Exploring a first-principles based model of zooplankton respiration

Exploring a first-principles based model of zooplankton respiration T.T. Packard*†§, M. Gómez§ and M. Alcaraz*. *Instituto de Ciencias del Mar, Paseo Marítimo de la Barceloneta 37-49, 08003 Barcelona, Spain †Bigelow Laboratory for Ocean Science, W. Boothbay Harbor, Maine 04575, USA §Biological Oceanography Laboratory, Facultad de Ciencias del Mar, Universidad de Las Palmas de Gran Canaria, Campus Universitario de Tafira., 35017 Las Palmas de G.C., Canary Islands, Spain. This is a contribution from ICM-CSIC, BLOS, ULPGC, the projects: MICROROL (CICYT CTM2004-02757/MAR), MODIVUS (CTM200504795/MAR), OITHONA (CTM2007-60052). But the MTE only predicts respiration when the food supply is adequate! Senescence respiration can’t be predicted (Fig. 3)! Comparing Figs. 1 and 3 shows that clearly. How can your model predict respiration when food is scarce and respiration falls? Note parallelism in Fig. 3 between decreases in respiration and pyruvate (food source) during hour 10 to 13. Something in the food limits respiration. That’s our hypothesis! Since enzymes control respiration, that “something” is the enzyme’s substrates (Fig.4). Consequently, we argue that a respiration model should incorporate a Michaelis-Menten expression (Fig.5). Figs. 1 & 2. Modeling respiration from bisubstrate enzyme kinetics is feasible in Bacteria (1). For zooplankton, should we adapt this model or the MTE model? How does the MTE (Metabolic Theory of Ecology 2) do this? The MTE would predict respiration (R) by the following equation, R = i M0.75, where i is a stoichiometric factor and M is the biomass (Fig 3). Slide 1 Our model is: R0 = SVmax0/(Km + S), where Vmax0 is, the potential respiration (ETS). We use  rather than M0.75 because biomass just packages the ETS. The ETS is the real cause of respiration. Furthermore, the relationship between R and ETS is better and more direct than between R and M (Figs 6, & 7) . 0 25 50 010 20 30 Time (h) Measured Modelled PnPy260593 Respiration (mM O2 min-1) a Fig. 1 0 10 20 30 010 20 30 Time (h) Respiration (mM CO2 min1) PnPy100693 Measured Modeled Fig. 2 0 10 20 30 40 50 60 70 0 5 10 15 20 25 30 Time (h) Protein/5 (mg/L), Pyruvate x 3 (mM), R-measured & Rpredicted (mM O2/min) Measured Respiration Cell Protein MTE Predicted Respiration Nutrient (pyruvate) PnPy260593 Fig. 3 0 10 20 30 40 50 0 5 10 15 20 25 30 Time (h)  NADPH NADH b Fig. 4 0 30 60 010 20 30 TIME (h) M O2 min-1  Measured Respiration Enzyme Kinetic Model Predicted Respiration Fig 8 y = 0.4656x - 1.5603 R2 = 0.9846 0 50 100 150 200 0 100 200 300 400 Respiration (ml O2 h-1animal-  (ml O2 h-1 animal-1) Fig 7 y = 0.9414x - 0.3444 R2 = 0.9811 -3 -2 -1 0 1 2 3 -2 -1 0 1 2 3 Log () Log (Respiration) -3 -2 -1 0 1 2 3 -3 -2 -1 0123 Log (Dry Weight) Log (Respiration) y = 0.7565x + 0.1757 R2 = 0.9363 R = 1,5M0,76 Fig 6 This model transforms f (Time) into R = f (Time) (Fig 8).