Ecophysiological responses of Litopenaeus vannamei were evaluated as functions of 1) salinity and animal size, 2) temperature and the animal's nutritive state, and 3) dissolved-oxygen concentration and animal size. Growth rate, routine metabolic rate, limiting oxygen concentration for routine metabolism, and marginal metabolic scope were determined for L. vannamei maintained and tested at salinities of 2, 10, and 28 ppt, all at 28 C. Routine metabolic rate (RMR) was not demonstrably dependent on salinity but decreased with increasing shrimp weight. Limiting oxygen concentration for routine metabolism (LOCr) was independent of shrimp weight up to 9 g; but, for larger shrimp, decreased with increasing weight. Marginal metabolic scope (MMS = RMR/LOCr) also decreased with increasing shrimp weight and was independent of salinity for shrimp weighing up to 9 g; but, like LOCr, MMS was dependent on salinity for larger shrimp. Growth rate was significantly less at 2 ppt than at 10 or 28 ppt, which gave similar growth rates. The effects of four temperatures (20, 24, 28, and 32 C) on growth, RMR, LOCr, and MMS were examined for fed and starved L. vannamei. Routine metabolic rate increased with increased temperature both for fed and starved shrimp. Marginal metabolic scope and growth appeared to be positively related and, at 20 C, seemed to induce a state of metabolic torpor. Data from the study of chronic effects of hypoxia (~2 mg O2 L-1) vs. normoxia (> 5 mg O2 L-1) on ecophysiological responses indicated that although low-DO environments can depress RMR and growth in L. vannamei, animals grown under hypoxic and normoxic conditions did not differ in their metabolic responses upon acute exposure to hypoxia, providing no evidence of acclimation to hypoxia in L. vannamei. Data from the above experiments were used to parameterize Ecophys.Shrimp, a computer simulation model of shrimp growth in time-varying environmental regimes. One unified model was able to simulate all my experiments; and, with only minimal adjustment of the model parameter MMSO, it also adequately simulated studies taken from the literature. Thus, Ecophys.Shrimp seems capable of realistically representing the ecophysiological dynamics of shrimp metabolism and growth in various culture systems.

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It is generally accepted that the Marginal Value Theorem (MVT) describes optimal foraging strategies. Some research findings, however, indicate that in natural conditions foragers not always behave according to the MVT. To address this inconsistency, in a series of computer simulations, I examined the behaviour of four types of foragers having specific foraging efficiencies and using the MVT and alternative strategies in 16 simulated landscapes in an ideal environment (no intra- and inter-species interactions). I used data on elk (Cervus elaphus) to construct the virtual forager. Contrary to the widely accepted understanding of the MVT, I found that in environments with the same average patch quality and varying average travel times between patches, patch residence times of some foragers were not affected by travel times. I propose a mechanism responsible for this observation and formulate the perfect forager theorem (PFT). I also introduce the concepts of a foraging coefficient (F) and foragers hub (), and formulate a model to describe the relationship between the perfect forager and other forager types. I identify situations where a forager aiming to choose an optimal foraging strategy and maximize its cumulative consumption should not follow the MVT. I describe these situations in a form of a mathematical model. I also demonstrate that the lack of biological realism and environmental noise are not required to explain the deviations from the MVT observed in field research, and explain the importance of scale in optimal foraging behaviour. I also demonstrate that smart foraging, which is a set of rules based on key ecological concepts: the functional response curve (FRC), satisficing, the MVT, and incorporates time limitations, should allow for fitness maximization. Thus, it should be an optimal behavior in the context of natural selection. I also demonstrate the importance of the FRC as a driver for foraging behaviors and argue that animals should focus more on increasing the slope of their FRC than on choosing a specific foraging strategy. Natural selection should, therefore, favor foragers with steep FRC. My findings introduce new concepts in behavioural ecology, have implications for animal ecology and inform wildlife management.