Received on July 24, 2003; accepted on December 22, 2003 Final version

Phytoplankton community growth-rate -response to nutrient pulses in a shallow turbid estuary, Galveston Bay, Texas

Erla Björk Örnólfsdóttir1 , S. Elizabeth Lumsden and James L. Pinckney

Estuarine Ecology Laboratory, 3146 TAMU, Department of Oceanography, Texas A&M University, College Station, TX, 77843-3146, U.S.A.

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Current address: Center for Coastal Fisheries and Habitat Research, National Ocean Service, NOAA,

101 Pivers Island Road, Beaufort, NC 29516.

Phone: 252 728 8792 Fax:

252 728 8784

Email: [email protected]

Running title: Phytoplankton growth rate response to nitrate pulses

Keywords: chemtax, diatoms, growth rate, nanophytoplankton, nutrients, phytoplankton, Texas

Journal of Plankton Research,  Oxford University Press; all rights reserved

ABSTRACT

Phytoplankton growth is a physiological process often limited by temperature, nutrients or light while biomass accumulation is a function of growth rates, grazing, and deposition. Although primary productivity measurements are usually used to assess responses to limiting factors, the rates are proportional to biomass and inversely related to grazing pressure during experimental incubations. Alternatively, carbon-specific growth rate determinations provide insights into physiological responses without the confounding effects of biomass and grazing. The objective of this study was to quantify the growth rate responses of phytoplankton to enhanced nutrient availability (nitrate and phosphate) over a range of in-situ irradiances. Growth rates were determined based on chl a-specific 14C uptake rates by phytoplankton. Phytoplankton demonstrated high (24h) growth rates when exposed to increased concentrations of limiting nutrients independent of the surface irradiances (12 – 41%). Growth rate responses were also compared with the biomass (chl a) responses and community composition. Observed and estimated phytoplankton biomass changes during the incubations differed, emphasizing the structural role of grazers on the phytoplankton community. The phytoplankton community in Galveston Bay has the potential to instantaneously respond to nutrient pulses, facilitating diatom biomass accumulation in spring and summer and small flagellated species and cyanobacteria during periods of low nutrient inputs. Thus Galveston Bay phytoplankton biomass and community composition reflect a dynamic balance between the frequency of nutrient pulsing and grazing intensity.

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INTRODUCTION

Excess nutrient enrichment of estuarine ecosystems is a widespread consequence of human population increases in the coastal zone and this trend is predicted to further increase in the 21st century (Nixon 1995). High rates of nutrient loading to coastal environments frequently enhances phytoplankton growth and biomass and increases the rate of organic matter loading, ultimately resulting in eutrophication (Nixon 1995; Smith et al., 1999). The nutrient stimulus is often associated with increased availability of nitrogen sources (Ryther and Dunstan, 1971; Capone 2000). However, local and seasonal phosphate induction of phytoplankton growth is frequently observed (Fisher et al., 1992; Fisher et al., 1999; Holmboe et al., 1999). Additionally, the potential for nutrient limitation in aquatic ecosystems (both marine and freshwater) is usually governed by the concentration of nitrogen and phosphorus (combined dissolved organic and inorganic forms) and the relative ratio of these two major nutrients (Guildford and Hecky, 2000). Furthermore, nutrient inputs into coastal waters can support phytoplankton growth and biomass to the level where other nutrients such as silica become growth limiting (Dortch and Whitledge, 1992; Justic et al., 1996; Malone et al., 1996). Knowledge of the spatio-temporal growth rate responses of estuarine phytoplankton communities to increased nutrient loading offers insights into the potential effects of eutrophication on energy transfer within the ecosystem and provides a tool for establishing ecologically relevant management strategies (C onley 2000; Olsen et al., 2001). The impacts of eutrophication on estuarine ecosystems can be quite different and some estuaries exhibit low phytoplankton biomass even when nutrient levels are high (Alpine and Cloern, 1992; Le Pape and Menesguen, 1997). Turbid estuaries frequently exhibit this condition (Cloern 1999). Constrained phytoplankton biomass and productivity in estuaries due to light limitation is welldocumented for natural phytoplankton assemblages (Cole and Cloern, 1984; Pennock and Sharp, 1994; Middelburg and Nieuwenhuize, 2000). Similar responses have been illustrated using mathematical models of phytoplankton growth (Geider et al., 1998; Flynn et al., 2001). Using model simulations, Cloern (Cloern, 1999), showed that the interactive effects of light and nutrient limitation on phytoplankton growth is a dynamic continuum in which estuaries can be nutrient, light or both nutrient and light limited over broad ranges of nutrient and light resources. The form of phytoplankton growth limitation depends on the relative concentration of the two limiting resources (light and nitrogen) (Cloern, 1999). Galveston Bay is one of seven major estuaries in Texas and its drainage basin includes the major cities of Houston and Dallas-Fort Worth. Armstrong and Ward (Armstrong and Ward , 1993) 3

