JPR Advance Access originally published online on November 25, 2005
Journal of Plankton Research 2006 28(1):87-101; doi:10.1093/plankt/fbi102
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Growth and development of Neocalanus flemingeri/plumchrus in the northern Gulf of Alaska: validation of the artificial-cohort method in cold waters
Institute of Marine Science, University of Alaska, Fairbanks, AK 99775-7220, USA
* Corresponding Author: hopcroft{at}ims.uaf.edu
Received June 16, 2005; accepted in principle August 25, 2005; accepted for publication November 14, 2005; published online November 25, 2005
Communicating editor: R.P. Harris
In situ growth and development of Neocalanus flemingeri/plumchrus stage C1–C4 copepodites were estimated by both the artificial-cohort and the single-stage incubation methods in March, April and May of 2001–2005 at 5–6°C. Results from these two methods were comparable and consistent. In the field, C1–C4 stage durations ranged from 7 to >100 days, dependent on temperature and chlorophyll a (Chl a) concentration. Average stage durations were 12.4–14.1 days, yielding an average of 56 days to reach C5, but under optimal conditions stage durations were closer to 10 days, shortening the time to reach C5 (from C1) to 46 days. Generally, growth rates decreased with increasing stage, ranging from 0.28 day–1 to close to zero but were typically between 0.20 and 0.05 day–1, averaging 0.110 ± 0.006 day–1 (mean ± SE) for single-stage and 0.107 ± 0.005 day–1 (mean ± SE) for artificial-cohort methods. Growth was well described by equations of Michaelis–Menten form, with maximum growth rates (Gmax) of 0.17–0.18 day–1 and half saturation Chl a concentrations (Kchl) of 0.45–0.46 mg m–3 for combined C1–3, while Gmax dropped to 0.08–0.09 day–1 but Kchl remained at 0.38–0.93 mg m–3 for C4. In this study, in situ growth of N. flemingeri/plumchrus was frequently food limited to some degree, particularly during March. A comparison with global models of copepod growth rates suggests that these models still require considerable refinement. We suggest that the artificial-cohort method is the most practical approach to generating the multispecies data required to address these deficiencies.
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