An analysis of factors effecting the growth of benthic microalgae following the decline of a surface phytoplankton bloom

Citation
An analysis of factors effecting the growth of benthic microalgae following the decline of a surface phytoplankton bloom

Material Information

Title:
An analysis of factors effecting the growth of benthic microalgae following the decline of a surface phytoplankton bloom
Creator:
Darrow, Brian P.
Place of Publication:
Tampa, Florida
Publisher:
University of South Florida
Publication Date:
Language:
English
Physical Description:
viii, 76 leaves : ill. ; 29 cm.

Subjects

Subjects / Keywords:
Algal blooms -- Florida ( lcsh )
Microalgae -- Florida ( lcsh )
Dissertations, Academic -- Marine Science -- Masters -- USF ( FTS )

Notes

General Note:
Thesis (M.S.)--University of South Florida, 2001. Includes bibliographical references (leaves 71-76).

Record Information

Source Institution:
University of South Florida
Holding Location:
Universtity of South Florida
Rights Management:
All applicable rights reserved by the source institution and holding location.
Resource Identifier:
028870245 ( ALEPH )
50704803 ( OCLC )
F51-00156 ( USFLDC DOI )
f51.156 ( USFLDC Handle )

Postcard Information

Format:
Book

Downloads

This item is only available as the following downloads:


Full Text

PAGE 1

AN ANALYSIS OF FACTORS EFFECTING THE GROWTH OF BENTHIC MICRO ALGAE FOLLOWING THE DECLINE OF A SURF ACE PHYTOPLANKTON BLOOM by 'vBRlAN P. DARROW A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science College of Marine Science University of South Florida December 2001 Major Professor: John J. Walsh Ph.D.

PAGE 2

Examining Committee : Office of Graduate Studies University of South Florida Tampa, Florida CERTIFICATE OF APPROVAL This is to certify that the thesis of BRIAN P DARROW in the graduate degree program of Marine Science was approved on November 14,2001 for the Master of Science degree. Majdi)h.lfessor :/J okh J Walsh Ph D. Ph.D.

PAGE 3

This work is dedicated to my parents, Leo and Stephanie Darrow, for their belief in my education from an early age. Though I have chosen my own path in life, the sacrifices and decisions they made on my behalf throughout my youth have allowed me the freedom to pursue my chosen field to the highest level.

PAGE 4

Acknowledgments This analysis would not have been possible without the fieldwork conducted during the Florida Shelf Lagrangian Experiment. Specifically, I would like to thank Rik Wanninkhof, Peter Ortner and Jia-Zhong Zhang for providing temperature, salinity, dissolved silica and phosphate data. I am indebted to Robert Masserini and Kent Fanning for the collection and analysis of seawater samples for nitrate and ammonium during FSLE-1 and FSLE-2. Gary Hitchcock, Gabe Vargo and Mary-Lynn Dickson provided the pigment, dissolved inorganic carbon and incident PAR data for the analysis. In addition, Gabe Vargo provided benthic microalgal biomass data from a previous study on the West Florida shelf. Finally, the technical assistance ofDwight Dieterle and the comments of Kent Fanning, Gabe Vargo and especially John Walsh were invaluable to the completion of this work.

PAGE 5

Table of Contents List ofTables 11 List ofFigures 111 Abstract Vll Introduction 1 Methods 5 Model description 5 Model initialization 25 Perturbation experiments 26 Results 33 Baseline 33 Nearshore DOC case 45 Enhanced diffusion case 51 Discussion 55 Conclusions 68 References 71

PAGE 6

Table 1 Tabl e 2 List of Tables Initial benthic param e ters Model parameters II 30 3 1

PAGE 7

List of Figures Figure 1. Location of the FSLE experiment on the West Florida shelf 3 Figure 2 Incident PAR at the ocean surface during the model's simulations 6 Figure 3. Initial phytoplankton and zooplankton fecal pellet Profiles 27 Figure 4 Initial DIC profile 27 Figure 5 Initial DOC profiles 28 Figure 6. Initial water-column nutrient profiles 28 Figure 7. Initial bacterial biomass 30 Figure 8. Initial DOC profile for the nearshore DOC case of the model 31 Figure 9. Surface chlorophyll concentrations during the baseline Simulation and the FSLE-1 study 35 Figure 10. Net photosynthesis and consumption in the surface waters of the baseline simulation 35 Figure 11. Near-bottom chlorophyll concentrations during the baseline simulation and the FSLE-1 study 36 Figure 12. Near-bottom ammonium concentrations during the baseline simulation and the FSLE-1 study 36 Figure 13. Near-bottom nitrate concentrations during the baseline simulation and the FSLE-1 study 37 Figure 14. Near-bottom DIC concentrations during the baseline simulation and the FSLE-1 study 37 Ill

PAGE 8

Figure 15. Figure 16. Figure 17. Figure 18. Figure 19. Figure 20 Figure 21. Figure 22 Figure 23. Figure 24 Figure 25. Depth integrated phytoplankton and bacterioplankton stocks during the baseline simulation Near-bottom labile DOC concentrations during the baseline simulation Near-bottom phosphate concentrations during the baseline simulation and the FSLE-1 study Near-bottom silicate concentrations during the baseline simulation and the FSLE-1 study Factors limiting the photosynthesis of phytoplankton in the surface waters of the baseline simulation Factors limiting the photosynthesis of phytoplankton in the near-bottom waters of the baseline simulation Benthic chlorophyll stocks integrated over the upper 1 em of the sediments during the baseline simulation compared to measurements made by G. Vargo (personal communication) in April 1993 (day 1) and July 1992 (day 86) Net photosynthesis of the benthic microfloral community during the baseline simulation, compared to consumption of the benthic diatoms Factors limiting the photosynthesis of the benthic microalgae during the baseline simulation Pore-water nutrient concentrations during the baseline Simulation Diffusive nutrient fluxes across the sediment/water interface during the baseline simulation iv 38 38 39 39 41 41 42 42 43 43 44

PAGE 9

Figure 26. Diffusive carbon fluxes across the sediment/water interface During the baseline simulation 44 Figure 27 Surface and near-bottom chlorophyll concentrations during the nearshore DOC case 46 Figure 28. Near-bottom nutrient concentrations during the nearshore DOC case 46 Figure 29. Surface and near-bottom DIC concentrations during the nearshore DOC case 47 Figure 30. Surface and near-bottom DOC concentrations during the nearshore DOC case 47 Figure 31. Depth integrated phytoplankton and bacterioplankton stocks during the nearshore DOC case 49 Figure 32. Factors limiting the photosynthesis of near-bottom Phytoplankton during the nearshore DOC case 49 Figure 33 Factors limiting the photosynthesis of benthic microalgae during the nearshore DOC case 50 Figure 34. Chlorophyll stocks integrated over the top 1 em of sediments during the nearshore DOC case 50 Figure 35. Chlorophyll stocks integrated over the top 1 em of sediments during the enhanced diffusion case 52 Figure 36. Pore-water nutrient concentrations during the enhanced diffusion case 53 Figure 37 Factors limiting the photosynthesis of benthic microalgae During the enhanced diffusion case 53 v

PAGE 10

Figure 38 Figure 39. Diffusive fluxes across the sediment/water interface during The enhanced diffusion case Diffusive carbon fluxes across the sediment/water interface During the enhanced diffusion case V l 54 54

PAGE 11

AN ANALYSIS OF FACTORS EFFECTING THE GROWTH OF BENTHIC MICRO ALGAE FOLLOWING THE DECLINE OF A SURF ACE PHYTOPLANKTON BLOOM by BRIAN P DARROW An Abstract of a thesis submitted in partial fulfillment of the requirements for the degree of Master of Science College ofMarine Science University of South Florida December 2001 Major Professor: John J. Walsh, Ph. D. v ii

PAGE 12

The West Florida continental shelf is an oligotrophic system for most of the year. An episodic chlorophyll plume often occurs on the northern portion of the shelf during the spring months. The fate of the plume's nutrients upon its decline in the late spring and early summer is unknown. Decreased chlorophyll levels and sustained nutrient stocks may be explained by sediment/water-column interactions, including the presence ofbenthic microalgae. A one-dimensional model of 16 state variables was constructed to simulate the decline of a surface chlorophyll bloom in the northeastern Gulf of Mexico as measured during the Florida Shelf Lagrangian Experiment (FSLE). Remineralized nutrients from the declining bloom were taken up by heterotrophic bacteria in the water-column and by benthic microalgae in the sediments. Perturbation experiments revealed that low light levels due to increased CDOM did not have significant effects on the benthic microfloral community, while increased diffusion coefficients at the sediment/water interface adversely effected the microphytobenthos. Date Approved: __ .:,__ __ _;_ ____________ Vlll

PAGE 13

Introduction The importance of benthic microalgae as primary producers in estuarine and other s hallow ecosystems has been known for some time (Macintyre eta!. 1996) Only recently however, have studies begun to show the impact of the microphytobenthos in continental shelf ecosystems (Cahoon and Cooke, 1992; Nelson e t al. 1999). In coastal w a ters cl e ar enough to allow sufficient light penetration to the sediment surface micro algae in the sediments can be expected to influence the exchange of nutrients at the sediment/water interface (Sundback eta!., 1991) On the oligotroph i c West Florida shelf, chlorophyll a concentrations in coastal nearshore waters are typically 1-2 )lg r1 and rarely exceed 0 3 )lg r1 seaward ofthe 40 m isobath (Steidinger 1973). Blooms o f the toxic dinoflagellate, Karenia br e vi s accounting for chloroph y ll a concentrations of2 to 30 )lg r1 (Vargo et al, 1987) may result from nitrogen excreted by Trichodesmium e rythra e m i n the central and southern portions of the shelf(Walsh & Steidinger, 2001) Near bottom blooms ofup to )lg r1 are thought to result from intrusions of slope water during upwelling favorable conditions (Walsh e t al., in pre parati o n) while chlorophyll plumes of up to 6 )lg r1 occasionally extending along the shelfbreak (Gilbes et al., 1996 ; Miiller-Karger e t al., 1991) in the spring follow increased nutrient loading on the northern shelfby the Apalachicola, Suwannee, Escambia Choctawhatchee, Mobile and Mississippi rivers.

PAGE 14

The decline of one such bloom occurred in April 1996, coinciding with the Florida Shelf Lagrangian Experiment (FSLE). FSLE-1 (figure 1) was conducted to study water mass movement, air-sea gas exchange and net biological production on the West Florida shelf (W anninkhof et al, 1997). During the experiment, a cluster of over 100 stations were occupied and a set of measurements (temperature, salinity, chlorophyll a, phaeopigments, NI4, N03, NOz, P04, Si04, DIC and Oz among others) were taken during April 1-18, 1996. Furthermore, stations in the same area were occupied in late June 1996 as part of the FSLE-2 experiment. This second set of observations included only temperature, salinity, NH4, N03 + NOz and Oz. Circulation patterns on the West Florida shelf are seasonal in nature (Weisberg et al., 1996). Model output indicates that average velocities may be minimal in April (Yang & Weisberg, 1999). In situ observations of a SF 6 water mass tracer (Wanninkhof et al., 1997) during FSLE indicate little or no net water movement. Given this lack of circulation in the study area, the fall-out and remineralized nutrients from the declining bloom must have remained on the shelf during FSLE-1. Previous measurements of benthic chlorophyll on the West Florida shelf (G. Vargo, personal communication) indicate a background average of 8.48 mg m-2 integrated over the top 1 em of sediment from nearshore out to the 30 m isobath in April of 1993. In July of 1992, sediment chlorophyll was an average of30.09 mg m-2 in the top 1 em of sediment out to the 30m isobath. Likewise, in the South Atlantic Bight, Nelson et al. ( 1999) measured -12.5 mg chi a m-2 integrated over the top 0.5 em of sediment at a 27m depth station in April 1996, compared to -35 mg chi a m-2 integrated over the top 0.5 em of sediment at the same station in late June 1996. It would, thus, appear that some 2

