ICES mar. Sei. Symp., 197: 141-148. 1993

The importance of the DOC pool for estimates

George A. Jackson

Jackson, G. A. 1993. The importance of the DOC pool for primary production estimates. - ICES mar. Sei. Symp.. 197: 141-148.

Phytoplankton release of dissolved has important consequences for the planktonic ecosystem. Their effects can be compared with those expected at the rates of dissolved organic (DOC) release measured in field incubations. Calculated DOC release rates must be consistent with other incubation measurements, such as those for bacterial growth and for nitrate and ammonia uptake. In this paper, comparisons are made between these different sets of measurements, showing that there is no need for DOC excretion of more than 0.1 of net primary production to account for ecological effects. Furthermore, a simple model of DOC release during productivity measurements shows that grazing on and on during an incubation can also be important sources of fixed C loss.

George A. Jackson: Department of Oceanography, Texas A&M University, College Station, T X 77843, USA.

Introduction characterization of DOM has shown it to be quite different in concentration and composition from that In no other part of oceanography have there been as indicated by Sugimura and Suzuki (1988) and Suzuki et many reversals of opinion, doubts about techniques, and al. ( 1985) (Benner et al., 1992). There remains consider­ uncertainties about concentrations and rates as there able uncertainty about the real concentrations of DOC have been associated with dissolved organic matter and DON, but the area remains an active and exciting (DOM) and its constituents part of chemical oceanography (J. Hedges, in press). (DOC) and nitrogen (DON). The situation has not been DOM excretion by phytoplankton is important to the helped by the fact that DOM is a mixture of chemical understanding of algal physiology (e.g., Antia et al., compounds, most of which have not been identified. 1991). Williams (1990) has given a thoughtful overview Prior to about 1975, oceanic benthic regions were of phytoplankton DOM excretion and its ecological believed to use DOM to meet their metabolic needs consequences. Excretion affects estimates of primary (e.g. Craig, 1969; Menzel and Ryther, 1970). With the production rates and of nutrient uptake and is poten­ realization that there is rapid vertical transport of or­ tially important as a source of DOM for the large DOC ganic matter in relatively large, rapidly sinking particles and DON pools. such as fecal pellets (e.g. McCave, 1975; Deuser et al., Much of the biological interest in DOM has resulted 1981) and, more recently, , there was a loss from the realization that bacteria consume it at rates that of general interest in DOM. The recent development of are high relative to those measured for primary pro­ high temperature combustion techniques for measuring duction (e.g. Azam etal., 1983). The practice of present­ DOC and DON (Suzuki et al., 1985; Sugimura and ing bacterial production rates as a fraction of primary Suzuki, 1988) and the resulting associations that they production has tended to emphasize the role of ex­ observed with apparent oxygen utilization and nitrate cretion by algal cells, even to the point of suggested concentrations have brought DOM back to the attention elaborate interactions between chemotactic bacterial of the general oceanographic community. and algal cells (e.g., Azam and Ammerman, 1984). Higher concentrations of DOC and DON would re­ There are other possible sources. Williams (1981) noted quire profound changes in our understanding of the that large bacterial growth rates suggested DOM release distributions and fluxes of most biologically active ele­ by . Jumars et al. (1989) refocused interest ments (e.g., Jackson, 1988; Toggweiler, 1989). Recent on zooplankton and their feces as DOM sources by 142 G. A. Jackson IC ESm ar. Sei. Symp., 197 (1W3) noting that an animal's complete of dissolved (e.g., Marra et al., 1981; Smith, 1982; Williams, 1990), organic matter produced during digestion of its food is although Williams (1990) briefly considered the effects neither practical nor desirable. Other potential sources of as well. These studies noted that inter­ of DOM include the dissolution of . nal phytoplankton DOC pools would slow the initial The measurement of phytoplankton uptake of nitro­ release of labeled DOC during a 14C incubation. gen compounds could be affected by DON release. This article examines, first, how large algal excretion Uptake is usually measured by the accumulation of needs to be consistent with other properties of plank- material containing 15N in the particulate phase after a tonic ecosystems and, second, what the manifestation of timed incubation. Unfortunately, much of the l5N tracer such excretion would be in a bottle. cannot be found after the incubation. This has been observed when the compounds were ammonia (Glibert et al., 1982), urea (Hansell and Goering, 1989), and nitrate (Ward etal., 1989). If the missing tracer is taken Studies of whole ecosystems up, incorporated into organic compounds, and released, it can represent an important part of the tracer uptake Observations of DOC disappearance which is not included in the uptake calculations. Bronk Kirchman etal. (1991) have recently measured observed and Glibert (1991) have recently developed a technique disappearance rates for DOC in seawater samples col­ of measuring DON excretion by using 15N tracer tech­ lected as part of the JGOFS program. They measured niques. A comparison of estimated DON release rates DOC concentrations in water samples several days after yielded values ranging from 54 to 260% of estimated their collection using the technique of Sugimura and ammonia uptake rates. These large values suggest that Suzuki (1988). DOC disappearance rates varied, but technique cannot yet provide the information needed to were as high as 0.36 d” 1 over a day for initial DOC determine the fate of the missing l5N tracer. concentrations of 178 //M, equivalent to a decrease of Sharp (1977) noted that methods commonly used to DOC equal to 64,mM. Such high rates of DOC consump­ assess DOC production were subject to several artifacts tion should be matched by equally high rates of 0 2 which could give artificially high rates of DOC ex­ consumption. If the 0 2 to DOC consumption ratio is 1, cretion. Typical excretion rates were calculated from then the associated 0 2 concentration decrease in the measurements of radioactivity present in the filtrate environment should be 64 /

