Growth Rate Variation and Larval Survival: Inferences from an Individual-Based Size-Dependent Predation Model
Creators:Rice, James A.
Miller, Thomas J.
Rose, Kenneth A.
Crowder, Larry B.
Marschall, Elizabeth A.
Trebitz, Anett S.
DeAngelis, Donald L.
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Citation:Rice, James A.; Miller, Thomas J.; Rose, Kenneth A.; Crowder, Larry B.; Marschall, Elizabeth A.; Trebitz, Anett S.; DeAngelis, Donald L. "Growth Rate Variation and Larval Survival: Inferences from an Individual-Based Size-Dependent Predation Model," Canadian Journal of Fisheries and Aquatic Sciences, v. 50, no. 1, 1993, pp. 133-142.
We used an individual-based Monte Carlo simulation model to explore how changes in the mean and variance of growth rates of individuals in a larval fish cohort interact with size-dependent predation to affect the number and characteristics of individual survivors. Small changes in initial cohort mean growth rate can change survival over the first 60 d of life 10- to 30-fold. But when variance in growth rate among individuals is high, survival can be substantially higher than expected from the initial mean cohort growth rate. Selection for faster-growing individuals becomes stronger with increasing variance and increasing predation rate. In some cases, >80% of the survivors may come from the upper 25% of the initial growth rate distribution, and the mean growth rate of the survivors may exceed twice the initial mean growth rate. When individual growth rates change from day to day rather than remaining constant, the contribution of atypical individuals is accentuated even further. Counterintuitively, most of the selection for faster-growing individuals happens only after the majority of mortality has already taken place. These results suggest that interactions between individual variability and selective mortality may have important cohort-level implications for survival in fishes.
This research was sponsored by the following agencies: Electric Power Research Institute under contract No. RP2932-2 (DOE No. ERD-87-672) with the U. S. Department of Energy, under contract No.DE-AC05-840R21400 with Martin Marietta Systems, Inc.; University of Wisconsin Sea Grant College Program and the state of Wisconsin through federal grant NA800AA-D-00086, Project RlLR-37; University of North Carolina Sea Grant College Program and the state of North Carolina through federal grant NA85AA-D-SG022, Project RlMER-12; NOAA South Atlantic Bight Recruitment Experiment (NAI6RG0492-01), Project RlSAB-4; and the North Carolina Agricultural Research Station. TJ.M. and E.A.M. were supported in part by EPRI Fellowships in Population Biology administered through the Sports Fishing Institute.
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