PAGE 15

31 30 29 27 26 25 -87 -86 85 :":"JIIi,:.:. .. -84 Longitude -83 -82 Figure 1 Location of the FSL E experiment on the West Florida shelf. 3 -81 ., ..,,

PAGE 16

mechanism, which limits the growth ofbenthic microalgae in the spring is alleviated in the summer. This work explores the factors that effect success ofbenthic microalgae under varying conditions. It makes use of a one-dimensional numerical model of 16 state variables: photosynthetically active radiation (PAR), vertical eddy diffusivity (k z ), dissolved inorganic carbon (DIC), nitrate, ammonium, phosphate, silicate diatom biogenic silica, total phytoplankton chlorophyll (POC), benthic microflora, fecal pellets, nitrifying bacteria, ammonifying bacteria, inert dissolved inorganic carbon (DOC) labile DOC and CDOC, to simulate the shelf environment over the course of the 86 days from the start ofthe FSLE-1 experiment to the end ofthe FSLE-2 experiment. 4

PAGE 17

Methods Model description The one-dimensional model consists of27 depth levels (ilz = 1 m) in the water column and one integrated benthic layer of 1 em thickness at the 27-m isobath near 29N, 84W on the West Florida shelf. Temperature and salinity profiles of the water column were taken from the FSLE-1 data set for the first fourteen days of the model and the FSLE-2 data set for day eighty-six Values of temperature and salinity were then interpolated at each depth interval for days fifteen through eighty-five. Average daily wind velocities were obtained for the same period from NOAA's Coastal Marine Automated Network (C MAN) station CDRF1located in Cedar Key FL. From these daily physical parameters, a coefficient of vertical eddy diffusivity (kz) is calculated for each depth interval from a turbulence closure scheme (Mellor & Yamada 1992) Daily photosynthetically active radiation (PAR) at the surface of the ocean was obtained for the first fourteen days of the model from shipboard observations during FSLE-1. These fourteen values were then repeatedly looped for the rest of the model, ie. incident PAR on day 15 was the same as on day 1, (Figure 2). These daily integrated totals are then dispersed as a sine function around solar noon (Kirk, 1994) to arrive at an incident PAR value (10 ) integrated over each time step. PAR at each depth interval (lz ) is calculated according to Beer s law of exponential decay, (1) 5

PAGE 18

60 50 '""' "0 40 "! E Ul '-' 30
PAGE 19

where k is an attenuation coefficient described by, k [ k ,z+ k, Jr(z)dz+ k, JrDOC(z)dz] (2) z Here, kw, kp and k
PAGE 20

oP at z = h, kz-= 0 az (3b) where his the depth of the water column. The other terms of eq. (3) are respectively, gross photosynthesis (limited by the availability of light, phosphorus, nitrogen, or silica), excretion of DOC through cell lysis, respiration of C02 grazing and sinking. As such, g1 \j/1 1 y1 and Wp represent the phytoplankton gross growth rate, excretion rate, respiration rate, grazing loss rate and settling rate, respectively. Within equation 3b, the influx of sand-attached phytoplankton to the upper 1 em of sediment is neglected Phytoplankton sinking from the water column are just allowed to accumulate in the near bottom water where they remain viable The gross photosynthesis (g2 ) of the benthic micro flora (M, g C m"2 ) is also limited by the availability of light at the sea bottom and phosphorus, nitrogen, or silica within pore waters of the sediment in the second term of oM oM -= kb-+ g2M-\j/2M-s2M-y2 M 8t az subject to the boundary condition aM at z = h = h + hm, k b -= 0 8z (4) (4a) where Kb represents a bioturbation coefficient which would allow for movement of microalgae within the sediments. Eq. (4), however is integrated over h to h+hm, the 1 em 8

PAGE 21

thickness of the surface sediment layer so that this term always equals zero in the model. The remaining terms of eq. ( 4) are similar to those of eq. (3). Just as no phytoplankton enter the sediments, none of the benthic micro flora leave. Of the specific biological rates (in units oft-1), g1,2 expand to non-linear, timedependent expressions, {min(Iz I Isat e(l-l zllsat)1 (NO J I {knitrate + NOJ} ), or ] gl,2 = I {kammonium NH 4 } ), (P04 I {kphosphate + P04} ), (SI04 I {ksilicate + SI04}) (5) where J..li is the maximal phytoplankton gross growth rate of 1.5 dai1 derived from a net one of 1.3 day -1 measured during FSLE-1 (Hitchcock eta!., 2000). I(z t) is the spectrally averaged PAR at depth. Isat is the saturation light intensity for each diatom group (pelagic and benthic) effecting photo-inhibition The ki are the respective MichaelisMenten half-saturation constants for uptake of nitrate, ammonium phosphate, and silicate. The maximal gross growth rate of sand microflora (J..l2 ) at J.!E m -2s -1 typical of the bottom light regime at 27m in the Georgia Bight (Nelson eta!., 1999), is 0.5 day -1 (Sundback & Graneli, 1988 ; Pinkney & Zingmark, 1993), assuming a Clchl ratio of 30 for the microflora instead of 45 for the planktonic diatoms, and respective respiration and excretion rates of 10% and 4%. Sinc e the minimal nutrient concentrations are s till five-fold less in the water column than in the sediment pore waters at the 27-30 m isobaths of the West Florida and 9

PAGE 22

Georgia shelves (Marinelli et al. 1998), the respective values of the half-saturation constants are assumed to be 0.1 and 0.5 f.Lmol N03 kg-1 1.0 and 5.0 f.Lmol NH4 kg-1 0.1 and 0.5 f.Lmol P04 kg-1 1.0 and 5.0 f.Lmol SI04 kg-1 One might also expect shade adaptation of the benthic micro flora (Sundback & Gran eli, 1988), such that the saturation light intensities for the pelagic and benthic diatoms are 100 and 65 ).lE m-2 s -1 respectively. The respiration and excretion losses are instead the same for each diatom group i e 10% and 4% ofthe gross productions g1P and g2M. Grazing ingestion rates are modeled as MichaelisMen ten functions (Mullin eta!., 1975). Assuming that the same gut modification of chlorophyll to phaeopigments by pelagic herbivores (Downs & Lorenzen, 1985) is performed by benthic ones, the daily phaeopigments of the microflora on the 27-m isobath in the Georgia Bight (Nelson et al., 1999) suggest a consumption of -35% of the chlorophyll stock, compared to -100% of the phytoplankton stock during FSLE-1. The maximum phytoplankton loss rate to grazing by herbivorous copepods (YmaxJ) is set to 0. 7 dai1 with a half saturation constant (ky1 ) of 0.65 ).lg chllite(1 For the benthic microalgae, maximum ingestion rate (Ymax2 ) is set to 0.2 dai1 with a half saturation constant (ky2 ) of 36 mg chl m 2 for the 1 em sediment depth integral. Each diatom community is subject to a refuge population (Pr. Mr) below which no grazing occurs For the phytoplankton, this occurs at 0.3 ).lg chlliter-1 while Mr for the benthic microalgae is 6.0 mg m 2 Because this model of the fate of the spring bloom ignores nitrogen-fixation, the only form of"quasi-new" nitrogen is described in the water column by 10

PAGE 23

(6) subject to the boundary conditions, at z = 0 k 8N03 = 0 z az (6a) (6b) and in pore waters (pw) by (7) subject to the boundary conditions 8pwN03 [ (p )] at z=h, = km wN03 -N03 l h b az (7a) 8pwNO at z = h + h 3 = 0 m, az (7b) with eq. (7) again integrated over h to h + hm. In eqs. ( 6)-(7), the fraction 0.15 is an inverse Redfield C/N ratio of 6.67, converting nutrient uptake to C02 sequestration in particulate matter during net 11

PAGE 24

photosynthesis ([g1 ,2 E1 ,2 ]), i.e allowing for higher C/N ratios during gross production (Sambrotto et al., 1993) Across the diffusive sub-layer at the sediment interface (Morse, 1974; Schink & Guissano, 1977), the transfers ofN03 P04 Si04 DOC, and C02 occur in the model at their molecular rates of diffusion (km) 1.5 x 1 o5 cm2 s 1 (Henrichs & Farrington, 1984). Finally, nitrification occurs in the water column as a function of the biomass of nitrifying bacteria (B2). P2 is the respiration rate of the nitrifying bacteria. X2 is the rate of nitrification within pore waters, 0 .01 N kg-1 and I( z, t) < 0 .0110 In the water column at z=h, loss ofN03 may occur due to uptake by benthic microalgae ( -0.15(g 2 E2)M), when concentrations ofN03 in this near bottom water are greater than equivalent concentrations ofNH4 and N03 in the pore waters and NH4 at z=h. Beneath the turbid water column at the 5 m isobath of the Georgia Bight, denitrification occurs at sediment depths of 5-15 em, such that the bottom effluxes of nitrogen may be partitioned as ammonium another 35% as N 2 7 % as DON, and the remaining 10% as nitrate (Hopkinson, 1987), i.e PON DON + NH4 + N03 + N 2 In contrast, at the 27-m isobath denitrification does not prevail within the upper 15 em (Marinelli et al., 1998). Instead, the paradigm is PON N03 such that denitrification is ignored in this simulation of element cycling at the 28-m isobath of the West Florida shelf In the southeastern Bering Sea where nitrification dominates the bottom effluxes of nitrogen, the first order sediment rate is N03 kg-1day 1 (Rowe and Phoel, 1992) for X 2 compared to ammonium oxidation rates of0.02-0.05 N03 kg-1day1 in the water column (Hattori et al., 1978) Using a Q10 of2. 0 for metabolic changes of 12

PAGE 25

nitrifying bacteria in relation to temperature and a 20C increment for West Florida waters, the value ofX2 is assumed to be 1.0 J..Lmol N03 kg -1dai1 The measured rate of 11.5 J..Lmol NH4 kg-1 day-1 for sediment ammonification (X3 ) at the 27m isobath of the Georgia Bight (Marinelli et al., 1998), compared to the model's rate ofbenthic nitrification, is consistent with effluxes of mainly ammonium from this well-lit coarse sand bottom This process of remineralization is described, in terms of nitrogen, by (8) subject to the boundary conditions, at z = 0 k BNH4 = 0 z 8z (8a) (8b) and in pore waters by 13

PAGE 26

subject to the boundary conditions (9a) 8pwNH at z = h + hm, k z 4 = 0 Oz (9b) with eq (9) again integrated over h to h + hm. If the amount ofporewater substrate (pwDOC) becomes 0.0 at any time step, the assumed rate of ammonification (X3 ) is set to zero. Most ofthe other sources of ammonium in eqs (8) and (9) are the nitrogen equivalent of respiration by "sloppy" zooplankton, feeding on pelagic diatoms (81[1-sJ]yiP), by ammonifying bacteria by their predators and those of nitrifying bacteria-heterotrophic flagellates (m1B 1 m2B2), and by the more efficient herbivorous meiofauna (82[1 s21Y2M). As a result of assumed sloppy feeding by copepods (s1), only 50% of the diatoms grazed by them are ingested to supply sources of respired C02 excreted NH4 and sinking POC, i.e s 1 is 0.5 The other herbivores are not a source of DOC during feeding, such that S2 is zero. The metazoan respiration rates (8 1 2 ) of 0 65 assume an assimilation efficiency of 65% of the ingested food, such that fecal pellets are formed at 35% of the food intake. The z ooplankton fecal pellets fall to the sea floor for dissolution, while the extruded pellets of the meiobenthos are dissolved to DOC within the upper 1 em of sediment. Remineralization, photosynthesis, and nitrification, in terms of carbon are described in the water column by 14