reported that Galveston Bay receives approximately 60% of the urban and industrial wastewater of Texas. The estimated anthropogenic nutrient loading into the estuary is 2 - 9 g phosphorus m-2 year -1 and 16 - 45 g nitrogen m-2 year-1 (Santschi, 1995). Additionally, 1.7 g nitrogen m-2 year -1 presumably enters the estuary through atmospheric deposition (Santschi, 1995). Anthropogenic nitrogen input to Galveston Bay reached a historical maximum in the late 1970’s but has gradually declined since 1980 (Jensen et al., 1991). Based on the stochiometric ratio of nitrogen and phosphorus, Guillen (Guillen, 1999) suggested that phytoplankton in Galveston Bay is phosphorus limited. However, recent work has revealed that nitrate additions enhance phytoplankton biomass while phosphate amendments have no significant effect on biomass (Örnólfsdóttir, 2002). Paradoxically the estuary shows moderate or low phytoplankton biomass, with typical values of 13 - 17 µ g chl a l-1 in upper Trinity Bay (Strong, 1977; Krecji 1979; Smith, 1983) and 3.8 - 14.6 µ g chl a l-1 in Trinity and Galveston Bay, as summarized by Santschi (Santschi , 1995). The waters of Galveston Bay are turbid, containing 10 - 500 mg l-1 of suspended particulates (Santschi, 1995) thus it is possible that light availability limits phytoplankton growth rate during very turbid conditions. Assessing phytoplankton biomass response to controlled experimental treatments is a valuable first step approach for determining the positive or negative impacts of the nutrient manipulations on phytoplankton productivity in the presence of grazers. The change in biomass (chl a, carbon, biovolume or other measure) is a measure of the net ecosystem response to the experimental conditions. However, the phytoplankton response determined from simple changes in biomass may underestimate the actual magnitude of biomass production because losses due to grazing are not quantified. Carbon-specific growth rate measurements, particularly when based on the chlorophylllabeling method (Redalje and Laws, 1981, Goericke and Welschmeyer, 1993), provide a sensitive, physiologically-based measure of potential phytoplantkon biomass accumulation in the ecosystem. Natural phytoplankton assemblages, commonly grow under non-optimal growth conditions. Observed growth rates of phytoplankton assemblages range from 0.11 – 1.08 d-1 (Eppley, 1972; Redalje and Laws, 1981; Gieskes and Kraay, 1989). However, the growth rate of phytoplankton cultures grown under nutrient-replete conditions range from 0.26 - 2.75 d-1 (MacIntyre et al., 2002). The growth rate responses of natural phytoplankton communities across environmental gradients in space or time provides insights into the physiological mechanisms that regulate growth and subsequent changes in the relative abundance of algal groups. Furthermore, assessment of phytoplankton growth rates from manipulated bioassay experiments may provide predicable tools to infer the potential effects of anthropogenic nutrient loading on phytoplankton biomass and community structure. These

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physiological responses are an integral component in mechanistic models to predict ecosystem trophodynamics. The objective of this study was to quantify the instantaneous growth rate responses of natural phytoplankton communities in Galveston Bay to enhanced nutrient availability (nitrate+phosphate, N+P) over a range of in-situ irradiances. Observed phytoplankton growth rates were compared with phytoplankton biomass (chl a) responses and the impacts of phytoplankton growth changes on the phytoplankton community structure were assessed. The hypotheses tested were; 1) Addition of growth limiting nutrients (N+P) increases carbonspecific growth rates of phytoplankton, in particularly of nanophytoplankton; 2) Phytoplankton growth rates are lower in conditions of reduced surface irradiance compared to high light regimes; 3) Phytoplankton community structure remains unchanged following nutrient additions.

METHOD

Water collection Water for the experiments was collected from Galveston Bay at two of the seven long-term sampling stations established by the Estuarine Ecology Lab (Figure 1). Water was obtained at station 4 (21 km inshore of the mouth of the Bay) in March or station 5 (12 km inshore) in May and July. The water was collected using an integrated water sampler (PVC baler) that retained 3 liters of water from the uppermost meter of the water column. Samples were gently poured into acid cleaned 10 liter carboys and transported in an insulated cooler (chilled with ice) to the boat basin at Texas A&M University at Galveston (TAMUG). The jugs were stored overnight (18 h) in a floating corral in the boat basin until initiation of the experiment the next morning.

