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A time-dependent, size-structured, bioenergetically based model was developed to examine the growth dynamics of Antarctic krill Euphausia superba 2 to 60 mm in size. The metabolic processes included in the model are ingestion, a baseline respiration, respiratory losses due to feeding and digestion, and an activity-based respiration factor. The total of these processes, net production, was used as the basis for determining the growth or shrinkage of individuals. Size-dependent parameterizations for the metabolic processes were constructed from field and laboratory measurements. Environmental effects were included through time series of pelagic phytoplankton concentration that were derived from data sets collected west of the Antarctic Peninsula. Simulated growth rates during the spring and summer for all brill size classes were consistent with published growth rates; however, initial results indicated that winter shrinkage rates were too large. Although the use of a seasonally varying respiration activity factor (reduced winter respiration rates) resulted in winter shrinkage rates of adults that were consistent with observations of experimentally starved individuals, the annual change in length of specific size classes was still inconsistent with observations. Subsequent simulations examined the effect of ingestion of sea ice algae by krill in the late winter and early spring. The annual growth cycle best matched observations, particularly those for larval and subadult krill (<35 mm), when reduced winter respiration rates and ingestion of sea ice algae were both included. These results suggest that the ability of krill to exploit a range of food sources and reduced winter metabolism rates are the mechanisms that allow krill to successfully overwinter. The need for additional observations of krill physiological processes, especially during winter, is clearly indicated.

Original Publication Citation

Hofmann, E.E., & Lascara, C.M. (2000). Modeling the growth dynamics of Antarctic krill Euphausia superba. Marine Ecology Progress Series, 194, 219-231. doi: 10.3354/meps194219