PAGE 27

8DIC a 8DIC ( ) ( ) B2+e:tP+8t Ytp (lO) + (pt + mt)Bt + X4 subject to the boundary conditions O 8DIC at z-'kz--k m---=-az 8hsa 8 DIC at z = h kz--= km(pwDIC-DIC)Ihb az (lOa) (lOb) In eq. (lOa) Km is the molecular diffusivity of C02 at the air-sea interface, where his now the stagnant film thickness Their ratio (vp) is termed the gas exchange coefficient, or piston velocity, and is computed following Wanninkhof et al. (1997) to allow comparison ofthe model's results with prior synthesis ofthe FSLE-1 data A simple budget suggested that the observed increment ofDIC over 14 days ofFSLE-1 could be attributed to 80% biotic remineralization of organic carbon and only 20% to invasion of atmospheric C02 is the difference between the pC02 of air and of surface sea water, in which atmospheric pC02 is assumed to be a constant 370 j.latm. At each t i me step, values ofDIC are used to calculate (Peng et al., 1987) both the concentration of C02 and thence its partial pressure, using solubility (a) ofthis gas in sea water. 15

PAGE 28

The last term of eq. (11) represents photochemical degradation of DOC to DIC by ultraviolet radiation within the upper 5 m of the model at a rate of0. 02 f.J.mol DOC kg -1 daylight hr-1 (Mopper e r al., 1991). All other terms are defined, except 0 088 in eq. (11) This number reflects utilization ofDIC during nitrification (Ward 1986) unlike the inefficient use of DOC (Wood 1987) during such oxidation of ammonium (Walsh e t al., 1999) Pore water DIC is described by, subject to the boundary condit i ons at z = h, k z apwDIC = [km (pwDIC DIC)] h b f)z at z = h + hm, k z apwDIC = 0 (11) (11a) (11 b) Like pelagic diatoms in the Gulf of Mexico (Nelson & Dortch 1996) the benthic diatoms may experience Si-limitation, explaining success of some dinoflagellates in b e nthic mesocosm experiments (Sundback & Graneli 1988) As such dissolv e d silica (Si04 ) is described in the water-column by 16

PAGE 29

(12) subject to the boundary conditions t O k 8Si04 O a z----' z a z (12a) (12b) and in pore waters (pw) by (13) subject to the boundary conditions (13a) 17

PAGE 30

8pwSiO at z = h + hm, k z 4 = 0 oz (13b) k s is the silica dissolution rate constant of3. 89 x 10-10 m s-1 for Rhizoselenia in seawater (Kamatani and Riley, 1979). Ce is the solubility of particulate silica (mmol m-3 ) in seawater described by C e = 1130 + 24.6T (14) where Tis the temperature of the water in degrees Celsius Vis the volume around the grid point and Sb is the surface area of biogenic silica determined from, S b = Kconvert [Si] (15) where Kconvert is a conversion factor of 3.97 m2 mmol Si-1 (Kamatani and Riley, 1979) Si is the non-living biogenic silica concentration in the water described by, (16) subject to the boundary conditions o 8pwSi atz=h -k =0 'az z az (16a) 18

PAGE 31

8pwSi at z = 0 k = 0 z Oz (16b) in the water column, where is the assumed fecal pellet degredation rate of 4 day -1 in the near bottom water when fecal pellets are present. Pore water biogenic silica is described by, (17) subject to the boundary condition, 8pwSi atz=h=h k = 0 m, z az (17a) such that, like the other particles in the model, biogenic silica is not exchanged across the sediment/water interface Phosphate cycling in the water column is described by, 8P04 = k z BP04 0.00937{g 1 -EJ)P-0.00937 (g 4 B 2 at Oz a z (18) + 0.00937 8 1 (1p + + m1)B1 19

PAGE 32

subject to the boundary conditions, (18a) at z = O k 8P04 = 0 z o z (18b) The ratio of carbon respiration to phosphorus regeneration in Georgia sediments is a Redfieldian one of 130 (Hop ki nson 1985 ; 1987) such that phosphate cycling in the pore waters is described in the model by, = 0 0625 x3 + 0 00937 g2( 3z(1s2)/..2 M + 0 0093 7 (0 65 y2 M) -0 00937(g2 s2)M0.0625 x z -0 k z--'ap'---w_ P 0 -'-4 o z o z (19) subj ect to the boundary conditions, (19a) 8pwP04 at z=h+hm, k z Oz = 0 (19b) 2 0

PAGE 33

Fecal pellets of z ooplankton origin arrive quickly at the bottom with a mean s ettling rate (wr) of 100m day"1 (Paffenhofer & Knowles, 1979) for typical copepods of the West Florida shelf (Kleppe I e t a l ., 1996) in their state equation az a a z a = k P w r-Z-kd Z Qt Oz z Oz I Oz e g subject to the boundary cond i tions a z atz=O, k z-+wrZ=O Oz a z a atz=h k --wr-Z=O z[)z Oz (20) (20a) (20b) where the egestion rate (p) is 35 % of the assimilated food, (1-;tht P Since the settling velocity (wr ) is 0 at z=h, fecal pellets are allowed to accumulate in the near bottom water w here they are converted to Lab i le DOC at their degradation rate of 4 0 day -1 Labile DOC, as well as the inferred DON and DOP bound to it is also released by the z ooplankton in the water column as a result of" sloppy fe e ding (;t) (Jumars e t al. 1989; Banse, 1992) providing another food source for the ammonifying bacteria (Baines & Pace, 1 991) in the fifth term of aDOC a aDOC --= -kz +\Jf1P +;1y1P-x4 -g3 B 1 +kdegZ Ot Oz Oz (21) 21

PAGE 34

subject to the boundary conditions 8DOC at z = 0, kz = 0 8z (21a) 8DOC atz=h, k z =[km(pwDOC-DOC)]Ihb oz (21b) Within the sediments, labile pore water DOC sources are the soluble forms of the fecal pellets extruded by the meiobenthos, as well as rnicroflora excretion defined by 8pwDOC = 0 35 M M-6 67 !_ 8pwDOC Y 2 + \112 X 3 kz____::_ __ 8t 8z oz subject to the boundary conditions atz=h, k z 8pwDOC =[km(pwDOC-DOC)]Ihb 8z 8pwDOC atz=h+hm, k z =0 8z In the model, inert DOC (iDOC) concentrations are used to calculate light (22) (22a) (22b) attenuation due to total DOC in the third term of equation 2. Inert DOC is neither gained nor lost from the water column during the course of a model run, but it is exchanged throughout the water column in the only term of its state equation, 22

PAGE 35

&DOC a &DOC at az subject to the boundary conditions, a &DOC at z=O=h, k z = 0 az az The population of ammonifying bacterioplankton is given by, subject to the boundary conditions aB1 at z = 0 = h k = 0 z az The growth of ammonifying bacteria is another Michaelis-Menten function, g3 =am (DOC /(nb +DOC)) (23) (23) (23a) (23b) with a half-saturaton constant (nb) of0.4j..lmol DOC kg1 and a maximum bacterial growth rate (am) of 1.3 day"1 A mortality rate of0. 24 day1 was based on prior sensitivity 23

PAGE 36

analyses of the microbial loop of the Gulf of Mexico (Walsh & Dieterle, 1994 ). The respiration rate CP) is 55% of the DOC consumed (del Giorgio and Cole 2000) while 100% of the predation loss to heterotrophic flagellates is regenerated as DIC, NH4 and P04in the last term of eq (23) Similarly, nitrifying bacteria are given by, (24) subject to the boundary conditions, at z = 0 = h k oB2 = 0 z oz (24a) with a mortality rate (m2 ) of0.24 dai1 assuming the same grazing pressure as the ammonifying bacteria The respiration rate is instead 60% of the DIC and inorganic nutrients consumed (del Giorgio and Cole, 2000) The model's nitrifying bacteria are in competition with the phytoplankton for NH4 and P04 Similar to the phytoplankton, their specific growth rate expands to a non-linear, time dependent expression, (24b) 24

PAGE 37

with a maximum growth rate of 1.3 day"1 and half-saturation constants for NH 4 and P04 (nn, np) of0.1 IJ.mol NH4 kg-1 and 0.1 IJ.mol P04 kg-1 respectively Model initialization The model was initialized with respect to phytoplankton biomass (figure 3) in terms of carbon based on an early chlorophyll a profile from the FSLE experiment and an assumed carbon/chlorophyll ratio of 45 for pelagic diatoms. The uniform profile, representing concentrations of 1 6 Jlg r1 reflects the homogenous water column measured during the first few days ofFSLE-1 Likewise, initial zooplankton fecal pellet concentrations were determined from the corresponding phaeopigment profile and a carbonlphaeopigment ratio of 45. Initial DIC concentrations (figure 4) were taken from the FSLE-1 data set. DOC concentrations were not measured during FSLE, however. The model was initialized based on measurements made by Carder et al. (1989) in a similar post bloom situation near the FSLE study site (figure 5) The labile DOC concentrations were intialized at 182.6 IJ.g r1 in the top 5-m of the water column with inert DOC concentrations of730 IJ.g r 1 in the top 5-m and an inert background of 8 IJ.g r 1 in the rest of the water column. This inert : labile doc ratio of 4:1 is consistent with studies of DOC remineralization rates (Kirchman et al., 1991; Carlson and Ducklow, 1995). The colored component (CDOC) affecting light attenuation is assumed to be 50% of the total (inert + labile) DOC throughout the simulations. 25

PAGE 38

Inorganic nutrients (figure 6) wer e initialized from profiles on day 1 of the FSLE1 experiment. Biogenic silica" in the model represents diatom frustules remaining in the water column follow ing the lysis of diatom cells Phaeopigment profiles from FSLE-1 i ndicate the degredation of three times the amount of chlorophyll present on day I of the experiment. A conservative estimate of 4% (the diatom lysis rate) of the population present on day 1 was used to arrive at the initial biogenic silica profile, assum ing a molar C : Si ratio of 6 625:1 Biogenic silica is also contained within fecal pellets of z ooplankton origin, but is not available for dissolution until the degredation of the f e cal pellets in the near bottom water (Bidle and Azam, 1999) Bacteria (figure 7) were initiali z ed according to biomass estimates of Ducklow (2000) This total background biomass was divided evenly between the nitrifying and ammonifying functional groups Benthic nutrients (Table 2) wer e i n i t i alized from measurements made at the 27 m isobath in the South Atlantic B i ght by Marinelli e t al. (1998) in the spring of 1996 The initial benthic microalgal populat i on is based on sediment chlorophyll measurements made out to the 30-m isobath in the Gulfof Mexico in April 1993 (G V a rgo personal communication) The pore water DIC was initialized at the sam e concentration as the near bottom water Perturbation experiments Two perturbation experiments were conducted to test the viability of benthic microalgae under conditions more adverse than those in the baseline simulation Light 26

PAGE 39

I 3 5 7 9 ,....., II E 13 .._, --Phytoplankton ..c 0. cu 15 zooplankton fecal pellets 0 17 19 21 23 25 27 70 75 80 85 90 95 Carbo n (Jlg r') Figure 3 Initial phytoplankton and zooplankton fecal pellet profiles. 3 5 7 9 ,....., II 5 1 3 ..c 0. 15 0 17 19 21 23 25 27 2000 2025 2050 2075 2100 Carbon (Jlg r') Figure 4 Initial DIC profi l e 27

PAGE 40

1 3 5 7 9 6 1 1 ......, 1 3 -..<:: a. II) 1 5 -Cl 1 7 1 9 2 1 23 -2527 0 200 1 3 5 7 9 g 1 1 1 3 ..<:: a. Q) 1 5 Cl 1 7 1 9 21 23 25. 27 0 0 2 -Inert DOC --Labi l e DOC 400 600 800 1000 1 200 1400 1600 1800 2000 0.4 Figure 5. Initial DOC p r ofi l es. 0.6 ---Ammonium --Nitra t e Phospha t e ____.._S il icate __.__ Biogenic Sil i ca 0 8 1.2 1.4 Nutrie n t concentrat i on (Jlm o l kg"1 ) 1.6 Figure 6. I nitia l wa t er-co lu mn nutrient profiles. 28 1.8 2

