Parameterizing plankton functional type models: Insights from a dynamical systems perspective

Journal of Plankton Research

Volumn 31, Issue 9, 2009, Pages 939-963

  Cropp, Roger ^a   Norbury, John ^b  

^a GRIFFITH UNIVERSITY   (Australia)

^b UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BIOGEOCHEMICAL CYCLE; CLIMATE CHANGE; CLIMATE EFFECT; ECOLOGICAL MODELING; GRAZING; GROWTH RATE; HEURISTICS; MARINE ENVIRONMENT; MORTALITY; NUTRIENT USE; PARAMETERIZATION; PHYTOPLANKTON; ZOOPLANKTON;

EID: 68849109616     PISSN: 01427873     EISSN: 14643774     Source Type: Journal    
DOI: 10.1093/plankt/fbp042     Document Type: Article

References (35)

1. Anderson, T. R. (2005) Plankton functional type modelling: running before we can walk? J. Plankton Res., 27, 1073-1081.
2. Anderson, T. R. (2006) Confronting complexity: reply to Le Quéré and Flynn. J. Plankton Res., 28, 877-878.
3. Billen, G. and Becquevort, S. (1991) Phytoplankton-bacteria relationships in the Antarctic marine ecosystem. Polar Res., 10, 245-253.
4. Cropp, R. A., Norbury, J., Gabric, A. J. et al. (2004) Modeling dimethylsulphide production in the upper ocean. Global Biogeochem. Cycles, 18, 1-21.
5. Dhooge, A., Govaerts, W. and Kuznetsov, Y. A. (2003) MATCONT: a Matlab package for numerical bifurcation analysis of ODEs. ACM Trans. Math. Soft., 29, 141-164.
6. Edwards, A. M. and Brindley, J. (1999) Zooplankton mortality and the dynamical behaviour of plankton population models. Bull. Math. Biol., 61, 303-339.
7. Edwards, A. M. and Yool, A. (2000) The role of higher predation in plankton population models. J. Plankton Res., 22, 1085-1112.
8. Falkowski, P., Laws, E. A., Barber, R. T. et al. (2003) Phytoplankton and their role in primary, new and export production. In Fasham, M. J. R. (ed.), Ocean Biogeochemistry. Springer, New York, pp. 99-121.
9. Fenchel, T. (1982) Ecology of heterotrophic microflagellates. IV. Quantitative occurrence and importance as bacterial consumers. Mar. Ecol. Progress Ser., 9, 35-42.
10. Flynn, K. J. (2003) Modelling multi-nutrient interactions in phytoplankton: balancing simplicity and realism. Prog. Oceanogr., 56, 249-279.
11. Flynn, K. J. (2006) Reply to Horizons article 'Plankton functional type modelling: running before we can walk' Anderson (2005): II. Putting trophic functionality into plankton functional types. J. Plankton Res., 28, 873-875.
12. Franks, P. J. S. (2002) NPZ models of plankton dynamics: their construction, coupling to physics, and application. J. Oceanogr., 58, 379-387.
13. Gabric, A. J., Matrai, P. A. and Vernet, M. (1999) Modelling the production and cycling of dimethylsulphide during the vernal bloom in the Barents Sea. Tellus, 51B, 919-937.
14. Gabric, A. J., Whetton, P. H. and Cropp, R. A. (2001) Dimethylsulphide production in the subantarctic southern ocean under enhanced greenhouse conditions. Tellus, 53, 273-287.
15. Gause, G. F. (1934) The Struggle for Existence. Williams and Wilkins, Baltimore.
16. Hansen, B., Christiansen, S. and Pedersen, G. (1996) Plankton dynamics in the marginal ice zone of the central Barents Sea during spring: carbon flow and structure of the grazer food chain. Polar Biol., 16, 115-128.
17. Hood, R. R., Laws, E. A., Armstrong, R. A. et al. (2006) Pelagic functional group modeling: progress, challenges and prospects. Deep-Sea Res. II, 53, 459-512.
18. Huang, X. C. and Zhu, L. (2005) Limit cycles in a general Kolmogorov model. Nonlinear Anal., 60, 1393-1414.
19. Hutchinson, G. E. (1961) The paradox of the plankton. Am. Nat., 95, 137-145.
20. Kolmogorov, A. N. (1936) Sulla Teoria di Volterra della Lotta per l'Esisttenza. Giorn. Instituto Ital. Attuari, 7, 74-80.
21. Le Quéré, C. (2006) Reply to horizons article 'phytoplankton functional type modelling: running before we can walk' Anderson 2005: I-abrupt changes in marine ecosystems? J. Plankton Res., 28, 871-872. doi:810.1093/plankt/fbl1014.
22. Le Quéré, C., Harrison, S. P., Prentice, I. C. et al. (2005) Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models. Global Change Biol., 11, 2016-2040.
23. May, R. M. (1973) Stability and Complexity in Model Ecosystems. Princeton University Press, Princeton.
24. Mitra, A. (2009) Are closure terms appropriate or necessary descriptors of zooplankton loss in nutrient-phytoplankton-zooplankton type models? Ecol. Model., 220, 611-620.
25. Mitra, A., Flynn, K. J. and Fasham, M. J. R. (2007) Accounting for grazing dynamics in nitrogen-phytoplankton-zooplankton models. Limnol. Oceanogr., 52, 649-661.
26. Moloney, C. L., Bergh, M. O., Field, J. G. et al. (1986) The effect of sedimentation and microbial nitrogen regeneration in a plankton community: a simulation investigation. J. Plankton Res., 8, 427-445.
27. Montes-Hugo, M., Doney, S., Ducklow, H. W. et al. (2009) Recent changes in phytoplankton communities associated with rapid regional climate change along the Western Antarctic Peninsula. Science, 323, 1470-1473.
28. Muller-Niklas, G. and Herndl, G. J. (1996) Dynamics of bacterioplankton during a phytoplankton bloom in the high Arctic waters of the Franz-Joseph Land archipelago. Aquat. Microb. Ecol., 11, 111-118.
29. Raick, C., Soetaert, K. and Gregoire, M. (2006) Model complexity and performance: how far can we simplify? Prog. Oceanogr., 70, 27-57.
30. Ruan, S., Ardito, A., Ricciardi, P. et al. (2007) Coexistence in competition models with density-dependent mortality. C. R. Biol., 330, 845-854.
31. Scheffer, M., Rinaldi, S., Huisman, J. et al. (2003) Why plankton communities have no equilibrium: solutions to the paradox. Hydrobiologia, 491, 9-18.
32. Slagstad, D. and Stole-Hansen, K. (1991) Dynamics of plankton growth in the Barents Sea. Polar Res., 10, 173-186.
33. Spitz, Y. H., Moisan, J. R. and Abbott, M. R. (2001) Configuring an ecosystem model using data from the Bermuda Atlantic Time Series (BATS). Deep-Sea Res. II, 48, 1733-1768.
34. Steele, J. H. and Henderson, E. W. (1992) The role of predation in plankton models. J. Plankton Res., 14, 157-172.
35. Vallina, S. M., Simo, R., Popova, E. E. et al. (2008) A dynamic model of ocean sulfur (DMOS) applied to the Sargasso Sea: simulating the dimethylsulfide (DMS) summer paradox. J. Geophys. Res. (Biogeosciences), 113, 1-23.