Experimental setup Upon initiation, the 10 liter jugs were taken from the corral and gently inverted a few times before 1 liter aliquots were poured into 1 liter Nalgene bottles (clear polycarbonate). The growth bioassays were composed of two manipulated factors, nutrients (two levels) and irradiance (three levels). Nutrient addition bioassays were conducted as control treatments (ambient nutrient concentrations) and a combined nitrate (N) and phosphate (P) addition of 10 µmol l-1 nitrate (NaNO3) and 3 µ mol l-1 phosphate (KH2PO4) to the experimental water. The three light leve ls used were 41, 30 and 12% of the incident surface irradiance. Light levels were regulated by placing the incubation bottles in bags of 1, 2 5

and 3 layers of neutral density screen (gray fiberglass mesh), respectively. Each nutrient treatment was conducted in triplicate at each light level. 14

C pigment radiolabelling

Incubation bottles (1 liter) were spiked with 25 µCi ml-1 of

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C (NaHCO3) prior to incubation. The

experimental protocols and initial analysis were performed according to the methodology described by Redalje (Redalje, 1993a). The initial dissolved inorganic carbon (DIC) concentration (µ g l-1) of the experimental water was measured in two sub-samples from every jug containing the experimental water. The DIC samples (100 ml) were poured into acid clean plastic bottles and kept tightly closed until analyzed, within 5 h. The DIC content of the samples was determined based on pH of the sample before and after acidification with 0.01N HCl (Parsons et al., 1984).

HPLC analysis of pigments Upon termination the bottles were removed from the incubation bags and stored in a darkened box until filtration was completed. Aliquots (150-300 ml) from each bottle were filtered under low vacuum onto 25mm glass fiber filters (Whatman GF/F) for phytoplankton pigment and chl a-specific 14C analysis. Similarly, an aliquot was screened through 20 µM Nytex mesh and filtered onto 25mm GFF filters from each bottle for nanophytoplankton pigment and chl a- specific

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C analysis. The filter samples

were immediately frozen on dry ice and stored at -80ºC until analyzed. The GF/F filters containing phytoplankton were extracted in 100% acetone (0.75 ml), gently mixed and homogenized with a flat spatula and stored at -20°C for 15 - 20 h before analysis. Filtered extracts (300 µ l) were mixed with 150 µ l of 1M ammonium acetate ion-pairing solution and injected directly into a Hewlett Packard model 1100 HPLC equipped with a single monomeric (Hewlett Packard ODS Hypersil; 100 x 4.6mm, 5 µ l) and two polymeric (Vydac 201TP, 250 x 4.6, 5 µm) reverse-phase C18 columns in series, connect to a photodiode array detector. The mobile phases and solvent flow rates followed that described by Pinckney et al. (Pinckney et al., 1996). Solvent A consisted of 80% methanol:20% ammonium acetate (0.5 M adjusted to pH 7.2) and solvent B was composed of 80% methanol:20% acetone. The column temperature was 40°C. Pigment peaks were identified by comparison of retention times and absorption spectra with pure crystalline standards of chlorophylls a, b, β-carotene (Sigma Chemical Company), fucoxanthin, lutein, canthaxanthin, and zeaxanthin (Hoffman-LaRoche and Company). Other pigments were identified by comparison to extracts from

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phytoplankton cultures (Wright et al., 1991). Photopigment concentrations were quantified using chromatogram peak area and the appropriate extinction coefficients (Rowan, 1989; Jeffrey et al., 1997).

Phytoplankton growth rate Phytoplankton growth rate was determined based on chl a- specific

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C uptake by phytoplankton

(Redalje and Laws, 1981; Redalje, 1993a, b; Welschmeyer and Lorenzen, 1984). The chl a -specific growth rate estimate provides a carbon specific estimate of algal growth rate (i.e., µ) independent of grazing and the presence of other organic carbon sources (Redalje and Laws, 1981; Redalje, 1983; Welschmeyer and Lorenzen, 1984). Chl a -specific growth rate estimates were assumed to approximate the carbon-specific growth rate (i.e., balanced growth) (Redalje, 1983; Welschmeyer and Lorenzen, 1984). Imbalance between chl a synthesis and precursors (tetrapyrrole and phytol) synthesis frequently occurs as the precursors are formed during daylight hours while chl a is synthesized during day or night (Goericke and Welschmeyer, 1992, 1993). Goericke and Welschmeyer (1993) proposed that all chl a specific growth rate estimates should be based on 24 hour incubations (dawn to dawn), because the time of chl a synthesis (within a diel cycle) cannot be predicted due to lack of information on the light history of natural phytoplankton assemblages. Thus all incubations were initiated in early morning (7:00) and terminated the next morning in attempt to fulfill the conditions necessary for the assumption of balanced growth of the algae. Phytoplankton growth rate (d–1 ) was calculated as defined by Redalje (Redalje, 1993a) and Pinckney et al. (Pinckney et al., 1996). Photopigment associated

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C radioactivity was identified and quantified using an inline flow

scintillation counter (Packard Radiomatic 525A) connected to the HPLC. The eluent of the HPLC was mixed with scintillation cocktail (Ultima Flo M, Packard) prior to flowing into the scintillation counter. The radiogram lagged behind the chromatogram by a few seconds, depending on the flow rate of the sample through the HPLC columns and radiodetector. The radioactive peak for chl a was most distinctive and integrated as the phytoplankton community growth rates for respective samples. The major phytoplankton groups contributing to the phytoplankton growth rate response were determined using CHEMTAX (Figure 2).