PAGE 41

limitation is a key factor in the success or failure of benthic microalgae in shallow, near shore environments (Macintyre eta!., 1996). The first perturbation experiment consisted of a "nearshore DOC" case of the model. While the baseline simulation was initialized with DOC concentrations found in a post bloom scenario near the FSLE study site, this high DOC simulation was instead initialized with DOC concentrations (figure 8) measured by Del Castillo et a!. (2000) several miles north of the FSLE study area in coastal waters near the termination of the Apalachicola River. Benthic microalgal biomass was seen to decline in the fall in both the study on the West Florida shelf(G. Vargo, personal communication) and the South Atlantic Bight (Nelson et a!., 1999). Sediment flux observations indicate that nutrients escape from the sediments even though large populations ofbenthic microalgae may exist (Sundback et a!, 1991 ; R. Jahnke, personal communication). The second perturbation experiment explored the role of sediment flux in the success of benthic rnicroalgae through an increased sediment exchange case of the model. The baseline model employs the molecular diffusion rates of the dissolved species in determining flux across the sediment/water interface. The "enhanced diffusion" case makes use of a diffusion coefficient (kb) to represent enhanced diffusion across the interface, presumably due to bioturbation (Marinelli, 1992), s uch that the exchange term in the state equations of the dissolved species becomes: [(km+ kb)(pwS S)]/h b where Sis the dis so lved species being calculated. The value ofkb was set to 3.75 x 10-3 cm-2 s-1 at the high end ofthe range of 50-250 times the molecular diffusion rate observed by R. Jahnke (personal communication) in the South Atlantic Bight. 29

PAGE 42

I 3 5 7 9 --Ammonifying bacteria '? II '-' 13 ..c 0. 15 v --Nitrifying bacteria Total bacteria Q 17 19 21 23 25 27 0 2 3 4 5 6 7 8 9 10 Figure 7. Initial bacterial biomass. Note that the ammonifying bacteria and the nitrifying bacteria were initialized at e qual concentrations throughout the water column. The total bacteria profile is twice that of the individual nitrifying and ammonifying bact eria Integrated Microfloral Ammonium Biomass (mg m -2 ) (J.tmol kg-1 ) 254.4 2 Nitrate (J.tmol kg1) 0.5 Silicate (J.tmo l kg-1 ) 1.7 Phosphate (J.tmol kg-1 ) 0.2 Table 1. Initial benthic parameters. 30 DIC DOC (J.tmol kg-1 ) (J.tg r1 ) 2052 36

PAGE 43

I 3 5 7 9 -,...., I I E 13 '-" 4) 15 -Ine rt DOC Cl 1 7 --Labile DOC 1 9 21 23 25 27 0 200 400 600 800 1000 1200 1400 1600 1800 2000 F i g ure 8. Initial DO C profile for the nearshore DOC case of the model. S ymbo l D escri ption Units Value h water co lumn d e pth m 27 h m thickn ess of the se diment la ye r m 0.01 k w s pe c ific attenuation coeffic i ent f o r water m' 0.03 kp s p ecific attenuation coeffic i ent for phyto plankton I Jlg c hr' m' 0 023 k
PAGE 44

Symbol Description Units Value 1m2 Light sturation intensity for benthic microalgae 11E m2 s1 65 knitratel Phytoplankton half-saturation constant for N03 JlmOl N03 kg "1 0.1 knitrate2 Benthic microalgae half-saturation constant for N03 jlmol N03 kg "1 0.5 kammoniuml Phytoplankton half-saturation constant for NH.t Jlmol NH 4 kg-1 1 kammonium2 Benthic microalgae half-saturation constant for NH 4 JlmOl NH4 kg"1 5 kphosphate I Phytoplankton half-saturation constant for P04 JlmOl P04 kg "1 0.1 kphosphate2 Benthic microalgae half-saturation constant for P04 JlmOl P04 kg"1 0 5 ksilieatel Phytoplankton half-saturation constant for Si04 JlmOl Si04 kg "1 1 ksilic:ate2 Benthic microalgae half-saturation constant for Si04 Jlmol Si04 kg"1 5 nb Anunonifying bacteria half-saturation constant for 11 DOC kg -1 0.4 DOC nn Nitrifying bacteria half-saturation constant for NH.t Jlmol NH4 kg "1 0.1 np Nitrifying bacteria half-saturation constant for P04 Jlmol P04 kg"1 0.1 ky, Phytoplankton grazer half-saturation constant JlmOl chl r1 0 65 l
PAGE 45

Results Baseline The baseline case of the model successfully simulates the decline of the surface chlorophyll bloom as measured during FSLE 1 (figure 9) Over the course of 14 days, the simulated and measured surface chlorophyll a concentrations in the water column decreased from initial concentrations near 1 5 Jlg r1 to approximately 0.3 Jlg r1 During this time grazing pressure was high (figure 10), accounting for more phytoplankton loss in the s urface waters than was gained through net photosynthesis. Near bottom chlorophyll concentrations did not match the FSLE data as well as the surface such that a rapid increase in near-bottom chlorophyll on days 3 and 4 ofFSLE was unexplained by the model (figure 11) However, ammonium concentrations remained steadily below 0.5 Jlmol kg-1 throughout most ofFSLE and FSLE-2 with the exception of a near bottom spike of>2 Jlmol kg -1 during days 8-11 (figure 12) After this near bottom s pike, ammonium concentrations returned to < 0.5 Jlmol kg-1 throughout the water-column, becoming as low as 0.08 Jlmol kg -1 by day 86, like the concentrations measured at the 27 m isobath during FSLE-2 Nitrate concentrations were also < 0.5 Jlmol kg-1 through most of the simulation, with the notable exception of a near bottom increase shortly after the spike in ammonium 33

PAGE 46

(figure 13) Simulated N03 rose to concentrations nearly 3-fold those measured during FSLE-1 and declined more gradually than the rapid decrease that was observed. Coincident with the increase in nitrogen concentrations near bottom was an increase in near bottom DIC concentrations (figure 14), reflecting the increase in bacterial growth Overall, DIC concentration increases in the water column over the first 14 days of the simulation were consistent with an observed increase of approximately 1 1-1mol kg-1 dai1 (Hitchcock et a/., 2000). In contrast to the computations of atmospheric C02 invasion at a rate of0.17!lmol C kg -1 dai1 made by Wanninkhof et al. (1997), however, C02 evaded from the baseline simulated surface waters at a rate of0. 30 1-1mol C kg-1 dai1 Over the water column, bacterioplankton increased approximately 10-fold in the first 10 days of the simulation (figure 15), reaching a greater biomass than the declining pelagic diatoms on day 6 of the simulation. The beginning of the subsequent gradual decline in bacterial growth was coincident with the near bottom maximum in NH4 on day 10, which also marked the exhaustion ofDOC in the near-bottom water (figure 16). Simulated near bottom phosphate concentrations were slightly higher than those measured during FSLE-1 (figure 17) Phosphate concentrations exhibited a small peak on day 11 in both the simulation and the FSLE-1 observations. Likewise, simulated near bottom silicate concentrations were higher than those observed during FSLE-1 (figure 18). While the simulated silicate exhibited trends similar to the observations, the small peak in observed silicate occurred approximately 7 days before the large peak in the simulation. Based on this simulated nutrient scenario, phytoplankton at the surface in the baseline case were initially limited by silica (figure 19) After day 12, however, nitrogen 34

PAGE 47

3 2 5 --Modeled -2 bl) ::t: Measured ,.:; ]' 1.5 -0.. ::t: 0 ... 0 :a u 0 5 0 6 II 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 Day Figure 9. Surface chlorophyll concentrations during the baseline simulation of the model 3 2 5 1 2 0.5 and the FSLE-1 study. ---Net photosynthesis Consumption 6 II 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 Day Figure 10. Net photosynthesis and consumption in the surface waters ofthe baseline simulation of the model. 35

PAGE 48

3 X 2.5 ,....., OJ) 2 --Modeled -.:;. X Measured >. 1.5 .c Q. 0 ... 0 :;: u X 0 5 0 6 II 16 21 26 3 1 36 41 46 51 56 61 66 71 76 81 86 Day Figure 11. Near-bottom chlorophyll concentrations during the baseline simulation and the FSLE-1 study 14 12 ,....., 10 Jf 8 --Modeled 0 E X Measured 5 6 :t z 4 2 0 6 II 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 Day Figure 12. Near bottom ammonium concentrations during the baseline case of the model and the FSLE studies 36

PAGE 49

14 12 ,..., 10 '7c.f) .!>( 8 --Modeled 0 E X Measured 6 ... 0 z 4 2 0 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 Day Figure 13. Near bottom nitrate concentrations during the baseline simulation of the 2 100 2090 2080 ,..., 2070 !f 2060 ] 2050 'C' 2040 8 2030 2020 2010 model and the FSLE-1 study --Modeled X Measured 6 I I 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 Day Figure 14 Near-bottom DIC concentrations during the ba s eline simulation of the model and the FSLE-1 study 37

PAGE 50

300 ,..... "' E 0 250 E Phytoplankton E '-' 200 c:: Bacterioplankton 0 .D 0 150 "0 bo 100 G) .S E. 50 G) Cl 0 6 II 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 Day Figure 15. Depth integrated phytoplankton and bacterioplankton during the baseline simulation of the model. 150 140 130 120 I 10 -; Cll 100 .I( 90 0 80 E d. 70 u 60 0 -50 Cl 40-30 20 10 0 6 I I I 6 2 I 26 3 I 3 6 4 I 46 5 I 56 6 I 66 71 7 6 81 86 Day Figure 16. Near-bottom labile DOC concentrations during the baseline simulation 38

PAGE 51

14 12-....... 10 bll --Mo deled .!<: 8 0 E X Me asured 6 .. 0 0.. 4 2 6 II 1 6 21 26 3 1 36 41 4 6 51 56 6 1 66 71 76 81 86 Day Figure 17. Near-bottom phosphate concentrations during the baseline simulation of the model and the FSLE-1 study. 14 12 ....... 10 bll .!<: 8 0 --Modeled E 6 X Measured .. 0 i:ii 4 2 0 6 II 1 6 21 26 31 36 41 46 51 56 61 66 71 76 8 1 86 Da y Figure 18. Near-bottom silicate concentrations during the baseline simulation of the model and the FSLE-1 study 3 9

PAGE 52

limitation took over with the exception of cloudy days (figure 2) when the surface phytoplankton were limited by light availability. In contrast, the near bottom phytoplankton were limited by light through almost the entire 86 days of the baseline simulation (figure 20). Nitrogen limitation occurred from day 81 to day 85. Benthic chlorophyll (Figure 21) increased in the model from an initial stock of 8 7 mg m-2 to 27.7 mg m-2 A similar increase was observed on the West Florida shelf in April1993 and July 1992 (G. Vargo, personal communication) and in the South Atlantic Bight (Nelson et al, 1999) Net production in the sediments (figure 22) mirrored the chlorophyll over time, reaching a maximum production of 10 54 mmol C m -2 dai1 (126.48 mg C m-2 day-1 ) on day 40, or approximately 18% of the integrated phytoplankton production on day 1 of the simulation and 250% of the integrated phytoplankton production on day 86. Benthic production, on day 86, however was lower than depth integrated phytoplankton production, reflecting episodic light limitation of the benthic microflora (figure 23) on that day The baseline simulated phosphorus limitation and low phosphate concentrations (figure 24) in the sediment pore waters are consistent with P04 concentrations of less than 1 Jlmol kg -1 measured by Marinelli et al. (1998) in the South Atlantic Bight in June 1996. Simulated NH4 and N03 concentrations were also similar, but Si04 concentrations were somewhat larger than the findings of that study. All four simulated algal nutrient species diffused out of the sediments into the near bottom water throughout the simulation (figure 25), with the exception of silicate, which invaded the pore waters in the first few days Si04 and NH4 were ultimately evaded from the sediments at rates an order of magnitude greater than N03 and P04. 40

PAGE 53

6 II 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 Day --Light ----Nitrogen _,._Silica -Phosphorus Figure 19 Factors limiting the photosynthesis of phytoplankton in the surface waters of th e baseline s imulation The factor h aving the l owes t fraction of maximum uptake is the C1) 0.8 0. ;:s E 5 o.6 E ""' 0 c:: .g 0.2 (J... limiting factor. 6 II 16 21 26 3 1 36 41 46 51 56 61 66 7 1 76 81 86 Day --Light ----Nitrogen _._Silica Phosphorus Figure 20. Factors limitin g the photosynthesis of phytoplankton in the near-bottom waters of the baseline simulation. The factor having the lowest fraction of maximum uptake is the limiting factor. 41