Analysis of ecosystem data Incubation model Estimates of organic matter excretion should be consist­ This model is designed to show the relationships be­ ent with other measured properties of a system. These tween measured quantities and planktonic processes might include rates of net particulate production, bac­ occurring within an incubation chamber. The approach terial production, grazing rates for the different particle is similar to that taken in Jackson (1983) to describe the feeders, and estimates. Vézina and Platt (1988) effect of zooplankton grazing of the algae on production developed an approach, known as the inverse tech­ estimates. nique, that allowed them to use least-squares minimiz­ The typical phytoplankton production estimate is ation to estimate all of the flows in a planktonic food web made by measuring the amount of l4C tracer collected from whatever data were available. They applied their on a filter a set time after the tracer is added to the technique to data from the English Channel and from solution as I4C bicarbonate. A typical seawater sample the Celtic . In both cases, they found that the DOC contains an assemblage of organisms which includes excretion was the minimum value that they allowed, phytoplankton, bacteria, and grazers as well as DOM. 10% of the gross primary production. The amount of newly formed particulate carbon col­ Ducklow et al. (1989) applied a similar technique to lected on the filter is usually considered to represent the data from warm core rings found off the East Coast of primary production. This ignores organic matter pro­ the United States but did not include DOC or DON duced and then excreted by the algae as well as grazing production in detritus. Because DOC and DON feed the effects. Such organic matter is in the filtrate as DOC bacteria, this omission stopped bacteria from feeding on and, possibly, as bacterial biomass. Excreted primary detrital matter. Their results showed no DON leakage production has been estimated by acidifying and then by phytoplankton for two of three data sets, although bubbling the filtrate to drive off inorganic 14C. 17% of total phytoplankton nitrogen uptake was Because the different carbon pools - the phyto­ excreted in the third. They found high DOC release , the DOC, and the bacteria - have different rates during the two months when there was no DON concentrations and different time constants, they are release (20 and 54% of total primary production) and affected differently by incubation conditions. The fol­ low DOC release when there was high DON release (5% lowing models show some of the relationships between of total primary production). These DOC and DON total primary production and quantities measured after release rates are inconsistent and may result from not an incubation. including detritus as an alternative source of DOM for bacterial growth. Jackson and Eldridge (1992) used the inverse tech­ nique to describe a planktonic food web off Southern Basic model California for which phytoplankton and bacterial pro­ Changes in the phytoplankton carbon concentration P duction measurements were available. They estimated are assumed to be determined by phytoplankton growth phytoplankton excretion rates at 10% of the phyto­ at a constant specific growth rate n and loss at a constant plankton particulate production. Almost half of the grazing rate y: DOC and DON needed to supply bacterial growth came from dissolution of detritus, with most of the rest coming from grazer excretion. f = ^P-yP (i) Hagström et al. (1988) reached a similar conclusion in the Mediterranean Sea, where they suggested that ex­ cretion of 12% of the particulate production could Similarly, the concentration of dissolved organic car­ sustain their measured bacterial populations. bon D is determined by phytoplankton excretion and by Model studies of plankton food webs also suggest that bacterial uptake at a rate proportional to D and bacterial large rates of DOC excretion by phytoplankton are not concentration B: necessary to account for observed bacterial growth rates (Taylor and Joint, 1990). — = a^P - bDB (2) Thus, analyses of field data on planktonic food webs dt which included bacterial growth rates have concluded that phytoplankton leakage need be only a small fraction where a is the excretion rate, expressed as the fraction of of the organic matter consumed by bacteria (Vézina and the growth rate, and b is the DOC uptake rate constant. Platt, 1988; Jackson and Eldridge, 1992). The exception Note that excretion is not included in the definition of,«. was the case where the important path from detritus was Changes in bacterial concentrations depend on bacterial not considered. growth efficiency c and rate of bacterivory d 144 G. A. Jackson ICES mar. Sei. Symp.. 197 (1993) dB Substitution of Equation (10) into Equation (5) and = cbBD - dB (3) dt solving for B* yields

