Growth and distribution of marine bacteria in relation to nanoplankton community structure

Deep-Sea Research II 47 (2000) 461}487

Growth and distribution of marine bacteria in relation to nanoplankton community structure Connie Lovejoy!,*, Louis Legendre!, Jean-Claude Therriault", Jean-ED ric Tremblay!,1, Bert Klein!, R. Grant Ingram#,2 !De& partement de biologie, Universite& Laval, Que& bec, Que& bec, Canada G1K 7P4 "Maurice Lamontagne Institute, Department of Fisheries and Oceans, P.O. Box 1000, Mont-Joli, Que& bec, Canada G5H 3Z4 #Department of Atmospheric and Oceanic Sciences, McGill University 805, Sherbrooke Ouest, Montreal, Que& bec, Canada H3A 2K6 Received 2 May 1997; received in revised form 17 November 1997; accepted 23 July 1998

Abstract Bacterial productivity and biomass were investigated along with nanoplankton community structure and environmental variables at a number of sites in the Gulf of St. Lawrence (mid-April and mid to late-June) and at additional sites o! the coast of Nova Scotia (late June), eastern Canada. Total bacterial cell concentrations were determined in conjunction with actively respiring cells (ARCs) visualized using a redox #uorochrome (5-cyano-2,3-ditolyl tetrazolium chloride, CTC). Bacterial growth rates were estimated by 3H-thymidine uptake. There were strong seasonal di!erences in bacterial activity within the euphotic zone. The CTC assay indicated that the proportion of ARCs to total bacteria (BN) in the euphotic zone was lower in spring (1}4%) than summer (3}12%). In the aphotic zone bacterial growth (TdR-H3 uptake) was much lower than above and the proportion of ARCs was frequently (1% of total bacteria. Bacterial productivity and water temperature in the euphotic zone were positively correlated, while both ARCs and BN tended to be negatively correlated with inorganic nutrients. The proportion of ARCs was negatively correlated with the proportion of heterotrophic nano#agellates and positively correlated with that of mixotrophic species. The proportion of ARCs and the apparent potential growth rates of ARCs varied with changes in nanoplankton community structure. Mixotroph-dominated communities were associated with

* Corresponding author. E-mail address: [email protected] (C. Lovejoy) 1 Current address: Department of Biology, McGill University, 805, Sherbrooke Ouest, Montreal, QueH bec, Canada H3A 2K6. 2 Current address: Department of Earth & Ocean Sciences, University of British Columbia, 6270 University Blvd., Vancouver B.C., Canada V6T 174. 0967-0645/00/$ - see front matter ( 1999 Elsevier Science Ltd. All rights reserved. PII: S 0 9 6 7 - 0 6 4 5 ( 9 9 ) 0 0 1 1 5 - 0

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bacterial communities that had a relatively high proportion of ARCs but with low apparent potential growth rates. Conversely, communities dominated by a mixture of phototrophs and heterotrophs had a low proportion of ARCs with high apparent potential growth rates. These observations suggest that nanoplankton community structure plays a major role in controlling bacterial abundance and activity in the sea. ( 1999 Elsevier Science Ltd. All rights reserved.

1. Introduction The balance between phytoplankton and bacterial production largely determines the fate of biogenic carbon (BC) in the ocean (Geider, 1997). Once photosynthetically "xed, much of the BC remains as DOM in the euphotic zone where it is processed by bacteria (Azam et al., 1992; Azam et al., 1994). Rothhaupt (1996,1997) has shown that photosynthetic, mixotrophic, and heterotrophic #agellates interact, and that mixotrophs should dominate under low nutrient conditions (see also Nygaard and Tobiesen, 1993). Because of species di!erences in nutrient turnover characteristics within nanoplankton communities (Rothhaupt, 1997), bacteria may react to changing nanoplankton taxonomic composition. The taxonomic composition of the nano-sized phytoplankton}protozoa in many marine open waters is little known and often has only been reported in terms of #uorescence and #ow cytometric characteristics (Li, 1995; Buck et al., 1996). Available results indicate dominance by phyto#agellates and small coccoid cells, but taxonomic details are lacking. Another potentially important factor in the balance between phytoplankton and bacteria and to the fate of BC is the growth characteristics of bacteria under various hydrodynamic and nutrient conditions (Schut et al., 1997). Recent studies using molecular biological techniques have shown the existence of diverse bacterial communities within marine systems (Fuhrman et al., 1994; Lee and Kemp, 1994; Suzuki et al., 1997), which may respond to external forcing in di!erent ways resulting in biomass and growth rate di!erences. However, there have been few studies on the potential growth characteristics of bacterial communities under di!erent biological, seasonal and hydrodynamic conditions. In a cross-system overview, Cole et al. (1988) found a general correlation between Chl a and bacterial biomass, as well as photosynthetic and bacterial production. However, many exceptions to this general trend have been reported (e.g. Shiah and Ducklow, 1994). Estimates of carbon #ux through bacteria range from 0 to '100% of local primary production (Pomeroy et al., 1991; Kirchman et al., 1993). Decoupling of phytoplankton and bacteria has been reported to be due to a response to allochthonous inputs at speci"c times of the year (Kepkay et al., 1993), seasonal changes (Pomeroy et al., 1991; Lovejoy et al., 1996), and variations in hydrodynamic conditions (Cho et al., 1994). Recent work indicates that fresh DOM is more readily used by bacteria than older DOM (Amon and Benner, 1996). A lag e!ect has been postulated to explain the ability of bacteria to decouple from current primary production in regions such as open oceans that lack substantial allochthonous input (Kirchman et al., 1993; Billen and Fontigny, 1987). If there is not enough DOM readily available