PAGE 54

40 ,.... 35 "! a OJ) 30 a .._, >. ..c 25 0. 0 20 ... --Modeled 0 ::2 15 () :.:: Measured -o Q) 'iQ Sh Q) 10 ] 5 0 6 II 16 21 26 31 36 41 46 51 56 61 66 71 76 8 1 86 Day Figure 21. Benthic c h l orophyll stocks integrated over the upper 1 em of t h e sediments during the b ase l ine sim u latio n compared to m easurements made by G. Vargo (personal communication) in April 1 993 (day!) and Ju l y 1 992 (day 86). c 0 12 Net p h otosyn t hesis ;; 0. a 10 ;:l "' c 0 () 8 ,.... "' "! 'Vi a Q) ..c u 6 .... c 0 >. "' a 0 0 E 4 ..c .._, 0. -o 2 "' ... OJ) Q) .s. 0 I 6 I I 16 21 26 31 36 4 1 46 51 56 61 66 7 1 76 81 86 Day Figure 22. Net photosynthesis of the benthic microflora l community during t h e baseline simulation, com p ared to con s umption of the b enthic diatoms 42

PAGE 55

II) i5. ;:s E ;:s E E .... 0 c:: g 0 "' .. 11. 0 8 0 6 0.4 0 2 0 6 I I 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 Day --Light ---*"""Silica Phosphorus Figure 23 Factors limiting the photosynthesis of the benthic microalgae during the baseline simulation The factor having the lowest fraction of maximum uptake is the limiting factor. 60 ,...... Of) ..:.: 50 --Nitrate 0 E ---*"""Silicate ..:; 40 c:: Phosphate 0 i 30 t: c:: II) 0 c:: 0 20. 0 i:: II) 10 ;::: ; z 0 6 II 16 21 26 31 36 41 46 51 56 61 66 71 76 81 Day Figure 24 Pore-water nutrient concentrations during the baseline simulation. 43

PAGE 56

,..., '0 E 0 E E .......-X ;:I u:: 0.8 0 6 0.4 0.2 0 -0.2 -0.4 -0 6 -0 8 -I 6 II 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 Day -<>-Ammonium --Nitrate __.,_Silicate Phosphate Figure 25. Diffusive nutrient fluxes across the sediment/water interface during the baseline simulation A negative flux represents diffusion into the sediments, while a positive flux represents diffusion out of the sediments 4 3 ,..., 2 '0 "! E 0 DIC E 0 E .......-DOC X 76 81 86 ;:I -1 c;: s: 0 -2 .D ... "' u -3 -4 Day Figure 26. Diffusive carbon fluxes across the sediment/water interface during the baseline simulation. A negative flux represents diffusion into the sediments, while a positive flux represents diffusion out of the sediments. 44

PAGE 57

Similarly, DOC was ultimately released from the sediments after an initial invasion in the first 10 days ofthe baseline simulation (figure 26). DIC invaded the sediment pore waters until day 75 of the simulation with the exception of episodic DIC release coinciding with days oflow incident PAR (figure 2). Nearshore DOC case Simulated surface chlorophyll concentrations in the nearshore DOC case varied little from the baseline case (figure 27). On average, chlorophyll concentrations were 0.1 r1 higher in the nearshore DOC case. The near bottom chlorophyll concentrations varied more, however, averaging about 0.6 1-1g r1 less in the nearshore DOC case relative to the baseline. Near bottom nutrient concentrations also varied little from the baseline simulation, with the exception of nitrate (figure 28) While the near bottom N03 concentrations in the nearshore DOC case reached a peak similar to that of the baseline on day 12 (figure 13), nitrate concentrations did not decrease as rapidly in the nearshore DOC case and remained at 2.3 kg-1 at the end of the simulation. Surface and near bottom DIC (figure 29) in the nearshore DOC case increased rapidly as surface and near bottom DOC (figure 30) decreased. In the surface waters, C02 evaded during the first 14 days of the simulation at an average rate of0. 75 kg -1 dai1 or more than double the rate of the baseline case. Like the baseline simulation, the increase in near bottom DIC in the nearshore DOC case began to level off on day 11, but the subsequent increase was less gradual in the nearshore DOC case The leveling off of 45

PAGE 58

3 2 5 ,......, bfJ 2 ::1. --Surface .._, >. ..c: 1.5 -Near bottom Q, 0 .... 0 :<:: 0 0 5 0 6 II 1 6 21 26 3 1 36 41 46 51 56 61 66 71 76 8 1 86 Day Figure 27. Surface and near-bottom chlorophyll concentrations during the nearshore DOC case. 14 12 ,......, bfJ ..><: 10 -----Amm onium 0 8 --Nitrate E 6 -.-silicate E 6 11) -Phosphate ; E ;:s 4 z 2 0 6 II 16 21 26 3 1 36 41 46 51 56 61 66 71 76 8 1 86 Day Figure 28 Near-bottom nutrient concentrations during the nearshore DOC case 46

PAGE 59

2100 2090 ........ !:0 2080 0 --Surface DIC E :::t '-" u Q 2070 Near Bottom DIC 2060-20506 II 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 Day Figure 29 Surface and near-bottom DIC concentrations during the nearshore DOC case. 150 140 130-120 -........ 110 100 Jf 90 0 80 --Surface DOC E 70 &' 60 Near bottom DOC 0 50 Q 40 30 20 10 6 II 16 2 1 26 31 36 41 46 51 56 61 66 71 76 8 1 86 D a y Figure 30 Surface and near-bottom DOC concentrations during the nearshore DOC case 47

PAGE 60

the DIC increase again coincided with the peak in integrated bacterial biomass (figure 31), which was 50 mg m-2 greater in the nearshore DOC case, compared to the baseline simulation. Near bottom phytoplankton in the nearshore DOC case were light limited to a far greater degree than the baseline (figure 32) The near bottom phytoplankton never grew at more than 41% of their maximum growth The benthic micro algae were also limited by light (figure 33), though they grew at nearly the same rate as in the baseline (figure 23) under phosphorus limitation Sediment chlorophyll (figure 34) changed from the baseline simulation, however. Integrated chlorophyll stocks in the upper 1 em of the sediments on day 86 of the nearshore DOC case reached 30 0 mg m-2 nearly identical to the baseline However, the sediment chlorophyll stocks in the baseline case reached 37 9 mg m-2 on day 49 (figure 21) then dropped down to 30.4 mg m -2 by day 86. Sediment stocks in the nearshore DOC case, instead reached 30.4 mg m -2 on day 47 and leveled off with small variations of approximately 1 mg m-2 for the rest of the simulation. Pore-water nutrient concentrations in the nearshore DOC case were similar to those of the baseline case Nutrients were, again typically released from the sediment pore waters to the near bottom water column in the nearshore DOC case. Sediment/water carbon fluxes did not vary significantly from the baseline simulation either 48

PAGE 61

300 ....... "' E 250 Cl) E '-' --+-Phytoplankto n c: 200 0 .D Total bacte riop lankton 1il 0 150 "0 d.l (;j So d.l .... 5 100 ..c: 50 c. d.l Q 0 6 I I 16 21 26 31 36 41 4 6 51 56 61 66 71 76 8 1 86 Day Figure 3 1 Depth integrated phytoplankton and bacterioplankton s tocks during the d.l 0.8 OS c. ;:1 E ;:1 0.6 E E 0.4 .... 0 c: 0 c 0 OS .. 0.2 [.1.. 0 nearshore DOC case. 6 II 16 21 26 3 1 36 4 1 46 5 1 56 61 66 71 76 8 1 86 Da y --Light .........._Silica Phosphoru s Figure 32 Fac t ors l i miting the photosynthesis of near-bottom phytoplankton during the nearshore DOC case. 49

PAGE 62

d) 0.8 0. ::1 E ::1 --Light E E 0.4 .... 0 c -<>-Nitrogen ---lr-Silica -Phosphorus 0 ;:: 0 0.2 C
PAGE 63

Enhanced diffusion case With respect to most variables, the enhanced diffusion case did not significantly vary from the baseline simulation. Water column phytoplankton biomass, nutrients, bacterioplankton biomass and dissolved carbon species were nearly identical between the two simulations In contrast to the water column, however, sediment variables differed significantly between the baseline simulation and the enhanced diffusion case. Benthic chlorophyll (figure 35) in the enhanced diffusion case r eached a similar peak to the baseline sediment chlorophyll on d ay 49. In this case, sediment integrated chlorophyll rose to a stock of39. 5 mg m 2 compared to the baseline's stock of37. 9 mg m2 on day 49. The benthic chlorophyll in the enhanced diffusion case, however, dropped sharply to a stock of23.7 mg m2 by day 86, almost 7 mg m2 less than the baseline stock on day 86 Pore water nutrient concentrations (figure 36) were also much lower in the enhanced diffusion case compared to the baseline simulation. Pore water silicate concentrations in the enhanced diffusion case increased to 12 Jlmol kg1 in the first 13 days of the simulation, similar to the results of the baseline simulation. In this case, however, the pore water silicate concentrations leveled off, instead of increasing gradually as they did in the baseline case (figure 24). NH4 concentrations were an order of magnitude lower. N03 and P04 concentrations, which were relatively low in the baseline case, were generally lower than 0 5 Jlmol kg-1 in the enhanced diffusion case The benthic microalgae in the enhanced diffusion case were limited predominantly by phosphorus (figure 37), like the baseline case In this case, however 51

PAGE 64

the benthic microflora became nitrogen limited much earlier than in the baseline (figure 23) In contrast to the baseline case, nutrients diffused into the sediments during much of the enhanced diffusion case (figure 38) Silicate, which was released by the sediments during the baseline case, diffused into the sediments during most of the enhanced diffusion case. N03 also diffused into the sediments. N14 diffused out of the sediments at far greater rates than it did in the baseline until the benthic microalgae became nitrogen limited (figure 37), at which time the sediment Nl4 release slowed down P04 diffused very little. DIC fluxes (figure 39) exhibited similar trends to those in the baseline case (figure 26), but were four times larger. DOC fluxes did not change significantly from the baseline case. ,....., "' E OJ) E '-' >. ..c: 0. e 0 :c C) "0 C1) ... "' til .s 40 35 30 25 20 1 5 10 5 0 6 II 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 Day Figure 35 Chlorophyll stocks integrated over the top 1 em of sediment during the enhanced diffusion case. 52

PAGE 65

60 ....., !!> 50 0 E Er 40 t:: 0 .b 30 t:: v 0 t:: 20 0 0 E v 'fj 1 0 ::s z 0 10 20 30 ---Ammonium --Nitrate _._Silicate Phospha t e 40 50 Day 60 70 80 90 100 Figure 36. Pore water nutrient concentrations d uri ng the enhanced diffusion case. ... 0.8 0. ::s E E o.6 E ...... -o t:: g 0.2 i:l.. 6 I I 16 21 26 3 1 36 41 46 51 56 61 66 71 76 81 86 Day --Light --Nitrgoen _._Silica Phosphorus Figure 37 Factors limiting the photosynthesis ofbenthic microa l gae during the enhanced diffusion cas e. T h e factor having the lowest fraction of maximum up t ake is the limiting factor. 53

PAGE 66

0.8 0 6 -I 0.4 0.2 --Ammo n iu m C'l I --Nitrate E 0 0 E -0 2 __..._ Silicate E ._, Phosphate >< 0.4 ::l ti: 0 6 0 8 -I Day Figure 38. D iffusive flu xe s across the se d iment/wat e r i nt erface d uri n g th e e nh ance d d iffusio n cas e A posi t ive flu x re pr esen ts flux o u t of the sed imen t s, w h i l e a negative flu x represe n ts flux in t o the sed iments 16 14-12,...... 108 6 "' 4 E 2 CJ) DIC E 0 -r-._, DOC ->< 2 1 6 2 1 26 3 36 41 46 6 ::l -4 II r;: 1:: 0 6 .0 -8 ... u 1 0 -12 -14 -16 Day Figure 39. D iffu s ive car bo n fluxes across th e sediment/wate r i n terface d u ring the enhance d d iffu s io n case. A positive flu x re p rese n ts d iffusion out of t he s edi m ent s while a negative flu x re p resents diffusion in t o th e s edi m en ts 54