Chemical Taxonomy ChemTax (Chemical Taxonomy) is a matrix factorization routine for calculating algal class abundances based on the concentrations of diagnostic chlorophyll and carotenoid photopigments (Wright et al., 1996; Mackey et al., 1997; Pinckney et al., 1998). The program uses a steepest descent algorithm to determine the best fit based on an initial estimate of pigment ratios for algal classes. Input for the 7

program consists of a raw data matrix of photopigment concentrations obtained by HPLC analyses and an initial pigment ratio file. The data matrix is subjected to a factor minimization algorithm that calculates a best-fit pigment ratio matrix and a final phytoplankton class composition matrix. Thus, ChemTax partitions the total chl a into major phytoplankton groups. The complexity of the estimated community structure depends upon the number of phytoplankton groups defined a priori by the researcher. We took a conservative approach in defining the initial ratio matrix, restricting our resolution to diatoms, chlorophytes, cyanobacteria, cryptophytes, dinoflagellates, two groups of haptophytes (hapto3s and hapto4s) and gyroxanthin-containing dinoflagellates. Hapto3s and hapto4s were

distinguished

by

the

diagnostic

pigments

19’hexanoyloxyfucoxanthin

and

19’butanoyloxyfucoxanthin, respectively (Jeffrey and Wright, 1994). These seven algal groups are commonly detected in estuarine waters (Roy et al., 1996; Tester et al., 1995; Cloern, 1996).

Nutrient analysis Water samples were filtered through combusted (350°C, 2.5 h) Whatman GF/F (25 mm) filters, poured into acid-rinsed Nalgene bottles and stored at –20°C until analyzed. Nitrate, nitrite, urea, phosphate and silica were quantified according to Practical manual for the use of the Technicon Autoanalyzer in seawater nutrient analyses (Atlas et al., 1971) and ammonium was quantified according to method developed by Ross and Jennings (Mr. Dennis Guffy pers. comm.).

Statistics Nonparametric statistics were used for statistical analysis when the number of measurements was at or close to the lower limit of measurements needed for parametric approaches (Dytham 1999). Phytoplankton growth rate responses and biomass changes were tested using the Mann-Whitney U test for total phytoplankton and nanophytoplankton (Sokal and Rohlf, 1981). Test for significant differences in growth rate of total phytoplankton community and the nanophytoplankton fraction were performed using the Wilcoxon signed rank test as the samples were related (Dytham, 1999). Changes in the relative abundances of algal groups in response to nutrient treatments were tested using ANOVA (Dytham, 1999). Changes in phytoplankton community composition across nutrient and light treatments were tested using a multivariate analysis of variance (Manova) and Bonferroni post hoc analysis of arcsin square-root transformed relative contributions (%) of individual phytoplankton groups to the phytoplankton biomass upon termination of the individual treatments.

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RESULTS

Nutrients The experiments spanne d a broad range in initial phytoplankton biomass (chl a) and ambient inorganic nutrient concentrations (Figure 3). In March and May, the ambient dissolved inorganic nitrogen concentrations (DIN as nitrate + nitrite + ammonia) were 43.6 and 21.5 µ mol l-1 , respectively but 1.9 µmol l-1 in July. Similarly, the initial phytoplankton biomass ranged from 21.5 to 8.4 µ g chl a l-1 , in March to July respectively (Table I). The total DIN concentration increased by a factor of 1.2, 1.5 and 10 when nitrate (NaNO3) additions of 10 µ mol l-1 were added to the ambient concentrations in the experimental treatments. Phosphate levels, on the other hand, increased by a factor of 2.4 in May and by a factor of 2 in March and July when phosphate (3 µ mol l-1 KH2PO4) was added to the ambient nutrient concentrations. Initial silica concentrations ranged from 38.1- 45.4 µmol l-1.