The amount of material produced during the incu­ B* - Bn 1 cD()(eD() B0 . B'l r ~dt bation can be expressed by modifying Equations (1)- cD() (3): (12)

dP* For this case, total production is simply — = /

TP = (1 + a)//P dt (7) No grazing

The amount of production retained on a filter FP If there is no grazing in the system, then y = d = 0. depends on the ability of the filter to retain bacteria as Integrating Equation (1) yields well as algae. If the filter retains bacteria and algae and if -/a the grazers have a negligible amount of labeled carbon, P = P(,e (16) then FP = FPpb = P* + B*; if the filter retains only algae, then FP = FPp = P*. If DOC* is included, then Substituting this into Equation (4) and integrating the observed production is UP = P* + B* + D*. yields

P„(e^'t - 1) (17) Solutions for different conditions If the sample was at steady state when removed from Steady state the ocean, then Equation (9) can be used to eliminate b If the total concentrations of phytoplankton, DOM, and from the equations. Again using P0 and,« to normalize bacteria are constant and equal to their initial concen­ the equations, but now tracking the total normalized trations Po, Do, and B(), as could occur if the system were algal, DOC and bacterial concentrations Pt , Dt, and By at steady state, then the system is described by

P | = er (18) D = = — (8) 0 b B„ ca^ P' = er - 1 (19) B _ a// P(, _ ca^Pp dD j a (9) — aP r — DTBX (20) 0 b D„ d dr B0D() dry = aP4 rD'Br (21) Integrating Equation (4) for P* assuming that y = n dr B||D,, yields dB | _ ac D i Bt (22) dr BÔDÔ P* = P„(l - e - "') ( 10) dB' _ ac D'B'r (23) dr BqD,', Solving Equation (5) for D* yields Equations (20)-(23) do not lend themselves to simple D* = D(,(l — e~bB|,t) ( 11) analytical solutions but can be solved numerically. ICES mar. Sei. Symp.. 197 ( 1993) The DOC pool for primary production estimates 145

