Estimates of oceanic mesozooplankton production: a comparison using the Bermuda and Hawaii...

Deep-Sea Research II 49 (2002) 175–192

Estimates of oceanic mesozooplankton production:a comparison using the Bermuda and

Hawaii time-series data

M.R. Romana,*, H.A. Adolf a, M.R. Landryb, L.P. Madinc,D.K. Steinbergd, X. Zhanga

aHorn Point Laboratory, University of Maryland Center for Environmental Science,

P.O. Box 775, Cambridge, MD 21613, USAbDepartment of Oceanography, University of Hawaii at Manoa, 1000 Pope Rd, Honolulu, HI 96822, USA

cWoods Hole Oceanographic Institution, Woods Hole, MA 02543, USAdVirginia Institute of Marine Science, P.O. Box 1346, Gloucester Point, VA 23062, USA

Accepted 12 June 2001

Abstract

Mesozooplankton growth rates were estimated for the Hawaiian (HOT) and Bermuda (BATS) oceantime-series stations using the empirical model of Hirst and Lampitt (Marine Biology 132 (1998) 247), whichpredicts copepod growth rate from temperature and body size. Using this approach we derived seasonaland annual estimates of mesozooplankton production as well as rates of mesozooplankton ingestionand egestion using assumed growth and assimilation efficiencies for the period 1994–1997. Annualmesozooplankton production estimates at HOT (average 0.79molCm�2 yr�1) were higher than productionestimates at BATS (average 0.33molCm�2 yr�1) due to both higher mesozooplankton biomass and higherestimated mesozooplankton individual growth rates. Annual primary production at the two sites wassimilar (average 14.92molCm�2 yr�1 at HOT and 13.43molCm�2 yr�1 at BATS). Thus, mesozooplank-ton production was a greater fraction of primary production at HOT (0.05) as compared to BATS (0.02).Mesozooplankton potentially contributed more to the gravitational flux of carbon at HOT, where the ratioof the average annual estimate of mesozooplankton fecal pellet carbon production/annual estimate ofcarbon flux at the base of the euphotic zone was 1.03 compared to the same ratio of 0.39 at BATS.Mortality estimates were similar to estimates of mesozooplankton production when compared over theentire study period. The higher mesozooplankton biomass and derived rate parameters at HOT comparedto BATS may be due to the more episodic nature of nutrient inputs at BATS, which could result in mis-matches between increases in phytoplankton production and the grazing/production response bymesozooplankton. In addition, there is evidence to suggest that there are periodic blooms of gelatinous

*Corresponding author. Fax: +1-410-476-5490.

E-mail address: [email protected] (M.R. Roman).

0967-0645/01/$ - see front matter r 2001 Elsevier Science Ltd. All rights reserved.

PII: S 0 9 6 7 - 0 6 4 5 ( 0 1 ) 0 0 0 9 9 - 6

macrozooplankton (salps) at BATS that may not be captured sufficiently by the monthly samplingprogram. Thus the gelatinous zooplankton would add to the overall grazing impact on the phytoplanktonat BATS as well as the contribution of zooplankton to the gravitational flux of biogenic material via fecalpellet production. r 2001 Elsevier Science Ltd. All rights reserved.

1. Introduction

In situ copepod growth estimates have been made in restricted water bodies such as lakes,mesocosms, lagoons and bays where emigration and immigration are zero or minimal. In situgrowth measurements in open waters have been conducted while following drogues (i.e. Cushingand Tungate, 1963), but the measurements are extremely time-consuming and it is difficult/impossible to follow the same population/water mass over enough time to measure copepodgrowth rates. Shipboard incubation techniques have been used for growth estimates for individualcopepod species based on molting frequency (e.g., Miller et al., 1984) and egg production (e.g.,Ki�rboe and Johansen, 1986; Berggreen et al., 1988), but these techniques are subject to a varietyof containment effects and are of limited value for overall copepod community growth estimatesin tropical and sub-tropical seas where the species diversity of copepods is great (e.g., Grice andHart, 1962; Timonin, 1971). In addition, in some circumstances weight-specific reproductivegrowth (i.e. egg production) is not the same as weight-specific somatic (increase in body mass)growth (McKinnon, 1996; Hopcroft and Roff, 1998), so that the egg production method may notaccurately represent the growth of the whole copepod population.Another approach to estimating copepod metabolism is based on regression models that use