Growth rates Phytoplankton growth rate responses of the total phytoplankton community and the nanophytoplankton were significantly higher (Mann-Whitney U test, N=9, p 0.05). The growth rate ranged from 1.0 - 1.2 d-1 in the control treatments while average growth rate of nutrient addition treatments was 1.1 d-1 (Figure 4). No significant differences were detected in phytoplankton growth rate between the experiments of decreasing surface irradiances. The growth rate responses of the whole (unfractionated) phytoplankton community and the nanophytoplankton community were not significantly different between the three surface irradiances tested (Mann-Whitney U test, N = 6, p > 0.05). Furthermore, nanophytoplankton growth rate was not significantly different from total phytoplankton growth rate in March and July (Wilcoxon signed rank test N = 18, p > 0.05), but significantly higher than the total phytoplankton community growth rate estimate in May (Wilcoxon signed rank test N = 18, p < 0.05). 9

Phytoplankton biomass Phytoplankton biomass at the termination of the experiments reflected the observed differences in phytoplankton growth rates. In May and July, phytoplankton biomass was significantly higher (MannWhitney U test, N = 9, p < 0.05) in nutrient addition treatments compared to the controls at all three levels of irradiance. In May the total phytoplankton biomass in the nutrient addition treatments was double that of the control bottles, ranging from 37.8 – 44.4 µ g chl a l-1 in the N+P, compared to 21.8 – 24.9 µ g chl a l-1 in the control treatments (Figure 5). The phytoplankton biomass in the N+P additions in July was 3 times the biomass in the controls (8.9 – 16.2 µ g chl a l-1 vs. 3.3 – 4.4 µ g chl a l-1) but the phytoplankton biomass (chl a) in the control treatments had declined to half of the biomass present at the beginning of the incubation (Figure 5). However, in March 2001, when the incubation water had a high initial phytoplankton biomass (21 µ g chl a l-1 ) and total DIN concentrations (43.63 µ mol l-1 ), the total phytoplankton biomass was not significantly different between control and nutrient treatments at the termination of the experiment (Mann-Whitney U test, N = 9, p > 0.05). After 24 h of incubation the phytoplankton biomass in all treatments was double the initial biomass, ranging from 35 - 43 µ g chl a l1

(Figure 5). Nanophytoplankton was the major group contributing to the phytoplankton biomass,

comprising an average of 84, 69 and 88% of the total phytoplankton biomass (chl a) in March, May and July (Figure 5). The nanophytoplankton biomass response to nutrient and light manipulations mirrored the signal of the unscreened incubations thus no significant change of biomass was detected in March whereas in May and July, nanophytoplankton biomass was significantly higher in the N+P treatments compared to the controls (Mann-Whitney U test, N = 9, p < 0.05) (Figure 5).

Phytoplankton community assemblages Community structure of the nano- and total phytoplankton community showed the same general trends at all times (data not shown for na nophytoplankton). Diatoms were the most abundant group, contributing 45 - 86% to the phytoplankton biomass (chl a) in all the experiments (Figure 6). Similarly, crypotophytes, chlorophytes and cyanobacteria were present in lower abundances than diatoms in all incubations. Significant changes in phytoplankton community composition were detected between the control and N+P addition treatments in all experiments (Table II). N+P additions in May increased the relative abundance of diatoms in the total phytoplankton community and the nanophytoplankton 10

fraction, coinciding with a relative decrease in the contribution of chlorophytes in N+P treatments compared to the controls (ANOVA, p < 0.05). The relative contribution of nanophytoplankton-sized cryptophytes and cyanobacteria also decreased in the N+P treatments relative to the control treatments in the bioassay conducted in May (ANOVA, p < 0.05). In July, during low initial DIN concentrations, the relative contribution of diatoms to total phytoplankton biomass (chl a) was significantly higher in N+P treatments compared to their contribution to biomass in the controls (ANOVA, p < 0.05). Simultaneously, cyanobacteria, cryptophytes and “other” phytoplankton groups significantly decreased in relative abundance in the N+P treatments (ANOVA, p < 0.05), The relative contribution of chlorophytes remained unchanged. The observed changes in phytoplankton community composition in July were consistent between algae in the nanophytoplankton size range and the total phytoplankton community. In March the relative contribution of “other” algae (dinoflagellates and haptophytes) was significantly higher in control treatments compared to the N+P amendment treatments for nanophytoplankton (ANOVA, p < 0.05) but no significant changes were observed for any other group of phytoplankton (Table II). In July nutrient and light had significant synergistic effects on phytoplankton community structure, indicating that the light response was enhanced by the nutrient availability. The relative contribution of diatoms to the total phytoplankton biomass was significantly higher at 12% surface irradiance compared to the incubations of 30 and 41% surface irradiance (MANOVA, p < 0.05). Cyanobacteria showed the opposite trend and were significantly less abundant at 12% surface light intensity compared to the incubations at 30 and 41% of surface irradiance. Chlorophytes contributed a larger fraction to total biomass in the incubation at 41% surface irradiance compared to the incubations at 30 and 12% irradiance, whereas cryptophytes were less abundant at the 41% light level compared with their proportional contribution to biomass of 30 and 12% incubations (MANOVA, p < 0.05). The percent contribution of nanophytoplankton-sized diatoms was significantly different among all light levels tested, decreasing in abundance with increased surface irradiance (Figure 6) (MANOVA, p < 0.05). Cyanobacteria abundance was also significantly different between all light levels but showed the opposite trend, increasing in relative contribution with increasing light (MANOVA, p < 0.05). The relative contribution of cryptophytes and chlorophytes was not significantly different among the light treatments but the relative contribution of other algae was significantly higher in incubations at 41% of surface irradiance than in the 12 and 30% light level incubations (Figure 6).