PAGE 67

Discussion The modeled baseline scenario compares favorably with the measurements made during FSLE-1 for most parameters The decline in surface chlorophyll (figure 9) over the course ofFSLE-1 and matched by the model can be chiefly explained through nutrient limitation and grazing Although the constant diatom settling velocity of 0.5 m dai1 (Walsh, 1983) removed more chlorophyll from the surface than was grown there after day 5, the diatoms grew at only 50% oftheir maximum growth rate at this time due to silica limitation (figure 19). Carbon remineralization was most prominent in the near-bottom water (figure 14) as a result of bacterial consumption of DOC (figure 16). On average, however DIC in the simulated water column increased by about 1 !J.mol kg-1 day-1 as it did during FSLE1 (Hitchcock et al. 2000). The microbial mediated DIC increases, coupled with photooegredation of DOC in the surface waters led to a net flux of C02 into the atmosphere at an average rate of0. 30 1-1mol C kg -1 dai1 during the first 14 days of the simulation This efflux from the water-column contrasted to the average influx of 0 17 !J.mol C kg-1 dai1 estimated by Wanninkhof et al. (1997) from the FSLE-1 measurements This discrepancy between the simulated and measured averages is most probably due to the initial surface DOC conditions DOC concentrations were not measured during FSLE-1 The initial DOC conditions were instead obtained from a similar April post-bloom scenario near the FSLE-1 site (Carder eta/. 1989) several years 55

PAGE 68

pnor. Lower initial surface DOC concentrations may have resulted in less efflux of C02 or possibly even influx to the water column since the increased initial DOC in the nearshore DOC case resulted in greater efflux ofDIC from the water column More than 100% of the phytoplankton growth increment was grazed on the first day of the simulation (figure 1 0), when diatoms were growing at approximately 55% of their maximum growth rate (figure 19) As indicated by chlorophyll a: phaeopigment ratios in the first few days of the FSLE-1 experiment (Hitchcock et al., 2000), grazing was a major factor in the real world as well The assumed copepod fecal pellet sinking rate of 100 m day -1 coupled with the diatom settling velocity efficiently transported organic matter from the declining bloom in the water column to the near-bottom water Of the two particulate carbon settling fluxes, the diatom settling flux contains living diatoms, while the fecal pellet flux contains dead diatoms packaged in the guts of copepods. The near-bottom pulse of ammonium (figure 12), coincident with the decline in the surface chlorophyll (figure 9) reflects the remineralization of the fecal pellets and phytodetritus first to DOM, then ammonium, and finally nitrate (Figure 13). This increased near-bottom dissolved nitrogen, coupled with alleviated light limitation and a steady rain of viable diatoms from above, led to sustained near bottom chlorophyll concentrations of> 1 Jlg r1 throughout the simulation (figure 11) Although much of the organic matter at the sediment surface was remineralized in the near-bottom water the near-bottom phytoplankton were not able to efficiently use it to produce a large near bottom bloom because they were under light limitation (figure 20), in contrast to the shade adapted microphytobenthos (figure 23). 56

PAGE 69

The simulated peak in near bottom nitrate concentrations occurred approximately 8 days after that of the near bottom ammonium as would be expected in the well oxygenated near bottom waters found during FSLE-1 The near-bottom nitrate peak occurred 3 day s after the ammonium peak during FSLE-1, and was not nearly the magnitude of the simulated peak, although the modeled rate of increase closely fits that of the measurements. The reasons for the discrepancy b e tween simulated and measured nitrate concentrations are not immediately obvious The simulated near-bottom nitrate concentrations are affected by the nitrifying bacteria, the phytoplankton and the benthic microalgae in addition to diffusive flux across the sediment/water interface and within the water column The discrepancy is unlikely due to the nitrifying bacteria since ammonium concentrations matched the data from both FSLE experiments well. It is possible that near bottom phytoplankton became shade adapted during FSLE-1, thus growing more and taking up more nitrate than in the simulation, but simulated chlorophyll concentrations were actually higher than measured concentrations on days 11 and 12 The remain i ng possibility is that the initial pore-water nitrate concentration of 0 5 kg-1 was too high, causing the benthic diatoms to use pore water nitrate instead of near bottom nitrate for growth Marinelli e t al (1998), however measured pore-water nitrate concentrations between 0.5 and 2 kg-1 in upper 2 em of the sediments in the South Atlantic Bight on 14 March 1996 Silica limitation in the upper water column was initially due to rapid uptake of silicate by the photosynthesiz i ng pelagic diatoms (figure 10) and subsequent sinking of particulate silica packaged in the fecal pellets of the grazers consuming them This 5 7

PAGE 70

process was coupled with increasing nitrogen concentrations due to rapid remineralization of surface DOC by bacteria and photodegredation Silicate concentrations in the upper water column were, on average, 0 5 J.Lmol kg-1 lower in the simulation compared to measurements made during FSLE-1. In contrast, simulated near bottom silicate concentrations were 6-fold larger than FSLE-1 measurements by day 11 (figure 18) Copepod C : Si ingestion ratios in the model were identical to the C : Si ratio in the diatoms. Given this the model results suggest that the copepods grazing the diatoms during FSLE-1 were not packaging the silica frustules into fecal pellets in the same proportion to the diatom cellular contents This would explain the disparity between the simulation and the observations since particulate silica was transported to the bottom to a greater degree in the simulation via packaging in copepod fecal pellets. Phosphate concentrations in the simulated water column were similar to those measured during FSLE-1 (figure 17). Hitchcock et al. (2000) postulated that the water column phytoplankton during FSLE-1 were limited by phosphorus availability. While this was not true of the simulated surface waters (figure 19), it would certainly be true of the near-bottom waters if there were less DOC in the surface attenuating light and causing light limitation of the near-bottom diatoms (figure 20) This is despite an N : P regeneration ratio of 16 :1, ie identical to the phytoplankton and bacterial uptake ratio Phosphorus uptake in the water column was reduced relative to nitrogen due to the presence of nitrifying bacteria. While the nitrifying bacteria regenerate P04 at a 16 : 1 ratio to N03 they take up P04 in competition with the phytoplankton, at a 16:1 ratio with NH4 With Michaelis-Menten half-saturation constants of0. 1 J.Lmol kg -1 N03 and P04 are taken up by the pelagic diatoms with equal efficiency, in contrast to half-58

PAGE 71

saturation constants of 1.0 kg "1 for NH4 and Si04 The nitrify ing bacteria on the other hand are efficient users of and P04 with Michaelis-Menten half-saturation constants of 0 1 kg-1 They thus stripped the phytoplankton of their efficient source of phosphorus while simultaneously using a source of nitrogen less efficient for the phytoplankton NH4 to support the bacterial growth was s upplied by a continuous flux from the sediments (figure 25) A large continuous diffusiv e flux of DOC from the sediments also occurred after day 11 of the simulation (figure 26). This flux supported a population of ammonifying bacteria, which regenerat e d even more for use by the nitrifying bacteria. The resulting bacterial production ofDIC caused near-bottom DIC concentrations to gradually increas e o ver the course of th e simulation (figure 14). This, coupled with uptake ofDIC in the pore-water s b y the photosynthes i zing benthic diatoms (figure 22) resulted in a n e t diffus i ve flux of DIC into the sed i ments (figure 26). The episodic variation in the DIC flux was caused by increased light limitation of the benthic micro flora (figure 33) on cloudy days of low incident PAR at the ocean surface (figure 2) The overall dec r ease in the magnitude of the DIC influ x was due to a decrease in net photosynth e sis of the benthic diatoms (figur e 22) resulting in less uptake ofDIC in the sediments Gra z ing in the sediments was also r e duced (figure 22) resulting in lower DOC production in the pore-waters and consequently a low e r magnitude DOC efflux from the sediments (figure 26) After initial nitrogen limitation, the simulated benthic diatoms grew under phosphorus limitation at 40-60% of their maximum growth rate after day 11 of the baseline simulation when the initial nitrogen and light limitation were relaxed (figure 23) 5 9

PAGE 72

The benthic diatoms grew to an integrated chlorophyll stock of37.9 mg m 2 (figure 21), before net photosynthesis began to decrease (figure 22) as the benthic microfloral growth rate declined to less than 45% of the maximum (figure 23). Ultimately, benthic chlorophyll stocks declined to 30.4 mg m 2 by day 86. The main source of nitrogen and phosphorus to the pore-waters in the first few days of the simulation was the influx ofDON and DOP bound to the simulated DOC that diffused into the pore-waters before day 8 (figure 26). Silicate was instead removed from the water column by the benthic diatoms since concentrations were higher in the near bottom water (figure 18) during the first few days of the simulation Silicate was then regenerated in the pore-waters by dissolution of the benthic diatom frustules after lysis and grazing by the benthic herbivores A small amount of silicate diffused into the pore waters during days 1-6 (figure 25), but silicate diffused out of the sediments during the remainder of the simulation Overall, pore water nutrient concentrations in the baseline scenario were consistent with those reported in the South Atlantic Bight by Marinelli e t al. (1998) on 18 June 1996 amid similar sediment chlorophyll concentrations (Nelson e t al 1999). The simulated sil i cate concentrations in this study however, were somewhat higher than those reported in the South Atlantic Bight, probably due to the near-bottom increase in the water column silicate previously discussed Many studies of benthic microalgae report that light availability is the most common limiting factor ofbenthic microfloral communities (Macintyre e t al 1996, and references within) Indeed, the benthic diatoms in the baseline scenario were briefly limited by light in the early days of the simulation. Ultimately however, it was nutrient 60

PAGE 73

limitation that resulted in the small decline in benthic microalgal biomass from the midpoint of the baseline simulation through day 86. Since riverine sources of CDOM have been known to reach mid-shelf portions of the West Florida shelf (Del Castillo et a!., 2000), a second case of the model was run to test the effect of these typically nearshore CDOM concentrations on the dynamics of the benthic micro floral community and its subsequent impact on the flux of nutrients across the sediment/water interface This "nearshore DOC" case was initialized with DOC concentrations measured at station AR2, north of the FSLE study site, near the discharge of the Apalachicola river by Del Castillo et a! (2000) The surface chlorophyll in the nearshore DOC case was only slightly higher than the baseline scenario. Like the surface phytoplankton in the baseline, the nearshore DOC case phytoplankton were limited by nitrogen The near-bottom chlorophyll however, experienced greater light limitation (figure 32) than in the baseline (figure 20) The near bottom phytoplankton in the near-shore DOC case grew at rates of about 10% less than those in the baseline simulation Consequently, near bottom chlorophyll concentrations were, on average, 0 6 )!g r1 less than in the baseline (figure 27) PAR reaching the near bottom waters during the near-shore DOC case averaged about 13% of PAR incident upon the sea surface, compared to about 23% of surface incident PAR reaching near-bottom waters in the baseline scenario In the baseline 25% ofthe incident PAR was attenuated in the upper 5 m of the water column on day 86, while 35% was attenuated in the upper 5 min the nearshore DOC case Thus, the upper 5 m of the water column accounted for the entire difference in near-bottom PAR between the cases. 61