temperature (e.g. Huntley and Lopez, 1992) or temperature and body size (e.g. McLaren, 1965;Ikeda and Motoda, 1975; Hirst and Sheader, 1997; Hirst and Lampitt, 1998) to predict copepodgrowth rates. These empirical models are based on laboratory, and in some cases, fieldmeasurements of copepod growth rates (somatic growth) over a range of temperatures,food conditions, copepod body sizes and copepod species. The predictive equations assume thatall species (sizes of copepods) grow at the same rate at a particular temperature. In some cases weknow that this is not true. For example, cyclopoid copepods may grow slower than the same sizecalanoid copepods (Lampitt and Gamble, 1982; Ki�rboe and Sabatini, 1995; Hopcroft et al.,1998). This regression approach also has been criticized (Kleppel et al., 1996; Calbet and Agusti,1999) because it assumes that growth rate is not food limited. The egg production rates ofcopepods have been shown to be food-limited in a variety of marine waters (e.g. Checkley, 1980;Durbin et al., 1983; Saiz and Ki�rboe, 1995). It is interesting to note, however, that spatial andtemporal estimates of copepod biomass can vary by several orders of magnitude whereaspublished copepod growth rates at similar temperature varies by 2–4 times (e.g. Huntley andLopez, 1992; Hopcroft et al., 1998). Thus for estimates of copepod production (growthrate� biomass) the errors associated with estimates of growth rate are probably less compared tothose of biomass.We have used an empirical regression model (Hirst and Lampitt, 1998) to estimate

mesozooplankton production and assumed rates of ingestion and egestion at the Hawaiian andBermuda ocean time-series stations, both part of the US Joint Global Ocean Flux Study (US

M.R. Roman et al. / Deep-Sea Research II 49 (2002) 175–192176

JGOFS) program. At these study sites, seasonal measurements of mesozooplankton size fractionsand species composition can be used for size-based copepod growth models. JGOFS coremeasurements allow these mesozooplankton rate estimates to be compared to rates of primaryproduction and export flux to deduce the role of mesozooplankton in the cycling of biogenicmaterial. Repeated mesozooplankton biomass measurements over the year can provide thenecessary data for crude estimates of annual mesozooplankton production, which can becompared to annual estimates of primary production and the gravitational flux of material fromthe euphotic zone.

2. Methods

2.1. Mesozooplankton sampling

Mesozooplankton samples were collected at the Hawaiian ocean time-series (HOT; 221450N,1581000W; Karl and Lukas, 1996) and Bermuda Atlantic time-series (BATS; 311500N, 641100W;Michaels and Knap, 1996) stations. The details of mesozooplankton sampling and processinghave been described for both HOT (Landry et al., 2001) and BATS (Madin et al., 2001). Briefly,oblique tows were taken with a 1m-diameter (BATS) or 1-m2 (HOT), 200-mm mesh net equippedwith a General Oceanics flowmeter and time/depth recorder. Tows were conducted in the surface200m. This depth included both the euphotic zone and the depth of free-drifting sediment traps.Both day and night tows were taken at each station. Unless noted, we used the average of the dayand night tows in our analyses. Shipboard, the mesozooplankton catch was split for preservationand biomass measurements. The biomass sample was wet sieved through nested Nitex screens of5, 2, 1, 0.5 and 0.2mm mesh. Aliquots of these size fractions (0.2–0.5, 0.5–1, 1–2, 2–5 and >5mm)were analyzed for dry weight, carbon and nitrogen biomass.

2.2. Rate estimates

Copepod growth rates were estimated using the model of Hirst and Lampitt (1998), whichpredicts copepod growth rate from temperature and body size. This multi-regression model is anupdate of the original growth equation of Hirst and Sheader (1997). The Hirst and Lampitt (1998)model for broadcast and sac-spawning copepods (adults+juveniles) combined published dataðn ¼ 952Þ on copepod growth rates, body weights (0.075–3620mgC), and habitat temperature(�2.31C to 29.01C) in a multivariate regression equation that relates intrinsic growth rate ðg ¼d�1Þ to temperature ðT ¼ 1CÞ and copepod body weight (BW=mgC individual�1), log10g ¼0:0208½T �20:3221½log10BW�21:1408 ðr2 ¼ 0:435Þ: When Hirst and Lampitt compared themeasured values of growth to the growth estimates predicted by the equation, approximately95% of the predicted values were between 5 times and 0.2 times the measured values. Note thatthe 952 published growth rates used to generate the Hirst and Lampitt (1998) equation covered arange of food conditions. Thus, the predicted growth rates may be less than a maximum intrinsicgrowth rate if the growth rates included in the regression analysis were food-limited. Conversely,if the in situ growth rates are severely food limited, the Hirst and Lampitt (1998) predicted growthrates may represent an overestimate of the actual in situ rate. We have previously (Roman et al.,