Discussion of model results 0.9 The simulations, expressed in the normalized forms, are ^3_ OC 0.8 functions of only five parameters: Bo, Dû, a, c, and z. 0.7 C3 The values of the other rate constants are determined by (—* 0.6 these. Values for two of the parameters, a and c, are not I o-5 very variable. As discussed above, estimates for a range o 0.4 o 0.3 from 0.1 to 0.3; estimates of c are 0.5 to 0.7 (e.g., Payne, ° 0.2 1970). Probably the most poorly known values are those for B(> and D('>. (Note that these are set by the different rate constants, as in Equations (8), (9).) 0.9 When bacterial concentration is small and DOC and 0.8 algal concentrations the same, little of the labeled pro­ 0.7 duction goes to the bacteria (Fig. 1A). Labeled DOC UP1 0.6 takes longer to reach its steady-state concentration than 0.5 labeled algae. However, respiration and grazer con­ sumption of labeled carbon very rapidly decreases the 0.4 amount of fixed carbon which can be recovered, even if 0.3 the DOC is included (Fig. IB). Including bacteria has 0.2 0.5 2.5 little effect on production estimates. X Figure 2. Normalized concentrations (A) and production esti­ mates (B) as a function of normalized time r for D('> = 0.1, B,'i = 0.9 1, a = 0.1, and c = 0.5. This is a steady-state case where bacterial biomass is much greater than DOC, algal excretion ’S I °:? rate is 10% of particulatc primary production, and bacterial .N 3 0.6 uptake efficiency is 50%. Symbols as in Figure 1. 0.5 0.4 ° C 0.3 When bacterial and algal concentration are the same Z 3 0.2 and that of DOC small, more material appears in the bacterial compartment (Fig. 2A). However, this occurs at a much lower rate than it does for the algae. There is a 0.9 time-lag in the response of the bacteria as they must wait for the label to appear in the DOC pool first. The small 0.7 size of the DOC pool does allow material to appear in ü Ö the bacteria much sooner. Again, there is a rapid de­ Cl c 0 .6 crease in the production estimated from any of the ]u -2 0.5 UP' potential measurements (Fig. 2B). S ça 0.4 When excretion rate is larger, a = 0.3, and bacterial 0.3 uptake efficiency higher, c = 0.7, the relative size of the 0.2 0 0.5 1.5 2.5 bacteria component increases more rapidly but it is still only half that of the algae for the relatively long time of X when T = 3 (Fig. 3A). This is actually a long time. If the Figure I. Normalized concentrations (A) and production esti­ algae are growing at the fast rate of p = 1 d_1, this is mates (B) as a function of normalized time r for D» = 1. Bo = equivalent to 3 days. At this time the measured pro­ 0.1, a = 0.1, and c = 0.5. This is a steady-state case where bacterial biomass is a small fraction of DOC, algal excretion duction is about a third of the actual rate. rate is 10% of particulate primary production, and bacterial In the absence of grazing, algal concentrations in­ growth efficiency is 50%. Symbols: P' = labeled phytoplankton crease rapidly (Fig. 4A), whereas DOC and bacterial concentration relative to total algal concentration; D' = concentrations decrease more slowly. For BÔ = 1 and labeled DOC concentration relative to total algal concen­ tration; B' = labeled bacterial carbon concentration relative to D ('| = 0.1, the labeled bacterial concentration increases total algal concentration. In (B), primary production estimated quite slowly. The largest effect on productivity estimates from labeled algal concentration relative to actual algal pro­ is the overestimate of production relative to that of the duction (Fp = Fp/TP); primary production estimated from the natural population assumed to steady state (Fig. 4B). sum of labeled algal and bacterial concentrations relative to There are three effects which lower the estimate of actual algal production (Fph = Fph/TP); primary production estimated from the sum of labeled algal, bacterial and DOC phytoplankton production, FPp: excretion of fixed car­ concentrations relative to actual algal production (UP/TP). bon; bacterial respiration; grazing losses. As long as 146 G. A. Jackson ICES mar. Sei. Symp.. 197(1993)

