The adaptive timing of diapause - A search for evolutionarily robust strategies in Calanus finmarchicus

ICES Journal of Marine Science

Volumn 57, Issue 6, 2000, Pages 1825-1833

  Fiksen, O ^a  

^a UNIVERSITY OF BERGEN   (Norway)

Author keywords

Calanus finmarchicus; Diapause; Genetic algorithm; Life history strategy; Phenolgy

Indexed keywords

ADAPTATION; DIAPAUSE; ECOLOGICAL MODELING; PHENOLOGY; ZOOPLANKTON;

CALANUS FINMARCHICUS; COPEPODA;

EID: 0034463519     PISSN: 10543139     EISSN: None     Source Type: Journal    
DOI: 10.1006/jmsc.2000.0976     Document Type: Conference Paper

References (21)

1. Circulation patterns in the North Atlantic and possible impact on population dynamics of Calanus finmarchicus
2. Seasonal dynamics of phytoplankton and Calanus finmarchicus in the North Sea as revealed by a coupled 1-D model
3. A Lagrangian ensemble model of Calanus finmarchicus coupled with a 1-D ecosystem model
4. Evolution of condition-dependent dispersal: A genetic-algorithm search for the ESS reaction norm
5. A model of optimal life history and diel vertical migration in Calanus finmarchicus
6. Genetic algorithms: Principles of natural selection applied to computation
7. The timing of copepod diapause as an evolutionarily stable strategy
8. Diapause in the marine copepod Calanus finmarchicus - A review
9. Ecology in Mare Pentium: An individual based spatio-temporal model for fish with adapted behaviour
10. Seasonal changes in respiration of copepodite stage V Calanus finmarchicus (Gunnerus)
11. The timing of life history events
12. Biological/physical simulations of Calanus finmarchicus population dynamics in the Gulf of Maine
13. Timing of entry into diapause: Optimal allocation to "growth" and "reproduction" in a stochastic environment
14. Phenology in Calanus finmarchicus; hypotheses about control mechanisms
15. An experimental study of the resting phase in Calanus finmarchicus (Gunnerus)
16. Coupling of an individual-based population dynamic model of Calanus finmarchicus to a circulation model for the Georges Bank region
17. Super-individuals: A simple solution for modeling large populations on an individual basis
18. Genetic algorithms and evolution