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DISCUSSION

Environmental setting and experimental design The experiments were conducted with bay water collected during periods of high and low freshwater inflow. The average daily discharge from Trinity River, the main freshwater tributary to the estuary (Armstrong and Ward, 1993), was 149.6 x 106 m 3 d-1 in March, whereas it was 14.1 and 7.6 x 106 m3 d-1 in May and July, respectively. Consequently the total DIN concentrations measured in the estuary were high in March and gradually declined through July, reflecting the previously reported negative correlation between total DIN and salinity (Santschi, 1995). Due to high ambient DIN concentrations, the added nitrate (10 µM) only enhanced the initial DIN concentrations by a factor of 1.2 in March compared to 1.5 and 6.3 in May and July, respectively. In spring of 2001 the phytoplankton collected for the incubation experiments was thus collected from a generally nitrogen-replete nutrient environment with respect to phytoplankton growth. Phytoplankton growth rate estimates were based on the chl a-specific uptake of radioactive carbon. Growth rate responses for phytoplankton in Galveston Bay were based on 24 hour incubations and comparison among control and nutrient treatments conducted at three levels of surface irradiance. The growth rate estimates of the control treatment were assumed to resemble the ambient phytoplankton growth rates, thus providing a baseline for placing the N+P effects on phytoplankton growth rates into perspective. However, the measured phytoplankton growth rate responses to variable surface light regimes only permitted relative comparisons among the conditions tested as the past average light environment of the phytoplankton used in the incubation experiments was not known.

Nutrient pulses and growth rate response The natural phytoplankton communities of Galveston Bay showed a rapid chl a-specific growth rate response to enhanced nutrient concentrations. In May and July phytoplankton growth rate in nutrient addition treatments was double and triple that of the control treatments, reaching µ of 0.8 and 1.3 d-1 , respectively. Similarly, the growth rate of nanophytoplankton was also double and triple that of the control incubations, reaching 1.1 and 1.2 d-1. The phytoplankton growth rate in March was the same in the control and N+P addition treatments and the results reflect the initially high N and P concentrations of the incubation water. The phytoplankton growth rate estimated for the March community was comparable to the observed growth rate of N+P treatments at other times, indicating that the N+P

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induced phytoplankton growth rate response detected in the bioassays in May and July was of the same magnitude as measured for phytoplankton during nutrient replete growth conditions. Nanophytoplankton growth rate responses were significantly higher than the total phytoplankton community growth rate in May but not significantly different at other times. The measured growth rate responses were possibly dominated by the nanophytoplankton because this size class contributes the largest proportion to the total phytoplankton biomass. The significant difference in growth rate response of the two fractions in May coincided with the lowest contribution of nanophytoplankton to the total biomass (69% vs. 84 and 88%), possibly increasing the influence of microphytoplankton on the measured growth rate. The significantly lower growth rate of the nonfractionated sample implies that the microphytoplankton growth rate was low enough to significantly affect the average estimate for the phytoplankton community as a whole. Microphytoplankton growth rate responses were not estimated specifically as the values would have been calculated based on the difference in measurements for total- and nanophytoplankton. The inherent errors in the calculation would have been too high for a meaningful determination. The phytoplankton growth rates measured in our incubations were consistent with previous growth rate estimates using the chl a-specific growth rate approach (Redalje and Laws, 1981; Goericke and Welschmeyer, 1993). Furthermore, growth rates of phytoplankton community assemblages from Galveston Bay and the Neuse River Estuary, exposed to bioassay manipulations were similar in spring, but the estimated growth rate in summer was high in Galveston Bay compared to the estimated summer value of 0.28 d-1 for the Neuse River Estuary (Pinckney et al., 1999). Possibly, the differences in phytoplankton growth rate responses in the two estuaries in summer are related to differences in the phytoplankton community composition in the two estuaries. Diatoms dominated the community assemblage upon termination of the experiment in Galveston Bay whereas diatoms were a minor component of the community assemblage in the Neuse River Estuary in July (Pinckney et al., 2001). Many diatoms, particularly the smaller species, have been characterized as “opportunistic” species capable of rapid growth rate compared to other algal groups (Kilham and Kilham, 1980; Banse, 1982; MacIntyre et al., 2002). The abundant diatom population in Galveston Bay possibly accounted for a significant part of the phytoplankton growth rate response of the phytoplankton community.

