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MARINE ECOLOGY PROGRESS SERIES Mar Ecol Prog Ser Published March  Dynamic model of phytoplankton MARINE ECOLOGY PROGRESS SERIES Mar Ecol Prog Ser Published March  Dynamic model of phytoplankton

MARINE ECOLOGY PROGRESS SERIES Mar Ecol Prog Ser Published March Dynamic model of phytoplankton - PDF document

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MARINE ECOLOGY PROGRESS SERIES Mar Ecol Prog Ser Published March Dynamic model of phytoplankton - PPT Presentation

Box 775 Cambridge Maryland 216130775 USA ABSTRACT Acclimation of the photosynthetic apparatus to changes of irradiance temperature and nutrient availability involving regulation of the chlorophyll acarbon ratio g is a universal feature of all phytop ID: 34322

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is currently much more useful information on nitrogen distribution. our understanding the ocean global carbon cycle, phytoplankton cultures natural phytoplankton a concentration particulate or- (Banse 1977). samples that isolated from the water thus subject with bottle effects. information on bon ratio individual cells using fluorescence et al. et al. although there fluorescence yields carbon content not vary randomly. Rather it is al. 1995). limiting conditions. growth rate different conditions our previous dynamic description 1996) in simple regulatory rule. light absorption energy demand provides a metabolic that describes stable intermediate pigment different stable environmental high irradiance the rate light absorption exceeds the to assimilate availability may growth rate energy, leading in turn paper we analytical solution growth based internally consistent tained description is, our model a growth der et al. (1996). that they impose Nutrient saturated response curve (Jassby a saturating the measure we have use particulate carbon reflects cellular carbon concentration (Sukenik et limited within-strain carbon-specific photosynthesis algae and proportional to a con- chlorophyll-specific light sistent with observations that limited intraspecific organic carbon-specific and the carbon-specific photosynthesis light-saturated rate the irradiance the growth Irradiance curve intercepts our model, a variable can be limit on Growth rate by definition carbon concentration, directly pro- the growth the energetic using carbohydrates as a source carbon skeletons 1992). Substituting Eq. make the maximum achievable the duration al. 1989). day that be rearranged a complete chl a-specific response curve assume that growth irradiance variability can against irradiance, against the maximum potential conversion (Fig. both photosynthesis expressed as carbon- time. The versus the product unity. Finally, that a single curve describes the as a a For Fig shows that our model requires that different growth response curves. critical factor saturates growth. not allow maximum value balanced growth because down regulation model predicts that photosynthetic rate balanced growth maximum photosynthesis relationship holds The dependence on irradiance. that nutrient-limitation limit on Arrhenius equation temperature and maximum photosynthesis rate a reference tem- under nutrient-replete denotes nutri- an Arrhenius plot. Nutrient-replete conditions arisen. Irradiance was cosine detectors in that undoubtedly geometry. Again, used a least growth rate rate - exp(-a2 0 I)] (13) using the observed values variable p variable in phytoplankton We fit has the advantage one depen- one independent equation was shows that the identities should could be data even assumption that obtain a direct review). Second, sets have confidence in the procedure. Thus, the values these parameters. growth rate, prediction, based observations (Fig. 15 algal cyanobacterial species photoacclimation model amongst the by low high values. cyanobacteria, probably because harvesting pigments lowest val- resource-saturated growth rates model predicts that acclimated phytoplankton Ecol Prog 1984). Cul- under nutrient-replete limited conditions the nutrient- replete data (cf. Fig. Observed values values predicted the growth rate and the fit to nutrient-replete data al. 1985; knowledge, there studies that provide observations on nutrient chemostat cultures Published observa- nutrient-limited condi- values obtained growth rates light-saturated photosynthesis Temperature dependence data at growth temperatures. values predicted (Yoder 