excretion is a relatively small fraction of total pro­ 0.9 duction, as it is even when a = 0.3, most labeled C moves C 0.8 D'o= 0.1 through the phytoplankton. As such, a more careful ^ - 2■4—' 0.7 = 0.3 c3 = 0.7 consideration of grazing effects during an incubation u-> 0.6 should be at least as important as including the effects of Ii gs 0.4°-5 excretion for the measurement of net primary pro­ Z O 0.3 duction. In this model formulation, material lost to 0.2 grazers is not trapped on filters. A more complete model would include the grazing model of Jackson (1983). Larsson and Hagström (1979) made one of the more complete comparisons among primary production in particles larger than 3 um, which they assumed to be UP' phytoplankton cells, particles between 0.2 and 3 ^m, which they assumed to be bacteria, and filtrate passing a 0.2 nm filter, which they assumed to be exudate. The time course of carbon appearing in the different frac­ tions showed the general patterns noted above for small D,',: labeled DOC increased, but rapidly reached a 0.5 2.5 maximum; labeled algae took longer before slowing its X accumulation rate, and labeled bacteria increased slowly but maintained the same accumulation rate for 12 h. Figure 3. Normalized concentrations (A) and production esti­ mates (B) as a function of normalized time r for D,', = 0.1, B« = There are, however, several puzzling aspects to their 1, a = 0.3, and c = 0.7. This is a steady-state case where results. The initial increase rate for labeled DOC was bacterial biomass is much greater than DOC, algal excretion about 3^gC r' IT1 for 2 h. The similar rate for labeled rate is 30% of particulate primary production, and bacterial algae was about 4 fig C I-1 h” 1. Bacterial carbon uptake efficiency is 70%. Symbols as in Figure 1. increased at the slow rate of about 0.8 /