Light and growth rate response Phytoplankton respond to changes in light regimes by increasing/decreasing the chl a content per cell in accordance to the previous light history of the cell, thus phytoplankton acclimate to the average exposure irradiance (Post et al., 1984; Falkowski and Raven, 1997). This creates a potential for over- or 13

underestimation of phytoplankton growth rates across treatments of variable surface irradiance. Potentially, an inherent light response (unbalanced growth) is imbedded in the growth rate estimates at the three light intensities tested. However, the rate of the photoacclimation response has been estimated to be on the order of days (MacIntyre et al., 2000) and should not have affected the experimental results presented. Light induced differences in phytoplankton growth rate were not detected in any of the experiments, thus no apparent effect of unbalanced growth on phytoplankton growth rate estimates were detected. The lack of apparent differences in phytoplankton growth rate among incubations at 41, 30 and 12% of surface light intensity indicates that, at the time of the experiments, phytoplankton in Galveston Bay was exposed to light regimes that spanned the experimental conditions. Light penetration was measured at the same time as the water was collected for the experiments. Based on the light extinction coefficient, the depth at which 10% of the surface irradiance penetrated was 0.7m in March and 0.3 m in July at station 4 but 1.6 m in May at station 5. Phytoplankton was thus collected from the relatively well-lit part of the water-column but due to lack of stratification of the water, the cells were presumably mixed below the 10% surface intensity, which would explain why phytoplankton growth rate was not significantly different among light treatments. However, it is possible that 12% surface intensity was to high irradiance to induce phytoplankton growth-rate reduction of estuarine phytoplankton.

Phytoplankton growth and biomass accumulation Phytoplankton growth rate estimates of 0.8 - 1.3 d-1 in N+P treatments, and 0.4 - 0.6 in nutrient limited control treatments, predict a biomass increase of 2.2 to 3.7 times that of the initial biomass (chl a) in nutrient replete experiments and 1.5 - 1.8 times increase of the biomass in nutrient deplete conditions. Comparison of the predicted biomass (based on growth rates) to the measured phytoplankton biomass at the termination of the experiment revealed that the observed phytoplankton standing stock in March was 52 - 71% and 52 - 68% of the predicted biomass estimate in the control and N+P treatments, respectively. The phytoplankton biomass at termination of the experiment in May was closer to the growth rate estimate of the biomass, or 69 - 96% of the control treatments compared to 56 - 140% in N+P treatments. In July, the difference between expected and measured biomass increased again and only 25 - 45% (control) and 31 - 67% (N+P treatments) of the expected biomass was detected at the termination of the experiment. The lack of biomass accumulation, when compared to the estimated growth rate suggest that phytoplankton growth and grazing was slightly uncoupled in July and March, if assumed that zooplankton grazing was the main factor reducing phytoplankton biomass in the incubations. Similar growth rates of phytoplankton and grazing rates by zooplankton were observed for 14

the planktonic community of Galveston Bay in dilution bioassays conducted in April and December 2000 (Lumsden, 2002). These results are consistent with the hypothesis that zooplankton grazing reduced biomass accumulation in the growth rate experiment conducted in July and to lesser extent in March.

Phytoplankton growth and community composition Phytoplankton community composition was significantly different between control and N+P treatments, indicating that nutrient replete (N+P incubations) and nutrient -deplete environment (control incubations) facilitated growth of different phytoplankton groups. In general, diatoms increased in relative abundance (chl a) in N+P incubations whereas cyanobacteria, cryptophytes, chlorophytes and others remained constant or decreased in relative abundance. At times of nutrient replete conditions, diatoms showed no significant changes in relative contribution to phytoplankton community composition. The diatom-dominated growth response was consistent across variable phytoplankton standing stocks (5 - 21 µ g chl a l-1 ) and distinctively different community structure, characterized by diatoms in spring but cyanobacteria in summer. The phytoplankton community succession, from diatoms to cyanobacteria, and N+P facilitation of diatom growth is consistent with the relative affinity of diatoms and cyanobacteria for nitrate uptake and growth. Cyanobacteria are usually favored in an environment of low nitrogen availability but diatoms usually dominate in nutrient replete conditions (Tilman et al., 1986). Furthermore, the lack of biomass accumulation in July and the shift in community composition from cyanobacteria dominance to diatom dominance in the N+P additions suggests that the zooplankton community was able to rapidly utilize the newly grown diatoms. Thus, the nutrient addition induced the growth of r-selected species (diatoms in this case) that are susceptible to zooplankton grazing (Sommer et al., 1986; Kilham and Kilham, 1980). Cyanobacteria, on the other hand, are characteristic of high nutrient affinity and low grazing pressure (K-selected species). Cyanobacterial dominance in the initial sample followed by a shift to diatom dominance demonstrates that nutrient availability and grazing pressure may structure phytoplankton biomass composition in Galveston Bay. The apparently high grazing pressure in July suggests that the zooplankton community was able to reduce biomass accumulation of the edible algae, leaving cyanobacteria as the dominating group.