M.R. Roman et al. / Deep-Sea Research II 49 (2002) 175–192 177

2000) compared three different empirical models (Huntley and Boyd, 1984; Huntley and Lopez,1992; Hirst and Sheader, 1997) to estimate mesozooplankton growth rates in the Arabian Sea.The Hirst and Sheader (1997) model provided the most reasonable estimates of growth rate fordifferent mesozooplankton size-fractions when compared to published growth rates for similar-sized copepods at the ambient temperatures. We also compared direct measurements of growthrates of the copepod Acartia tonsa to indirect growth estimates using the Hirst and Sheader (1997)equation, and found that the two estimates of growth differed by o10% over two, 10-dayexperiments (Zimmer and Roman, unpublished).Habitat temperature is used to estimate copepod growth. Temperature data were obtained

by taking the average of all CTD casts from a particular station listed in the US JGOFSdatabase (http://usjgofs. whoi.edu). We assumed that most of the mesozooplankton collected inthe oblique tows at HOT and BATS were caught in the surface 100m. Stratified MOCNESStows at the BATS station (Roman et al., 1993) and in the Pacific at 121N, 1401W (White et al.,1995) confirmed this. Thus we averaged the temperature values at 1-m intervals in thesurface 100m to estimate the habitat temperature of mesozooplankton caught in the obliquetows.We assumed that copepods comprised all of the measured mesozooplankton biomass. Based on

previous studies of the mesozooplankton community at BATS (Deevey, 1971; Roman et al., 1993)and HOT (Landry et al., 2001), it appears that copepods usually comprised >80% of themesozooplankton. We used estimated body weights for copepods in the various size-fractions thatwere determined in the HOT study (Landry et al., 2001) for both the HOT and BATS time-seriesstations. These estimates were derived by dividing the average biomass (n ¼ 99 daytime, 101nighttime) by the average abundance measurements (71 daytime, 73 nighttime) counted in thevarious size-fractions. The calculated individual copepod weights were: 0.2–0.5mm=2.4 mgC;0.5–1mm=6.4 mgC; 1–2mm=37.6mgC; 2–5mm=117.4mgC; >5mm=1905mgC. If we assumethat the size of copepods caught on sieves was determined by the geometric mean of the mesh sizeinterval and calculated weights using the published copepod length–weight regression byRodriguez and Mullin (1986) or Uye (1982), we would calculate approximately the sameindividual weights as using the Landry et al. (2001) data. Thus it is reasonable to assume the sameindividual weights in the various copepod size fractions at HOT and BATS. The actual meanweight of the copepods caught in each size fraction likely varied with site and season, but weexpect that this variation is less than the order-of-magnitude variation in the total weight biomassof the various copepod size fractions.There were variable time intervals between sampling at both the HOT and BATS stations;

therefore, we derived average estimates of mesozooplankton rate processes for the periods withintime intervals rather than on the individual sampling dates. We calculated mortality rate for theperiods within time intervals by using the mean size-specific growth rates (g) of the initial and finalsample date and the initial and final biomass based on the equation

Bt ¼ B0eðg�mÞt;

where B0 and Bt are the initial and final biomass estimates of a sampling interval, g is the meangrowth rate, m is mortality rate, and, t is the time (days) between sampling intervals.Mesozooplankton production (P=mmolCm�2 d�1) is the product of the estimated growth rate(g) and the biomass (B). We determined mean mesozooplankton production and mortality for the


time between the sampling periods by using the mean growth rate (g) or the calculated mortalityrate (m), respectively, and the mean time-integrated biomass in each size group. This ‘‘average’’biomass /BS was calculated according to Frost (1972), where

/BS ¼B0½eðg�mÞt � 1�

tðg�mÞ:

Thus the mean production=g/BS and the mortality=m/BS:Once material is ingested (I) by copepods, it is partitioned into production (P), respiration (R),

and egestion (E=fecal pellet production); thus P ¼ I � R� E: We estimated mesozooplanktoningestion (mmolCm�2 d�1) by assuming a gross production efficiency ðP=IÞ of 30%. It has beensuggested that copepod production efficiency (here used in the same way as gross growthefficiency) can vary with food quality and temperature, ranging from approximately 14% to 50%with a mean of approximately 30% (Omori and Ikeda, 1984). A similar mean gross productionefficiency was determined by Straile (1997) for both protozoa and crustacean zooplankton.Copepod fecal pellet production (E) was estimated by assuming that 70% of the ingested material(I) was partitioned to growth and respiration and that 30% was egested as fecal pellets(E=I ¼ 0:3; n ¼ 104; SD ¼ 0:07; Conover, 1978). Note that since we assume the ratios of bothP=I and E=I ¼ 0:3; our calculations of mesozooplankton production are the same asmesozooplankton egestion (fecal pellet production). This coincidence is due to our numericalchoices for the production and egestion efficiencies. The actual efficiencies of copepod productionand egestion likely varied over the stations and seasons at HOT and BATS. However, theseefficiencies have been shown to vary 20–50% over a range of temperatures, food qualities andcopepod sizes, whereas mesozooplankton biomass during our study varied by more than an orderof magnitude.Estimates of primary production and the gravitational flux of particulate material for the HOT

and BATS sites were obtained from the US JGOFS database (http://usjgofs.whoi.edu).

3. Results

3.1. Mesozooplankton biomass

The seasonal cycles of mesozooplankton biomass at HOT (Landry et al., 2001) andBATS (Madin et al., 2001) have been described previously. In general, there was over twiceas much mesozooplankton at HOT compared to BATS (Fig. 1; Table 1), with the averagebeing 23.84mmolCm�2 at HOT and 11.38mmolCm�2 at BATS for samples collectedbetween 1994 and 1997. There were significant ðPo0:05Þ seasonal differences in mesozooplanktonbiomass at HOT, with the highest mean values found in the fall and the lowest mean valuesfound in the spring (Duncan’s multiple range test). There were no significant differencesbetween seasonal groupings for mesozooplankton biomass at BATS for the 1994–1997 period,although in general, the highest values of mesozooplankton biomass are found in spring (Madinet al., 2001).At the two time-series stations, roughly 18–28% of the total mesozooplankton biomass was

distributed in each of the 0.2–0.5mm; 0.5–1mm; 1–2mm and 2–5mm size fractions but lower


Fig. 1. Mesozooplankton biomass (mmolCm�2) in the surface 150m at BATS and HOT for 1994–1997.

Table 1

Hawaii ocean time series and Bermuda Atlantic time series 1994–1997a

MeanHOT SDHOT NHOT MeanBATS SDBATS NBATS

0.2–0.5mm zooplankton mmolCm�2 (% total) 4.33 (18.16) 1.42 36 2.46 (21.62) 0.98 470.5–1mm zooplankton mmolCm�2 (% total) 5.66 (23.74) 2.49 36 3.01 (26.45) 1.24 471–2mm zooplankton mmolCm�2 (% total) 6.69 (28.06) 3.26 36 2.54 (22.32) 1.09 47

2–5mm zooplankton mmolCm�2 (% total) 5.64 (23.66) 2.80 36 2.46 (21.64) 1.26 47>5mm zooplankton mmolCm�2 (% total) 1.52 (6.38) 1.17 36 0.91 (8.00) 0.62 47Total zooplankton mmolCm�2 23.84 8.85 36 11.38 4.61 47

Zoopl production and egestion mmolCm�2 d�1 2.25 0.73 35 0.95 0.30 46Zooplankton ingestion mmolCm�2 d�1 7.49 2.42 35 3.17 1.00 46Zooplankton mortality mmolCm�2 d�1 2.20 0.80 35 0.93 0.34 46

Temperature (C1) 24.32 1.05 36 21.50 1.53 47Sinking flux mmolCm�2 d�1 2.14 0.49 31 2.26 0.74 43Primary production mmolCm�2 d�1 41.08 9.84 34 35.31 8.05 46

aValues integrated from surface to 150m.


amounts of biomass (average 6% for HOT and 8% for BATS) in the >5mm size fraction. Thecontribution of the 0.2–0.5mm and 0.5–1.0mm fractions to total mesozooplankton biomass wasgreater at BATS as compared to HOT (Po0:05; paired t-test). In contrast, there was a greaterfraction of total mesozooplankton biomass in the 1–2mm fraction at HOT (Po0:05; pairedt-test). There was no significant difference in the proportion of mesozooplankton biomassallocated in the 2–5mm and >5mm at HOT and BATS (P > 0:05; paired t-test).

