Effect of turbulence on feeding of larval fishes: a sensitivity analysis using an individual-based model

Authored by S Hinckley, BA Megrey

Date Published: 2001

DOI: 10.1006/jmsc.2001.1104

Sponsors: United States National Oceanic and Atmospheric Administration (NOAA)

Platforms: No platforms listed

Model Documentation: Other Narrative Flow charts Pseudocode Mathematical description

Model Code URLs: Model code not found

Abstract

Recent research has shown that turbulence can be important in the feeding of larval fishes. The interplay of turbulence with other important factors affecting larval feeding and growth rates is less known because of the difficult problems associated with multi-factor in situ experiments. We use an individual-based model (IBM) of the early life stages of walleye pollock (Theragra chulcogramma) to examine the sensitivity of growth and mortality to turbulence. This probabilistic and mechanistic model follows individual fish through the egg, yolk-sac larvae, feeding larvae, and juvenile stages, and includes development, behaviour, feeding, bioenergetics, and growth for each life stage. Biological processes are driven by physical factors (temperature, salinity, and turbulence) derived from a companion hydrodynamic model and configured for environmental conditions prevalent in 1987. A foraging submodel explicitly incorporates the effect of turbulence, prey density, and larval size. Monte Carlo simulations using Latin Hypercube Sampling methods were used to perform a sensitivity analysis. The error analysis examines the relative importance of various feeding-related factors on larval growth and mortality. Model results conform to wind-induced turbulence/contact-encounter rate theory with maximum consumption rates occurring at windspeeds of 7.2 m s(-1). Reactive distance, minimum pursuit time, and weight-length conversion parameters were the most important input parameters affecting the turbulence-consumption processes. The rank order of important input parameters shows that the weight-length conversion power coefficient and reactive distance (directly through the reactive distance-length proportionality coefficient) were two factors that influenced the largest number (17 out of 24) and largest percentage (71\%) of output variables. Feeding depth was ranked third, influencing 50\% of the output variables. Our results show that smaller and younger larvae are more sensitive to turbulent effects than are larger and older larvae.

Tags

Phytoplankton Environments Plankton contact rates Encounter rates Small-scale turbulence Theragra-chalcogramma Walleye pollock Pacific-ocean Dome-shaped relationship Gulf-of-alaska