Phytoplankton dynamics in Galveston Bay The phytoplankton community in Galveston Bay has the potential to instantaneously respond to nutrient pulses, facilitating diatom biomass accumulation in spring and summer. Spatio-temporal 15

phytoplankton community composition in the estuary was often dominated by diatoms, but a shift to cyanobacteria dominance was observed in summer, particularly in Trinity Bay (Örnólfsdóttir, 2002). Commonly, small rapidly growing phytoplankton (often diatoms) are replaced by slow growing, filamentous or small inedible cell forms during nutrient deplete conditions or in spatially heterogeneous environment (Sommer, 1989). The reversal to the spring conditions and increased diatom abundance in N+P treatments in summer implies that brief nutrient pulses may maintain the longevity of diatom presence in the estuary. Furthermore, wind induced mixing may have facilitated the relatively stable and diverse phytoplankton community by randomly distributing the phytoplankton species in the water column (Margalef, 1978), by increasing the nutrient flux out of the sediment, and by maintaining the phytoplankton in the photic zone. The nanophytoplankton dominance in the estuary is therefore possibly maintained through frequent wind induced sediment resuspension and associated nutrient pulses that favor small, rapidly growing phytoplankton species. Diatoms, the dominant group of nanophytoplankton biomass, are non-motile and most species are prone to sinking out of the water column (Smetacek, 1999). Diatom abundance in Galveston Bay is possibly maintained through frequent wind mixing of the water column. The broad surface area of the estuary, coupled with a shallow water column, facilitates rapid and complete mixing. Nanophytoplankton dominance has been observed in the nearby estuary, Corpus Christi Bay (Pennock et al., 1999), thus phytoplankton communities in other Gulf of Mexico estuaries may be structured by similar mechanisms. The decrease in biomass during summer coincided with the highest observed differences between estimated (based on growth rates) and observed biomass accumulation, thus the phytoplankton standing stock in the estuary was potentially mediated by zooplankton grazing during summer months. The close coupling of growth and grazing rates and the seasonality in nutrient rich freshwater inflow provides a mechanism that could explain infrequent bloom events observed in the estuary (Buskey and Smith, 1992). The coupled nature of primary production and higher trophic levels has been observed in other regional (Gulf of Mexico) estuaries, emphasizing the role of freshwater flow on estuarine productivity (Chanton and Lewis, 2002). Wind mixing and pulsed nutrient inputs from the sediment in Galveston Bay may be a critical structuring feature but further research is needed to define the interactions and rates. Our results suggest that the phytoplankton community in Galveston Bay instantaneously responds to nutrient pulses by increasing growth rates and the manifestation of this increased growth (i.e., phytoplankton biomass accumulation) possibly depends on grazers. Spring rains result in nitrogen input events that stimulate diatom blooms within the bay. During periods of reduced riverine nutrient loading, especially during the dry summer months, small and/or flagellated species (e.g., cyanobacteria, 16

cryptophytes, dinoflagellates) are the most abundant algal groups. Biomass accumulation in the bay is tightly coupled with grazer responses, with grazers consuming as much as 75% of the daily phytoplankton production. Thus Galveston Bay phytoplankton biomass and community composition reflect a dynamic balance between the frequency of nutrient pulsing and loss terms, i.e. grazing intensity.

ACKNOWLEDGM ENTS We would like to thank Dr. Dave Millie and Dr. Gary Kirkpartrick for providing us with the facilities for the

14

C analysis of the data and for hosting us at the Mote Marine Laboratory in Sarasota, Florida.

We are most grateful to Mr. Larry Boihem for good advice and assistance in the lab and to Alyce Lee for helping out conducting the experiments. Dr. Tammi Richardson provided valuable comments on the manuscript at an early stage. This project was supported by funding from the Texas Institute of Oceanography to EBÖ and by funding to JLP from Texas Parks and Wildlife Department. The Institute of Biology at the University of Iceland provided EBÖ with research facility during the final preparation of this paper in November 2003. CHEMTAX Software is a project of CSIRO Division of Oceanography (Hobart, Australia) and available from D.J. Mackey ([email protected]).

17

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Table titels

Table I. Initial phytoplankton biomass (chl a), nutrient concentrations and physical parameters at initiation of bioassay incubations. Biomass values are for the total phytoplankton assemblage (Total) and the nanophytoplankton community (Nano). The nitrogen concentrations are presented as the cumulative DIN sources (DIN).

Table II. Phytoplankton community changes between control and nutrient addition (N+P) treatments for total phytoplankton community (Total) and nanophytoplankton (Nano) in March, May and July 2001. Statistical analysis performed using ANOVA, N=18, p