3.2. Mesozooplankton growth rate

Estimates of mesozooplankton growth rate are a direct function of water temperature and aninverse function of body size of copepods (Hirst and Lampitt, 1998). Thus the highest averagegrowth rates were for the 0.2–0.5mm mesozooplankton fraction, 0.17 d�1 (HOT) and 0.15 d�1

(BATS) and the lowest growth rates were estimated for >5mm mesozooplankton 0.02 d�1 (HOTand BATS; Table 2). The weighted average (by distribution of the size fractions) mesozoo-plankton growth rate was 0.09 d�1 at HOT and 0.08 d�1 at BATS. The higher estimated growthrates at HOT were due to higher water temperatures. The mean and SD of the 1m-averagedsurface 100m temperatures at HOT and BATS was 24.321C (1.051C) and 21.501C (1.531C),respectively. A greater variation in temperature over the year at BATS as compared to HOTresulted in greater seasonal variations in the estimated copepod growth rates.

3.3. Mesozooplankton production and egestion

The greater estimates of mesozooplankton production and egestion at HOT(mean=2.25mmolCm�2 d�1) compared to BATS (mean=0.95mmolCm�2 d�1) were the resultof higher biomass and slightly higher growth rates (Fig. 2; Table 1). Seasonal and annualvariations in production and egestion were similar, but not identical, to variations inmesozooplankton biomass, with the differences due to changing water temperatures and thesize composition of the mesozooplankton community.Primary production was similar at the two time-series stations (Table 1). Thus the ratio of

estimated daily mesozooplankton production/daily phytoplankton production was higher atHOT (0.06; Fig. 3) compared to BATS (0.03; Fig. 3). The integrated annual mesozooplanktonproduction estimates ranged from 0.20molCm�2 yr�1 at BATS in 1994 to 0.92molCm�2 yr�1 atHOT in 1996 (Table 3).

Table 2HOT and BATS zooplankton growth rates (d�1)

Zoopl size MeanHOT SDHOT NHOT MeanBATS SDBATS NBATS

0.2–0.5mm 0.17 0.01 36 0.15 0.01 470.5–1mm 0.12 0.01 36 0.11 0.01 47

1–2mm 0.07 0.00 36 0.06 0.00 472–5mm 0.05 0.00 36 0.04 0.00 47>5mm 0.02 0.00 36 0.02 0.00 47


Mesozooplankton egestion (fecal pellet production) estimates, as mentioned previously, are thesame values as the production estimates (Table 1; Fig. 2). Estimates of sinking carbon flux fromsediment traps at HOT and BATS were similar (Table 1); thus, the potential contribution ofmesozooplankton egestion to the sinking flux was greater at HOT compared to BATS (Table 1;Fig. 3). The ratio of mesozooplankton egestion/sinking carbon flux estimated at the base of theeuphotic zone (150m) ranged from 0.20 at BATS in 1994 to 1.20 at HOT in 1996 (Fig. 3). Theaverage integrated annual ratios of egestion/sinking flux were 0.39 at BATS and 1.03 at HOT(Table 3). Note that to date, there have not been analyses of the sediment trap material from HOTor BATS, so we cannot directly assess the contribution of fecal pellets to the sinking carbon flux.

3.4. Mesozooplankton mortality

Mesozooplankton mortality (mmolCm�2 d�1) was similar in magnitude to our estimates ofmesozooplankton production (Figs. 2 and 4), indicating that most of the mesozooplanktonbiomass produced was removed by predators and advection. There often was a time lag in thepeaks of mesozooplankton production and mortality (Figs. 2 and 4). Mesozooplankton biomass

Fig. 2. Mesozooplankton production and egestion (mmolCm�2 d�1) in the surface 150m at BATS and HOT for 1994–

1997.


(Fig. 1) tended to increase during particular time intervals (production>mortality) and decreasein other periods (mortality>production). However, when compared over all 4 years of sampling,it is apparent that mesozooplankton production and mortality were approximately in balance atboth HOT and BATS (Fig. 5).

3.5. Mesozooplankton ingestion

Mesozooplankton ingestion rates, calculated using the production estimates and anassumed 30% gross growth efficiency, represent total carbon consumed, which would

Fig. 3. Production ratio (mesozooplankton production/primary production); egestion ratio (mesozooplanktonegestion/sinking flux); and grazing ratio (mesozooplankton ingestion/primary production) for the surface 150m atHOT and BATS for 1994–1997. Means are shown with bars indicating standard deviation.


