1 when the disease affected production. When simultaneously considering both cases, mean annual production increased from 6300 kg ha−1 to 16,800 kg ha−1. White spot disease was a major factor determining variability of production. Shrimp production was particularly sensitive to levels of dissolved oxygen when Management was inadequate, while final weight and mortality rate of shrimp were more sensitive when Management improved. Water temperature and salinity had intermediate importance, and mortality caused by the disease and the time when mortality occurred had intermediate or low relevance. Improving management increased shrimp production and diminished variability. The duration of cultivation and stocking density were the most important management variables controlling variability of production when cultivation was affected by the white spot disease. When the disease was not present, pond size and duration of cultivation were the main factors affecting production. Starting time of aeration had relatively lower importance in determining variability, while the stochastic values of dissolved oxygen, in contrast, became most important. These results call for studies on improving aeration management to reduce variability of dissolved oxygen in ponds.