so Discussion T3 UP' P 1*O This model does not work well to reproduce fully the situation discussed by Larsson and Hagström (1979). The model may be faulty, the experiments may have artifacts, or both. Some of the model limitations have already been discussed. The experiments were flawed by not accounting for the potentially substantial contri­ 0 0.5 1.5 butions of cyanobacteria, algae small enough to slip through the filters and be considered as DOM (Larsson T Figure 4. Normalized concentrations (A) and production esti­ and Hagström, 1982). More work needs to be done. mates (B) as a function of normalized time x for D» = 0.1. B,', = This model does not help determine the fate of the l 5N 1, a = 0.1. and c = 0.5. This is a case with no grazing in the missing in the incubations to determine the uptake rates incubation bottle but with grazing leading to a steady state in of ammonia, nitrate, and urea. The rate at which ex­ the environment. Initial bacterial biomass is much greater than cretion accumulates in either DOC or bacteria is too DOC, algal excretion rate is 10% of particulate primary pro­ duction, and bacterial uptake efficiency is 50%. Symbols as in slow to account for the observed discrepancies of l5N. It Figure 1. is possible that those substances accumulate in organ- ICES mar. Sci. Symp.. 197 (1993) The DOC poo! for primary production estimates 147 isms, such as cyanobacteria or bacteria, that are not vironmental considerations. In Flows of energy and materials trapped on the GFF filters usually used. in marine ecosystems, pp. 345-360. Ed. by M. J. R. Fasham. The importance of grazing, which determines what Plenum Press, New York. Azam, F., Fenchel,T., Field, J. G., Gray, J. S., Meyer-Reil, L. fraction of production is present to be measured, A., and Thingstad, F. 1983. The ecological role of water- suggests that this could be a more important factor to be column microbes in the sea. Mar. Ecol. Prog. Ser., 10: 257- addressed than excretion. Ideally, both factors should 263. be addressed in fashion to the approach in Jackson Baines, S. B., and Pace, M. L. 1991. The production of dissolved organic matter by phytoplankton and its import­ (1983) and Smith (1982). ance to bacteria: patterns across marine and freshwater Results of this model do suggest the importance of systems. Limnol. Oceanogr., 36(6): 1078-1090. using short-term incubations to minimize the effects of Benner, R.. Pakulski, J. D., McCarthy, M., Hedges, J. I., and respiratory and grazing loss of labeled material. If the Hatcher, P. G. 1992. Bulk chemical characteristics of dis­ labeled carbon in both the filtrate and the particles is solved organic matter in the ocean. Science, 255: 1561-1564. Bronk, D. A., and Glibert, P. M. 1991. A lsN tracer method for measured, then there should be a minimal loss to bac­ the measurement of dissolved organic nitrogen release by teria or grazers. The definition of short incubations, as in photoplankton. Mar. Ecol. Prog. Ser., 77: 171-182. Jackson (1983), is in terms of /ut. Craig, H. 1969. Abyssal carbon and radiocarbon in the Pacific. This desire for short incubations contrasts with J. Geophys. Res., 74: 5491-5506. Deuser, W. G., Ross, E. H., and Anderson, R. F. 1981. Smith's (1982) conclusion that short incubation times Seasonality in the supply of sediment to the deep Sargasso were not good for estimating net primary production or Sea and its implications for the rapid transfer of matter to the DOC release rates because of time-lags introduced by deep ocean. Deep-Sea Res., 28: 495-505. isotopic equilibration of internal carbon pools. Ducklow, H. W., Fasham, M. J. R., and Vézina, A. F. 1989. Measurements of net primary production must manage Derivation and analysis of flow networks for open ocean plankton systems. In Network analysis in marine ecology, to be long enough for the phytoplankton to equilibrate pp. 159-205. Ed. by F. Wulff, J. G. Field, and K. H. Mann. with the isotope but short enough so that ecological Springer-Verlag, Berlin. interactions will not significantly alter concentrations. Fogg, G. E. 1983. The ecological significance of extracellular At best, measurements of complex systems are compro­ products of phytoplankton photosynthesis. Bot. Mar., 26: 3- 14. mises. Glibert, P. M., Lipschultz, F., McCarthy, J. J., and Altabet, M. A. 1982. Isotope dilution models of uptake and remineraliza­ tion of ammonium by marine plankton. Limnol. Oceanogr., 27: 639-650. Conclusions Hagström, Å., Azam, F., Andersson, A., Wiknet, J., and Rassoulzaadegan, F. 1988. in an oligotrophic Environmental data show no need for phytoplankton pelagic : possible roles of cyanobacteria excretion rates much greater than 10% of net particulate and nanoflagellates in the organic fluxes. Mar. Ecol. Prog. Ser., 49. primary production. Hansell, D. A., and Goering, J. J. 1989. A method for estimat­ Models of the effect of excretion and resulting ecosys­ ing uptake and production rates for urea in seawater using tem processing on calculated production rates show that [ C] urea and [ N] urea. Can. J. Fish, aquat. Sci., 46: 198— the least biased measurements are the shortest. Physio­ 202. logical considerations argue for longer measurements. Jackson, G. A. 1983. Zooplankton grazing effects on ,4C-based phytoplankton production measurements: a theoretical The best relationship between measured and environ­ study. J. Plankt. Res., 5: 83-94. mental production depends on the effects of grazing or Jackson. G. A. 1988. Implications of high dissolved organic non-grazing as well as on DOC excretion. matter concentrations for oceanic properties and processes. Oceanography, 1(2): 28-33. Jackson, G. A., and Eldridge, P. M. 1992. Food web analysis of a planktonic system off southern California. Prog. Ocean­ Acknowledgments ogr., 30: 223-251. Jumars, P. A., Penry, D. L., Baross, J. A., Perry, M. J., and This work was supported by Office of Naval Research Frost, B. W. 1989. Closing the microbial loop: dissolved Contract N00014 87-K0005 and US Department of carbon pathway to heterotrophic bacteria from incomplete ingestion, digestion and absorption in animals. Deep-Sea Energy grant DE-FG05-85-ER60341. Res., 36: 483-495. Kirchman, D. L., Suzuki, Y., Garside, C., and Ducklow, H. W. 1991. High turnover rates of dissolved organic carbon References during a spring phytoplankton bloom. Nature, 352: 612-614. Lancelot, C. 1983. Factors affecting phytoplankton extracellu­ Antia. N. J., Harrison, P. J., and Oliveira, L. 1991. The role of lar release in the Southern Bight of the North Sea. Mar. Ecol. dissolved organic nitrogen in phytoplankton nutrition, cell Prog. Ser., 12: 115-121. biology, and ecology. Phycologia, 30: 1-89. Larsson, U., and Hagström, Å. 1979. Phytoplankton exudate Azam, F., and Ammcrman, J. W. 1984. Cycling of organic release as an energy source for the growth of pelagic bacteria. matter by bacterioplankton in pelagic ecosystems: microen­ Mar. Biol., 52: 199-206. 148 G. A. Jackson ICES mar. Sci. Symp., 197 (1993)

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