Table 3Integrated annual values (molCm�2 yr�1)

Primary production Zoopl prod and egestion Zoopl./prim prod ratio Sinking flux Eges/sinking ratio

BATS1994 13.00 0.20 0.02 1.03 0.201995 14.01 0.34 0.02 0.73 0.461996 14.92 0.37 0.02 0.91 0.41

1997 11.79 0.42 0.04 0.85 0.49MeanSD 13.431.17 0.330.08 0.020.01 0.880.11 0.390.11

HOT1994 13.66 0.62 0.05 0.68 0.911995 18.61 0.70 0.04 0.67 1.05

1996 14.14 0.92 0.07 0.77 1.201997 13.25 0.90 0.07 0.92 0.98MeanSD 14.922.16 0.790.13 0.050.01 0.760.10 1.030.11

Fig. 4. Mesozooplankton mortality (mmolCm�2 d�1) in the surface 150m at BATS and HOT for 1994–1997.


include a combination of phytoplankton, small copepods, protozoa and detritus. The averageestimated ingestion was 7.49mmolCm�2 d�1 (SD=2.42mmolCm�2 d�1) at HOT and3.17mmolCm�2 d�1 (SD=1.00mmolCm�2 d�1) at BATS (Table 1; Fig. 6). Although theestimates of mesozooplankton ingestion at HOT were approximately twice the ingestion estimatesat BATS, primary production at both sites was similar. Thus the ratio of mesozooplankton

Fig. 5. Relationship between mesozooplankton production ðyÞ and mortality ðxÞ for 1994–1997 at BATS(y ¼ 0:75xþ 0:26; r ¼ 0:86) and HOT (y ¼ 0:81xþ 0:47; r ¼ 0:89).


carbon ingestion/primary production (grazing ratio) was higher at HOT (mean=0.18; Fig. 3)compared to BATS (mean=0.09; Fig. 3). Laboratory copepod ingestion rates are often expressedas a weight-specific rate (C-ingested/C-biomass/day). The average weight-specific ingestionestimates derived for mesozooplankton at HOT (0.31mmolCmmolC�1 d�1) and BATS(0.28mmolCmmolC�1 d�1) are reasonable estimates compared to published values for directingestion estimates for copepods (Mauchline, 1998), given the distribution of mesozooplanktonsize classes and the warm (>201C) temperatures (Table 1).

4. Discussion

Our estimates of mesozooplankton growth, production, mortality, egestion and ingestion willbe overestimates if the actual in situ mesozooplankton growth rates were food-limited. The 935published growth rates used to generate the Hirst and Lampitt (1998) equation covered a range offood conditions, some of which were food-limited growth. The average estimated mesozoo-plankton growth rates, weighted by the distribution of biomass size fractions, were 0.09 and0.08 d�1 at HOT and BATS, respectively. These growth estimates are in, or below, the range ofvalues published for copepod growth rates at similar temperatures (summarized in Mauchline,1998). As pointed out by Huntley and Lopez (1992), higher concentrations of phytoplankton may

Fig. 6. Mesozooplankton ingestion (mmolCm�2 d�1) in the surface 150m at BATS and HOT for 1994–1997.


exist at fine-scale vertical intervals in oceanic waters that are not sampled by traditional samplingtechniques (Cowles et al., 1993). In addition, most copepods are omnivores, eating protozoa(Kleppel, 1992; Dam et al., 1995a, b) and detritus (Roman, 1984); thus chlorophyll-a is a measureof only a portion of the food available for copepods. In waters off Jamaica, which exhibited arange in temperature and chlorophyll values similar to HOT and BATS, Hopcroft and Roff(1998) found no correlation between naupliar growth rates and chlorophyll concentration, butthat chlorophyll enhancement could result in up to a 32% increase in copepodite growth rates.However, the inclusion of chlorophyll did not significantly improve the regression betweencopepod body size and growth rate in the Jamaican waters.Direct measurements of weight-specific respiration for large migratory zooplankton collected at