PAGE 74

The increased attenuation was do to the increased DOC in the upper 5-m of the water column of the nearshore DOC case relative to the baseline. The labile portion of the DOC in the simulated water column declined rapidly (figure 30) This decline was due in small part to photodegredation of DOC to DIC, but ammonifying bacteria took up most of the DOC and remineralized it to DIC, P04 The NH.t was in turn taken up by nitrifying bacteria releasing N03 into the water column. This slightly alleviated the nitrogen limitation on the surface phytoplankton, causing them to grow to a slightly higher biomass than in the baseline The integrated bacterial biomass in the nearshore DOC case (figure 31) reached a peak on day 11 of293 mg m-2 or almost 50 mg m-2 greater than the baseline simulation (figure 15). A greater peak in surface DIC concentrations (figure 29) was also observed in the nearshore DOC case relative to the baseline due to the increased heterotrophic respiration This resulted in a net evasion of C02 into the atmosphere at a rate of0.75 !lmol kg-1 day-1 -more than twice the rate of the baseline simulation. Similar to the baseline case, spikes in near-bottom nutrient concentrations followed the rapid decrease of the near bottom DOC (figure 30) in the near-shore DOC case Near-bottom NH 4 P04 and Si04 concentrations did not vary significantly from the baseline case, but N03 concentrations declined more gradually following the day 11 peak in the near-shore DOC case N03 is the end member of a microbially mediated process of remineralization of the DON bound to the simulated DOC in the model. The addition of DOC to the well-oxygenated water column thus ultimately results in increased concentrations ofNOJ. 62

PAGE 75

The labile portion of the DOC, initially in the surface waters, was ultimately transported to the near-bottom water This process began with the reminerali z ation of the DOC into inorganic species in the surface water as previously discussed Following uptake by phytoplankton and grazing by herbivorous copepods, the organic matter was transported to the near-bottom water in the form of copepod fecal pellets In the near bottom water the fecal pellets degraded into DOC, which was again remineralized into inorganic species A large amount of near-bottom phosphorus was again contained as particulate organic phosphorus (POP) within the near-bottom bacterioplankton Due to increased light limitation near-bottom phytoplankton took up even less N03 than in the baseline case This, coupled with the increase in nitrogen to the water column through greater initial DOC concentrations resulted in elevated near-bottom N03 concentrations throughout the near-shore DOC simulation. Growth of the benthic diatoms in the near-shore DOC case was limited predominantly by light (figure 33). Unlike the baseline case, benthic chlorophyll in the near-shore DOC case did not reach a peak concentration in the middle of the simulation followed by a steady decline. Instead, benthic chlorophyll in this case (figure 34) rose gradually until about day 50, when growth leveled off. Overall, net photosynthesis leveled off at about 8 5 mg C m-2 dai1 after day 50. In the baseline case, the benthic microalgal biomass in terms of chlorophyll (figure 21) began to decline as the diatom growth rate fell below 50% of the maximum (figure 23) under phosphorus limitation. In the near-shore DOC case, the mean benthic diatom growth rate was about 45% of the maximum growth rate under light limitation 63

PAGE 76

The light limitation of the benthic micro algal community allowed it to "ration" the available nutrients. Since the near-bottom phytoplankton were under more severe light limitation (figure 32) than the benthic ones, they were not able to take up the available nutrients either. Ultimately, more nutrients were available to the benthic diatoms over the course of the simulation in the nearshore DOC case, such that they achieved a chlorophyll stock of30.47 mg m 2 essentially the same stock as the baseline simulation -by day 86, despite slower mean growth. Phosphorus limitation near the end of the simulation (figure 33) however, suggests that the benthic microalgae in this case may have declined too, if the simulation had been run longer Overall, the addition of the nearshore DOC concentrations to the surface waters of the model had little effect on the success of the benthic diatoms. In fact, the li ght attenuation due to the increased DOC had much more effect on the near-bottom phytoplankton than the benthic microalgae This is largely due to shade adaptation by the benthic microflora. While concentrations of DOC larger than those used to initialize this case are unlikely to occur as far out as the 27-m isobath on the West Florida shelf, coastal and estuarine benthic communities are more likely to be limited by light despite shade adaptation Furthermore, in shallower environments tidal mixing is more likely to suspend lithic and biogenic solids, which wo uld further attenuate li ght. It is probable that the mid-shelf environment is the most ideal location for the growth of benthic microflora, ass umin g nutrient l imitat ion can be alleviated. One factor important to the success of benthic microflora with respect to nutrient limitation is the flux of nutrients across the sediment/water interface. Recent benthic flux chamber studies in the South Atlantic Bight suggest that nutrients diffuse out of the 64

PAGE 77

coarse grained sediments at rates of 50-250 t i mes the molecular diffusion rates (R. Jahnke, personal communication) Since a similar sediment environment exists on the West Florida shelf a third case of the model was run to test the effect of enhanced diffusion at 250 times the molecular diffusion rate on the success of benthic microalgae In contrast to the nearshore DOC case pelagic parameters in the "enhanced diffusion" case did not vary significantly from the baseline scenario Sediment parameters, however, were quite different. Benthic chlorophyll (figure 35) reached a peak stock of39.5 mg m -2 on day 49 of the enhanced diffusion case, compared to a peak stock of37.9 mg m-2 on day 49 of the baseline simulation After day 49, however, benthic chlorophyll stocks fell to 23.7 mg m -2 almost 7 mg m -2 less than the baseline Although pore-water nutrient concentrations were not any higher in the first several days of the simulation relative to the baseline nitrate and silicate diffused into the sediments at greater rates than in the basel i ne (figure 38) In this simulation, the sediments became a significant s i nk for nitrate and silicate This reversal in diffusion direction is due in large part to the increase in NH4 efflu x. Like the baseline case DOC diffused into the sedim e nts in the first few days of the simulation (figure 39). This led to due to ammonification of the DON bound to the simulated DOC. In this case however diffused out of the sediments at rates between 0 2 and 0 9 mmol m -2 day-1 after day 10. This is much faster than the integrated sediment nitrification rate o f O .Ol mmol m2 day"1 In contrast, NH4 flux in the baseline case occurred at appro x imately the same rate as sediment nitrification (figure 25) allowing n i trate concentration to increase in the pore-waters 65

PAGE 78

Since the rapidly diffused out of the sediments during the enhanced diffusion case, the bacteria in the water column instead oxidized it to N03 N03 concentrations in the near-bottom water of this case, however, were not significantly greater than those of the baseline case. The nitrate was not taken up by the light limited phytoplankton either Instead, a small proportion of it was mixed into the upper water column, while the rest diffused back into pore-waters (figure 38), where it was taken up by the rapidly growing benthic microalgae (figure 35). As the benthic microalgae reached its peak population on day 49, the pore-water nutrient concentrations gradually declined to a low (figure 36) While the declining benthic diatom population was remineralized in the sediments, NH4 continued to diffuse into the ammonium depleted near-bottom waters where it was oxidized, and a proportion of the nitrogen was returned to the sediments as N03 while a small proportion was mixed into the upper water column, where the nitrogen starved pelagic diatoms took it up. Eventually, the benthic diatoms became nitrogen limited (figure 37) and declined to a chlorophyll stock of only 23 7 mg m-2 Meanwhile, surface chlorophyll concentrations were only slightly higher than the baseline One might assume that dramatic shifts in the nitrogen limited surface phytoplankton should occur, given the loss of approximately 1/3 of the benthic microfloral biomass. However, a nitrogen flux of 1 mmol m2 day1 is equivalent to only 0.08 kg-1 when diluted over the lower 12-m of the water column, or 0.03 kg-1 when diluted over the entire water column In contrast, from the perspective of a benthic diatom in the top 1 em of sediments, a flux of 1 mmol m-2 day-1 is equivalent to a loss of 100 kg-1 in terms of volume. 66

PAGE 79

In terms of carbon, the day 86 difference of 17.5 mmol C m2 integrated over the top 1 em of sediment between the baseline and enhance d d iffusion cases translates to 0 6 mmol C m3 over the entire water column, or an average chlorophyll increase of only 0 16 1-1 j.lg 67

PAGE 80

Conclusions Benthic microalgae have already been shown to be important factors in some continental shelf ecosystems (Cahoon & Cooke, 1992; Nelson eta/. 1999) Light limitation is a factor controlling growth of the microphytobenthos in these ecosystems, but their ultimate success or failure seems to depend on regenerated nutrients from pelagic sources. Light limitation of the microphytobenthos in these simulation analyses occurred during cloudy days, times of high phytoplankton biomass and during a simulation of typical nearshore CDOC to the upper water column. When not limited by light the benthic micro algae were most often limited by phosphorus due to uptake of phosphate by heterotrophic nitrifying bacteria in the near-bottom water. Nitrogen limitation occurred near the end of the enhanced diffusion case after nitrogen was gradually mixed back ro the upper water column. The results of this analysis suggest that the sinking detritus and grazing products of pelagic phytoplankton blooms provide efficient transport to nutrient limited benthic algae. Such transport is not I 00% efficient, however. Integrated benthic chlorophyll often exceeds integrated water column chlorophyll at the 27-m i sobath on the West Florida shelf and in the South Atlantic Bight (G.Vargo, personal communication, Nelson et al., 1999) Furthermore, integrated benthic microalgal biomass ultimately exceeded integrate d phytoplankton biomass in this analysis It is important to note, however, that 68

PAGE 81

the maximum integrated benthic microalgal biomass achieved during this analysis (98.6 rnmol m-2 on day 49 of the enhanced diffusion case) was only about 2/3 of the initial integrated phytoplankton biomass of 146.1 mmol m-2 Consistent with the fmdings of Hitchcock et al. (2000), much of the reminerali z ed organic matter from the declining surface phytoplankton bloom was taken up by heterotrophic bacteria The ultimate decline in benthic microalgal biomass during the enhanced diffusion case is consistent with observations of lower benthic chlorophyll stocks following sustained wind events (Nelson et al., 1999) in the South Atlantic Bight. Whether this is due to resuspension, light limitation, or simply enhanced diffusion is not obvious from the current set of observations A three dimensional analysis would provide more clues into this process since near-bottom flows could be taken into account in computing an enhanced diffusion coefficient. Furthermore such an analysis could begin to identify if and how the regenerated nutrients ultimately leave the shelf environment. Since the benthic microalgae are dependent on a declining bloom as a nutrient source this form of benthic production is regenerated production. Unless the benthic microalgae are capable of growing on sources of nutrients other than those in this analysis they cannot be considered a significant source of new production on the continental shelf. They are, however important factors in controlling flux across the sediment/water interface Benthic flux experiments on the 27m isobath of the SAB (Jahnke et al., 2000) found twice the amount of oxygen in light chambers, compared to dark ones Likewise silicate concentrations in the dark chambers were more than double those in the light Furthermore, ammonium fluxes in light chambers at the 27m isobath were 12 m-2 69

PAGE 82

dai1 in August during a period of high benthic chlorophyll (Nelson eta/, 1999) and 62.4 J..tmol m -2 in May (Marinelli eta/, 1998) during a period of background benthic chlorophyll, compared to 1,384 Jlmol m-2 dai1 on the highly turbid 5 m isobath of the South Atlantic Bight, where zero light penetrates to the sediment surface (Hopkinson, 1987) Increased diffusive fluxes of nutrients out of the sediments (figure 25) and decreased diffusive flux ofDIC into the sediments (figure 26) during episodic periods low benthic net photosynthesis (figure 22) are consistent with these observations, such that the observed fluxes on the SAB presumably represent environments with high (August, 27 m isobath), low (May, 27 m isobath) and no (5 m isobath) benthic microalgal populations. 70

