| Summary: | Newly hatched Atlantic cod (Gadus morhua) larvae face an uncertain future when they first enter their marine pelagic habitat. Prior to complete yolk absorption, the larvae will have to find food. This process includes the visual encounter, pursuit and attack, and capture and digestion of the prey item for utilization to meet energetic demands for metabolism and growth. However, food is not always easy to find and it is essential for larval survival that they encounter habitats where prey are abundant, and that the prey are of edible size. Fast growth ensures short time as small vulnerable larvae in a marine habitat consisting of numerous predators. This thesis emphasizes the use of individual-based models to explore and understand the various mechanisms that determine successful growth and survival through the early pelagic life stages of cod (Gadus morhua). We model larval feeding, growth, behavior, and survival, under various environmental settings at the spawning and nursery grounds along the coast of northern Norway and at Georges Bank located on the eastern coast of USA. Paper 1 focuses on the assemblage of a mechanistic individual-based model (IBM) for larval and early juvenile cod, and the validation of the model by comparing observed and modeled data. Validation and forcing data consisted of biological and environmental data from a controlled environment (macrocosm). Larval cod are able to move up and down in the water column in a prescribed manner by following rules of behavior. Vertical behavior elevates larval growth rates, compared to growth achieved under random behavior. Maximum growth rates are achieved for larvae in environments where prey density exceeded 10 nauplii·L-1. The implementation of vertical behavior in IBMs of larval fish was elaborated in Paper 2. Strong gradients in pelagic horizontal currents create different dispersal patterns of larval fish at different depths. This will in turn have strong effects on the integrated survival, growth, and dispersal of larval fish. Adaptive traits ...
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