1979; using a data set K). (B) values of from irradiance (Yoder 1979; as in were based on the g C C (k 1271) X 10%) from to 220 pm01 photons m-' S-' There is good agreem.ent between observed and pre- dicted values consistent manifes- the abundance also vary al.: Dynamic by light harvesting into growth (Kana meter' that the plastoquinone the synthesis harvesting complex proteins (Escoubas a regulatory photosynthesis divided linear extrapolation irradiance curve between energy demand and photosynthesis (PC) tosynthetic electron transfer provides a irradiance increases. at low irradiance increases. growth rate the rate thus reduce pigment content high irradiance (Maxwell that the light-saturated pho- tosynthesis rate simple regulatory rule (parameterized compensating reductions to account growth rates (Figs. limitations in limitations in assumptions that the accuracy this section chlorophyll-specific initial constant under tion. Reductions nutrient-limitation may arise the light-harvesting ters (Kolber et Falkowski 1989) reduced quantum efficiency is effect in al. 1989). 2 within a more amongst varies less maximum value irradiances (Kana Thus, our assumption at odds This assumption increased under Consistent with concurrent increase trast, our model photoperiod. An in this assumption should day length predicted few studies a function the day length in rate increases day length, in growth than the percentage noted above, day length (Yoder 1979, al. 1993). the tem- the temperature responses can day (mean Chattonella antiqua high irradiance on growth intuitive conclusion growth rate light without a corresponding increase growth rate This occurs in our (0) results the car- without affecting growth rate apparatus. These apparatus, (2) these compo- third criterion growth rate. pigment con- high light). on irradiance that the decline at which light-limited in Fig. maintain 0 these intermediate these irradiances. How- becomes light-saturated that some other than 'optimal' behavior results example, one light from However, observations the speculated (Geider 1993). the light, nutrient have been 1987, Langdon growth rate), (11) summarize our either irradiance growth rate. rules arise a simple model that includes pigment content. not sufficient the assumptions chl a-specific response curve (indepen- growth temperature, irradiance or nutrient that temperature- nutrient-limitation only light-saturated photosynthesis assumption that considered. However, indicate that growth rate irradiance, tem- growth rate. suggests experiments that refine our pigment content using empirical recognized that lack precision. concluded that estimated from nutrient concentration, Despite success ratio (0) interspecific variabil- growth rates, fundamental design preclude large simple regulatory rules. does, in provide a framework interspecific variability primary productivity that knowledge as knowledge the appropriate parameter estimating phytoplankton biomass the appropriate parameter concentration (by 148: 187-200, from light recognize that This work was supported Research Council Council ( a''', )l dchl - - - p chpCC - Rch'chl dt For small values Substituting Eq. Note that the case the case Eq. (A7) obtain a result Identical to describes the irradiance under balanced growth chl a (chl a has the same dependence growth rate cellular respiration). that the the data at higher Geider et design and Geider et al. abstract quantities such harvesting components organic carbon the Geider can be al. (1996) This application to algal growth Determining the natural phytoplankton. Mar toadaptation and the continuous hght intensity on marine phytoplankton. D (1994) to community structure in size. 1 continuous light. J Vidergar-Lucas L (1995) the phytoplankton organic release light. J Plankton algal photoadap- J Plankton Growth rates plankton correlation with light intensity regulation Natl Acad Acad K (1985) Falkowski PG, (1985) Chlorophyll mass. J Plankton 7 715-731 Roche J (1991) Acclimation spectral irra- J 15.139-150 dissertation, Dalhousie Halifax, NS (1987) Light (1992) Respiration: taxation tion. In: Falkowski PG, biogeochemical cycles in the p 333-360 Quantitative phytoplankton RJ, Maclntyre HL, (1996) A Phaeodactylurn tricornutum RJ, Platt (1993) Photosynthetic the marine a 12.12 cycle J Plankton Pigment turnover in nutrient avail- the concept phytoplankton popula- tion. J Falkowski PG (1989) Nitrogen WJ, Guest T (1976) on marine Deep Sea