Modelling multi-nutrient interactions in phytoplankton; balancing simplicity and realism

被引:108
作者
Flynn, KJ [1 ]
机构
[1] Univ Coll Swansea, Ecol Res Unit, Swansea SA2 8PP, W Glam, Wales
关键词
phytoplankton; model; Monod; quota; Droop; nutrient; light; temperature; nitrogen; phosphorus; silicon; iron; NPZ; multiple nutrient;
D O I
10.1016/S0079-6611(03)00006-5
中图分类号
P7 [海洋学];
学科分类号
0707 ;
摘要
Modelling multi-nutrient interactions in phytoplankton growth is considered in the context of balancing the level of complexity with the adequacy of output for ammonium, nitrate, P, Si, Fe, temperature and light limitations. Phytoplankton submodels for placement in ecosystem simulators should be capable of producing a believable output. This requires not only a realistic growth rate response to limiting nutrients but also a realistic consumption of non' or lesser limiting nutrients. The Monod structure, and allies, fails these requirements. The complexity of the Droop version of the quota model is not matched by flexibility, especially for the description of Si assimilation. A normalised version of the Caperon-Meyer quota model is a better (and no more expensive) structure that, by the addition of a feedback controlled uptake equation and a Monod-type Si assimilation control, gives considerable flexibility at reasonable computational cost. Once the step is taken to include one complex mechanistic component there is considerable advantage to be gained from adding further mechanistic structures with little more cost in integration time. This is especially so for light-iron interactions. Overly simplistic models should not be used just because they offer advantages in computational costs at the expense of realism, even if they give satisfactory fits to a particular data set, as output is more likely to be erroneous in 'what-if' scenarios and also during simulation of data-poor periods of extant data series. (C) 2003 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:249 / 279
页数:31
相关论文
共 94 条
[1]  
Andersen Valerie, 1998, Bulletin de la Societe Royale des Sciences de Liege, V67, P3
[2]   An optimization-based model of iron-light-ammonium colimitation of nitrate uptake and phytoplankton growth [J].
Armstrong, RA .
LIMNOLOGY AND OCEANOGRAPHY, 1999, 44 (06) :1436-1446
[3]   Towards a mechanistic model of plankton population dynamics [J].
Baird, ME ;
Emsley, SM .
JOURNAL OF PLANKTON RESEARCH, 1999, 21 (01) :85-126
[4]  
BANSE K, 1976, J PHYCOL, V12, P135
[5]   TESTING THE MICROBIAL LOOP CONCEPT BY COMPARING MESOCOSM DATA WITH RESULTS FROM A DYNAMICAL SIMULATION-MODEL [J].
BARETTABEKKER, JG ;
RIEMANN, B ;
BARETTA, JW ;
RASMUSSEN, EK .
MARINE ECOLOGY PROGRESS SERIES, 1994, 106 (1-2) :187-198
[6]   Photoacclimation and nutrient-based model of light-saturated photosynthesis for quantifying oceanic primary production [J].
Behrenfeld, MJ ;
Marañón, E ;
Siegel, DA ;
Hooker, SB .
MARINE ECOLOGY PROGRESS SERIES, 2002, 228 :103-117
[7]   PHYTOPLANKTON-BACTERIA INTERACTIONS - AN APPARENT PARADOX - ANALYSIS OF A MODEL SYSTEM WITH BOTH COMPETITION AND COMMENSALISM [J].
BRATBAK, G ;
THINGSTAD, TF .
MARINE ECOLOGY PROGRESS SERIES, 1985, 25 (01) :23-30
[8]   UNSTEADY CONTINUOUS CULTURE OF PHOSPHATE-LIMITED MONOCHRYSIS-LUTHERI DROOP - EXPERIMENTAL AND THEORETICAL-ANALYSIS [J].
BURMASTER, DE .
JOURNAL OF EXPERIMENTAL MARINE BIOLOGY AND ECOLOGY, 1979, 39 (02) :167-186
[9]   NITROGEN-LIMITED GROWTH OF MARINE PHYTOPLANKTON .1. CHANGES IN POPULATION CHARACTERISTICS WITH STEADY-STATE GROWTH-RATE [J].
CAPERON, J ;
MEYER, J .
DEEP-SEA RESEARCH, 1972, 19 (09) :601-+
[10]   An empirical model of the phytoplankton chlorophyll:carbon ratio - The conversion factor between productivity and growth rate [J].
Cloern, JE ;
Grenz, C ;
VidergarLucas, L .
LIMNOLOGY AND OCEANOGRAPHY, 1995, 40 (07) :1313-1321