BATS and incubated in surface seawater averaged 0.10mgC mgC�1 d�1 (Steinberg et al., 2000).Generally, the amount of carbon that copepods allocate to growth, respiration and egestion isapproximately similar (Mauchline, 1998), thus this value would be roughly the same as a weight-specific growth rate of 0.10mgC mgC�1 d�1 or instantaneous growth rate (g) of 0.07 d�1. Ourestimated growth rates for the copepod community at BATS (0.09 d�1) are consistent withSteinberg et al.’s (2000, 2001) respiration measurements.Direct mesozooplankton in situ ingestion estimates at the BATS site (assuming that the diets

were 50 : 50, phytoplankton : protozoa) averaged 0.3mmolCm�2 d�1 (range 0.2–0.8mmolCm�2 d�1) in August and 9.4mmolCm�2 d�1 (range 2.4–29.6mmolCm�2 d�1) inMarch/April (Roman et al., 1993). Using the derived mesozooplankton production estimatesfrom the Hirst and Lampitt (1998) equation and an assumed gross growth efficiency, wecalculated a mean mesozooplankton ingestion rate at BATS of 3.2 (range 1.1–5.2mmolCm�2 d�1; Table 1, Fig. 6). The isotope method used to measure mesozooplanktoningestion has a number of potential errors associated with it, all of which tend to giveunderestimates of the actual ingestion rate (Roman and Gauzens, 1997). Mesozooplanktoningestion measurements at BATS during March, based on the gut fluorescence technique, gave anaverage of approximately 3.3mmolCm�2 d�1 (Dam et al., 1995a), which is within our range ofingestion estimates (Fig. 6). Thus our indirect ingestion rates calculated here, compare favorablywith direct ingestion measurements at the BATS time-series site.Given approximately the same estimated mesozooplankton growth rates at HOT and BATS

(Table 2), the higher estimates of mesozooplankton production, egestion and ingestion are theresult of greater mesozooplankton biomass at HOT compared to BATS. Although primaryproduction was approximately the same at the two time-series stations (average primaryproduction at HOT 16% higher than BATS), the average mesozooplankton biomass was overtwice as high at HOT compared to BATS. At the onset of this study, we hypothesized that thecloser proximity to land and the passage of cold air masses at BATS (311500N, 641100W) ascompared to HOT (221450N, 1581000W) would result in more seasonal variation deep mixing,primary production and mesozooplankton biomass of BATS compared to HOT. However, thecoefficients of variation (SD/mean) of both primary production (0.35 BATS, 0.32 HOT) andmesozooplankton biomass (0.40 BATS, 0.37 HOT) were only slightly higher at BATS comparedto HOT over the 1994–1997 sampling period.Annual variations in both phytoplankton and mesozooplankton at BATS are influenced to a

large degree by the extent of deep mixing in winter, which can introduce nutrients into theeuphotic zone (Menzel and Ryther, 1960; Lohrenz et al., 1992). Thus, in years which there are


more cold air masses that pass near the Bermuda site, there is greater convective mixing and oftena greater winter/spring maxima in primary production and increased gravitational flux of biogenicmaterial (Deuser, 1986; Michaels et al., 1994). The North Atlantic oscillation (NAO) cycle maydetermine the magnitude and frequency of the cold-air mixing events that affect the BATS stationby shifting storm tracks southward, cooling surface waters, enhancing 181C-mode waterformation and deepening mixed layers (Bates, 2001; Steinberg et al., 2001). The period used in ouranalyses (1994–1997) did not have extreme mixing events (Madin et al., 2001; Steinberg et al.,2001) and was generally in the positive phase of the NAO (Bates et al., 2001).There may be episodic blooms of gelatinous herbivorous macrozooplankton at BATS that are

missed by the monthly sampling program. Salps are often abundant at BATS during March andApril (Deevey, 1971; Deevey and Brooks, 1971). Large blooms of salps, which can reducephytoplankton concentrations and can increase the gravitational flux of biogenic material, havebeen observed in the Northwest Atlantic Ocean (Wiebe et al.,1979) and at the BATS station(Steinberg et al., 2001).At the HOT station, there is evidence to suggest that primary production has increased over the

last decade as a result of the phase of the Pacific Oscillation (Karl et al., 1996). In a comparison ofHOT mesozooplankton data with previously collected data in the area, Landry et al. (2001)suggested that mesozooplankton also increased during the last decade. Thus our 1994through 1997 comparison of the two time-series sites may have been during a period of relativelylow mesozooplankton abundance at BATS and relatively high mesozooplankton abundanceat HOT.If the higher mesozooplankton biomass and derived mesozooplankton rates at HOT relative to