PAGE 83

References Baines, S.B. and M.L. Pace. 1991. The production of dissolved organic matter by phytoplankton and its importance to bacteria: patterns across marine and freshwater systems Limnology & Oceanography. 36, 1078 1090. Banse, K. 1992 Grazing, temporal changes of phytoplankton, and the microbial loop in the open sea In : Primary productivity and biogeochemical cycles in the sea, eds. P G Falkowski & A.D. Woodhead, Plenum Press, New York Pp. 409-440 Bidle, K.D. and F Azam 1999 Accelerated dissolution of diatom silica by marine bacterial assemblages Nature. 397, 508 512 Blanchard, G F and P .A. Montagna 1992 Photosynthetic response of natural assemblags of marine benthic microalgae to short and long term variation of incident irradiance in Baffin Bay, Texas. Journal ofPhycology. 28, 7 14 Cahoon, L.B and J.E. Cooke 1992 Benthic microalgal production in Onslow Bay, North Carolina, USA. Marine Ecology Progress Series. 84 185-196. Carlson, C.A. and H.W Ducklow 1995. Dissolved organic carbon in the upper ocean of the central equatorial Pacific Ocean 1992: Daily and finescale vertical variations Deep-Sea Research II 42, 639-656. Del Castillo, C.E., F Gilbes P G Coble and F E Miiller-Karger. 2000. On the dispersal of riverine colored dissolved organic matter over the West Florida shelf. Limnology and Oceanography 45, 1425 1432. Downs, J N. and C.J Lorenzen 1985. Carbon : pheopigment ratios of zooplankton fecal pellets as an index of herb i vorous feeding Limnology and Oceanography. 30, 1024-1036. Ducklow, H 2000. Bacterial production and biomass in the oceans. In : Microbial Ecology of the Oceans. Ed: D L Kirclunan Wiley-Liss, New York Pp. 85-120. Gilbes, F C Tomas, J.J. Walsh and F.E Miiller Karger. 1996. An episodic chlorophyll plume on the West Florida Shelf. Continental Shelf Research 16, 12011224. 71

PAGE 84

del Giorgio P .A. and J.J Cole 2000. Bacteria l growth ener g etics and growth efficiency. In: Microb i al ecology o f the oceans Ed : D.L. Kirchman Wilet-Liss New York Pp 289-325 Hattori A., J.J Goering, and D .B. Boisseau 197 8 Ammonium ox i dation and its significance in the summer cycl i ng of nitrogen in o xy gen depleted Skan Bay Unalaska Alaska Mar Sci. Comm 4 139 -151. Henrichs S M and J.W. Farrington. 1984. Peru upwelling sediments near 15 S 1. Reminiralization and accumulation of organic matter Limnology & Oceanography 29, 1 -19. Hitchcock, G.L., G.A. Vargo and M .L. Dickson. 2000 Plankton community composition production and respiration in relation to dissolved inorganic carbon on the West Florida shelf, April 1996 Journal of Geophysical Research 105 6579-6589. Hopkinson, C.S 1985. Shallow-water benthic and pelag i c metabolism-ev i dence of heterotrophy in the nearshore Georgia Bight. Marine Biology 87 19 32 Hopkinson C S Jr. 1987 Nutrient regeneration in shallow water sediments of the estuarine plume region of the nearshore Georgia Bi g ht USA Marine Biology. 94, 127-142 Jahnke R.A., J.R Nelson R.L. Marin e lli and J E Eckman 2000 Benthic flux of biogenic elements on the s outheas tern U S continental sh e lf: influence of pore w a ter advective transport and benthic microalgae Continental shelf research 20, 109 127. Jumars P A., D.L. Penry J .A. Baross, M.J Perry and B.W. Frost. 1989 Closing the microbial loop : dissolved carbon pathway to heterotrophic bacteria from incomplete ingestion digestion and absorption in animals Deep-Sea Reasearch 36 483 496 Kamatani A and J P Riley 1979 Dissolution of diatom sil i ca walls in seawater Marine Biology 55, 29 -35. Kirchman, D.L., Y. Su z uki, C. Garsid e and H W Ducklow 1991. High turnover rates of dissolved organic carbon during a spring phytoplankton bloom Nature. 352 612 614 Kirk, J T O 1994 Light and Photosynthesis in Aquatic Ecosystems Cambridge University Press, Cambridge United Kingdom 72

PAGE 85

Kleppe!, G.S C.A. Burkart, K. Carter and C Tomas. 1996 Diets of calanoid copepods on the West Florida shelf: relationships between food concentration, food composition and feeding activity. Marine Biology. 127, 209218. Klump J.V and C.S. Martens 1981. Biogeochemical cycling in an organic rich coastal marine basin. II Nutrient sediment-water exchange processes Geochim. Cosmochim Acta 45, 101 121. Lewin, J.C 1961. The dissolution of silica from diatom walls Geochimica et Cosmochimica Acta. 21, 182 -198. Macintyre, H.L., R.J Geider and D.C. Miller. 1996. Microphytobenthos: the ecological role of the "secret garden" of unvegetated, shallow-water marine habitats I. Distribution, abundance and primary production Estuaries 19, 186-201. Marinelli, R.L. 1992. Effects of polychaetes on silicate dynamics and fluxes in sediments : Importance of species, animal activity and polychate effects on benthic diatoms. Journa l ofMarine Research. 50,745-779 Marinelli R.L., R.A. Jahnke, D B Craven, J.R. Nelson and J.E Eckman 1998. Sediment nutrient dynamics on the South Atlantic Bight continental shelf Limnology & Oceanography. 43, 1305 1320. Martin D.W. 1984 Clastic to carbonate transitionsa modem example: the West Florida shelf. Masters Thesis. Univ S. Florida Mellor, G.L. and T. Yamada 1982 Development of a turbulence closure-model for geophysical fluid problems. Reviews of Geophysics. 20 851-875 Mopper, K. X Zhou R.J Kieber, D.J Kieber, R.J. Sikorski and R.D. Jones. 1991. Photochemical degradation of dissolved organic carbon and its impact on the oceanic carbon cycle Nature. 353 60 62. Morel, A 1988. Optical modelling of the upper ocean in relation to its biogenous matter content (case 1 waters). Journal of Geophysical Research. 93, 10749-10768. Morse, J.W 1974 Calculation of diffusive fluxes across the sediment-water interface Journal of Geophysical Research 33, 5045 5048. Miiller-Karger, F E., J.J Walsh, R.H Evans and M.B. Meyers 1991. On the seasonal phytoplankton concentration and the sea surface temperature cycles of the Gulf of Mexico as determined by satellites. Journal of Geophysical Research 96, 12,645-12,665. 73

PAGE 86

Mullin M M E.F. Stewert and F.J Fuglister 1975 Ingestion by planktonic grazers as a function of concentration of food Limnology and Oceanography 20 259 262. Nelson D.M. and Q Dortch 1996 Sil i cic acid depletion and silicon limitation in the plime of the Mississippi River : evidence from kinetic studies in spring and summer. Marine Ecology Progress Series 136, 163 178 Nelson, J.R., J.E. Eckman, C Y Robertson R.L. Marinelli and R.A. Jahnke. 1999 Benthic microalgal biomass and irradiance at the sea floor on the continental shelf of the South Atlantic Bight: spatial and temporal variability and storm effects Continental ShelfResearch 19, 477-506 Paffenhofer G.A. and S C.Knowles 1979 Ecological implications of fecal pellet size production, and consumption by copepods. Journal of Marine Research 37, 35-49. Peng, T.H., T Takahashi W S Broecker and J Ol a fsson. 1987 Seasonal variability of carbon dioxide nutrients and oxygen in the northern North Atlantic surface water: observations and a model. Tellus 39B, 439 458 Pinkney J.L. and R.G Zingmark. 1993. Modeling the annual production of intertidal benthic mic r oalgae in estuarine ecosystems Journal ofPhycology. 29, 396-407. Rowe, G.T. and W.C Phoel. 1992 Nutrient regeneration and oxy g en demand in Bering Sea continental shelf sediments. Continental Shelf Research. 12, 439 450. Sambrotto R.N., G Sav i dge C. Robinson P Boyd, T Takahashi D M Karl C Lan g don D Chipman J. Marra and L. Codispoti 1993 E leva t ed consumption of carbon relative to nitrogen i n the surface ocean Nature 363, 248 250 Schink, D R. and N L. Guinasso 1977 Effects ofbioturbation on sediment-seawater interaction Marine Geology 23, 133-154 Steidinger, K.A. Phytoplankton 1973 In: A summary ofKnowledge of the Eastern Gulf of Mexico Am. Pet. lnst. Pp IIIE-1 to IIIE-17. Sundback, K. and W. Graneli 1988 Influences of the microphytobenthos on the nutrient flux between sediment and water : a laboratory study Marine Ecology Progress Series 43 63 69 Sundback, K ., V Enoksson, W. Gran eli and K. Pettersson. 1991. Influence of sublittoral microphytobenthos on the o x ygen and nutrient flux between sediment and water : 74

PAGE 87

a laboratory continuous-flow study Marine Ecology Progress Series 74, 263279 Vargo, G.A ., K L. Carder, W. Gregg E Shanley C. Heil, K.A. Steidinger and K D Haddad. 1987 The potential contribution of primary production by red tides to the west Florida shelf ecosystem Limnology and Oceanography 32 762-767 Walsh J.J. Death in the sea : enigmatic phytoplankton losses. 1983 Progress in Oceanography 12 1-86. Walsh, J.J and D.A. Dieterle. 1994 C02 cycling in the coastal ocean I. A numerical analysis of the southeastern Bering Sea, with applications to the Chukchi Sea and the northern Gulf of Mexico Progress in Oceanography 34, 335-392 Walsh, J.J and K.A Steidinger 2001. Saharan dust and Florida red tides: the cyanophyte connection Journal of Geophysical Research Oceans. 106, 1159711612 Walsh, J.J., K.L. Carder and F E Mtiller-Karger 1992. Meridional fluxes of dissolved organic matter in the North Atlantic Ocean Journal of Geophysical Research 97, 15625 15637 Walsh, J.J., D A Dieterle and J Lenes 2001. A numerical analysis of carbon dynamics of the Southern Ocean phytoplankton community : the roles of light and grazing in effecting both sequestrato i n of atmospheric C02 and food availability to larval krill. Deep-Sea Research Part I -Oceanographic Research Papers 48, 1 48 Walsh, J.J D A. Dieterle and M.B. Meyers 1988 A simulation analysis of the fate of phytoplankton within the Mid-Atlantic Bight. Continental Shelf Research 8, 757-787 Walsh, J.J ., R H Weisberg D A. Dieterle R He B P. Darrow W P Bissett G A Vargo, G.J Kirkpatrick, K A. Fann i ng T.T Sutton D C Bigs and F E Mtiller-Karger. The phytoplankton response to intrusions of slope water on the West Florida shelf: models and observations In pre paration. Wanninkhof, R G. Hitchcock, W.J Wiseman, G. Vargo, P.B Ortner, W. Asher, D T. Ho, P. Schlosser, M Dickson, R. Masserini, K. Fannng and J. Zhang. 1997 Gas exchange, dispersion and biological productivity on the West Florida shelf: results from a Lagrangian tracer study. Geophysical Research Letters 24, 17671770 Ward, B B. 1986 In 'Nitrification (Ed J. Prosser). S G.M. Sp e cial Publications. 20 157 184. IRL Press Oxford. 75

PAGE 88

Wood, P.M. 1987. In 'Nitrification' (Ed. J. Prosser). S G M. Special Publications. 20, 39 62. IRL Press, Oxford. Weisberg, R.H., B.D. Black and H. Yang. 1996 Seasonal modulation of the West Florida shelf circulation. Geophysical Research Letters 23, 2247-2250. Yang, H. and R .H. Weisberg. 1999. Response of the West Florida shelf circulation to climatological wind stress forcing. Journal of Geophysical Research. 104,53015320. 76


printinsert_linkshareget_appmore_horiz

Download Options

close
No images are available for this item.
Cite this item close

APA

Cras ut cursus ante, a fringilla nunc. Mauris lorem nunc, cursus sit amet enim ac, vehicula vestibulum mi. Mauris viverra nisl vel enim faucibus porta. Praesent sit amet ornare diam, non finibus nulla.

MLA

Cras efficitur magna et sapien varius, luctus ullamcorper dolor convallis. Orci varius natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Fusce sit amet justo ut erat laoreet congue sed a ante.

CHICAGO

Phasellus ornare in augue eu imperdiet. Donec malesuada sapien ante, at vehicula orci tempor molestie. Proin vitae urna elit. Pellentesque vitae nisi et diam euismod malesuada aliquet non erat.

WIKIPEDIA

Nunc fringilla dolor ut dictum placerat. Proin ac neque rutrum, consectetur ligula id, laoreet ligula. Nulla lorem massa, consectetur vitae consequat in, lobortis at dolor. Nunc sed leo odio.