that of BATS is a permanent feature of the two areas, it is interesting to speculate on the causativemechanisms. There may be more of a mis-match between increases in phytoplankton productionand mesozooplankton production at BATS compared to HOT. This uncoupling might result in(1) more phytoplankton sinking directly at BATS compared to HOT, and (2) lower ratios ofmesozooplankton production/phytoplankton production and mesozooplankton egestion/sinkingflux (Fig. 3; Table 1) at BATS compared to HOT. Strong, deep convective mixing at BATS duringthe winter has been shown to vertically export significant amounts of dissolved organic carbon(Carlson et al., 1994). Usually this period of wintertime mixing coincides with yearly minima inmesozooplankton stocks (Menzel and Ryther, 1961; Deevey, 1971; Madin et al., 2001). Thereduced stock of mesozooplankton in winter may be the result of strong mixing of euphoticzone water with the 181C thermostad water. This severe dilution of euphotic zonemesozooplankton, like dissolved organic carbon, may add to the vertical export of carbon bythe deep mixing of surface mesozooplankton stocks. The winter mixing also may serve to de-couple phytoplankton and mesozooplankton. When stratification occurs and phytoplanktonproduction begins to increase, the mesozooplankton will lag the phytoplankton in their biomassincrease due to their larger size and slower growth rate. This de-coupling of phytoplankton andmesozooplankton production may not occur at the HOT station, and therefore themesozooplankton production/phytoplankton production ratio is higher than we found at theBATS station.At BATS the main nutrient input to the euphotic zone during the stratified period is from

eddies (McGillicuddy and Robinson, 1997; McGillicuddy et al., 1998). The input of nutrientsfrom eddies and deep mixing in support of annual primary production at BATS is approximately


equal (McGillicuddy and Robinson, 1997). Satellite altimetry combined with hydrographicobservations (Siegel et al., 1999) and model output (McGillicuddy and Robinson, 1997) suggeststhat the time scales of response to nutrient pulses increases in phytoplankton production, anddispersion may result in an uncoupling of phytoplankton and mesozooplankton. Similar to thewinter deep mixing events at BATS, the fate of phytoplankton increases due to transient eddy-induced nutrient inputs may be to sink rather than to be grazed. Support for this hypothesis canbe found in the conceptual model advocated by Goldman (1988) and time-series observations ofMalone et al. (1993). Pulsed nutrient inputs can result in transient blooms of large diatoms at thebase of the euphotic zone in the Sargasso Sea (Riley, 1957; Malone et al., 1993). High sinking ratesof the diatoms (Goldman, 1988) and relatively slow response times of increase by the zooplanktoncommunity (Steele and Frost, 1977) may result in direct sinking flux of eddy-inducedphytoplankton blooms at the BATS station (Malone et al., 1993).At HOT, permanent stratification and fewer episodic increases in primary production may

result in a higher efficiency of trophic transfer between phytoplankton and mesozooplankton.This is supported by our higher ratios of mesozooplankton grazing/primary production at HOTcompared to BATS. Another consequence of greater coupling between mesozooplankton andphytoplankton is a greater potential contribution of mesozooplankton egestion to the sinking fluxat HOT (average=1.05; Table 1) compared to BATS (average=0.42; Table 1).The observation that mesozooplankton biomass does not change appreciably over a 4-year

period at the two time-series sites underscores that the processes controlling mesozooplanktonproduction and loss are roughly in balance (Fig. 5). Given the warm temperatures (average mixedlayer temperature >221C) and relatively high mesozooplankton growth rates (0.09 d�1 for thewhole mesozooplankton community), the amount of mesozooplankton mortality (which includeslosses to advection, consumption by higher trophic levels, and gravitational flux) is roughly 1.02and 0.41 times the sediment trap flux at 150m at HOT and BATS, respectively (Table 1). The‘‘fate’’ of this mortality can include trophic transfer (with losses to respiration and egestion),emigration, sinking of carcasses, etc. We do not often think of mesozooplankton mortality as anexport flux from the water column. However, this added source of ‘‘export’’ can be important inbalancing food-web carbon models; in explaining the discrepancies between estimates of newproduction and export flux; and in linking studies of new and total primary production tofisheries. Mesozooplankton mortality may be especially significant in overall water column carboncycles in sub-tropical and tropical waters where there is usually low export production. The ratherconstant mesozooplankton biomass and high metabolic demands suggests a high carbon turnoverin the form of mesozooplankton mortality.

Acknowledgements

This research was support by Grant OCE-9725976 from the National Science Foundation aspart of the US JGOFS Synthesis and Modeling study. We are grateful to the scientists involved inthe HOT and BATS time-series programs for collecting and analyzing the data. Scott Doney andtwo anonymous reviewers made helpful comments on an earlier version of the manuscript. This isUniversity of Maryland Center for Environmental Sciences Contribution No. 3486; and USJGOFS Contribution No. 693.


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