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to bacteria after a few days, then mechanisms for maintaining the pool of utilizable DOM (e.g. Tranvik, 1993) are required (see also Thingstad et al., 1996). Analogous to the evidence that only a small portion of DOM in marine systems can be used rapidly by free-living pelagic bacteria (Van Wambeke, 1994; Amon and Benner, 1996) and that fresh DOM becomes refractory with time (e.g. Keil and Kirchman, 1993; Nagata and Kirchman, 1996), there have been suggestions that large numbers of non-active bacteria and a small pool of active bacteria have rapid turnover rates, mirroring refractory vs. labile DOM (JuK rgens and GuK de, 1994). Microautoradiographic studies consistently have shown that a variable proportion of bacteria in aquatic systems are metabolically active at any given time (e.g. Hoppe, 1976; Tabor and Neihof, 1984; Grossmann, 1994; Karner and Fuhrman, 1997). The existence of active vs. inactive bacteria is ecologically signi"cant since many #agellates are selective feeders and reject inert particles (Landry et al., 1991; Monger and Landry, 1992). Both chemical and behavioral properties of prey are positively selected by actively feeding protists (GonzaH lez et al., 1993; Christo!ersen et al., 1997). At present, there is no perfect way to determine the actual numbers of active bacteria in natural marine waters (Karner and Fuhrman, 1997; Schut et al., 1997) The #uorescent redox marker CTC, when used under carefully controlled conditions, provides an estimate of the proportion of respiratory active bacteria (actively respiring cells, ARCs) at the time of collection and over short incubation times under in situ nutrient conditions (Lovejoy et al., 1996; Karner and Fuhrman, 1997; Kalmbach et al., 1997). Ullrich et al. (1996) accurately point out that CTC kills bacteria by interrupting the respiratory chain, but this only happens when bacteria take up the #uorogenic CTC and the #uorescent compound is produced. The accepted methodology for bacterial enumeration, i.e. #uorescent staining using DAPI (Porter and Feig, 1980) or Acridine Orange (Hobbie et al., 1977), has been recently questioned. There have been suggestions that total bacterial numbers had been underestimated (Turley and Hughs, 1992; Suzuki et al., 1993) or overestimated in terms of viable bacteria (Sieracki et al., 1995; Zweifel and HagstroK m, 1995). It is recognized that neither total DAPI stained bacteria nor CTC #uorescently marked bacteria provides an estimate of the viable portion of the bacterial assemblage. Assuming that DAPI overestimates and CTC underestimates viable bacteria, in the present study we compare the apparent potential growth rate (Al) for both DAPI and ARCs. The aim of our study was to determine what factors were associated with bacterial growth and biomass characteristics in the Gulf of St. Lawrence for two separate seasons. We investigated potential controlling variables, including physical and chemical factors such as inorganic nutrients and temperature and also nanoplankton community structure. We taxonomically identi"ed and classi"ed each nanoplankton taxon according to its likely trophic mode. In addition, since not all bacteria are metabolically active at any given time (Karner and Fuhrman, 1997; Kalmbach et al., 1997), we predicted that a proxy for active bacteria (i.e. ARCs) would be more closely correlated to nanoplankton community structure or environmental factors than would total bacteria. We compared conditions during the cold-water spring bloom (high photosynthetic rates and Chl a concentrations, low bacterial productivity and numbers) with summer strati"ed conditions (low photosynthetic rates, Chl a

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concentrations and high bacterial productivity and numbers). The latter characteristics are commonly encountered in many oceanic systems (Kirchman et al., 1993). In summary, the &active' and &inactive' bacteria were compared for di!erent temperature, nutrient, and biological conditions that possibly could regulate bacterial numbers and production.

2. Materials and methods 2.1. Sampling Samples were collected in the Gulf of St. Lawrence (Fig. 1) at sites that were chosen because of their contrasting hydrodynamic characteristics. In mid-April 1994, four stations (1, 2, 4, and 5) were visited on board the Canadian Coast Guard ice breaker Sir =ilfrid ¸aurier. During the second half of June, sampling was from the CSS Hudson at the same sites as in April, plus three additional sites: Station 3 in the Gulf and two sites o! the coast of Nova Scotia, Station S (continental slope) and Station B (Emerald Basin). Vertical pro"les of temperature, salinity, and photosynthetically available radiation (PAR; BioSpherical instrument SPQ 200) were recorded with a Seabird SBE 25 CTD mounted on a rosette sampler (General Oceanics) or a Seabird SBE 9 plus CTD. Water samples were taken on the upcasts at 7 photic depths (calculated using PAR attenuation coe$cients) from 100 to 0.1% of surface irradiance using 8-l lever-action Niskin bottles (General Oceanics). At each station we selected 1}3 samples from the mid-to-deep euphotic zone for detailed taxonomic analysis of nanoplankton. Below the euphotic zone, samples were from every 50 m at stations

Fig. 1. Map of study area showing locations of the stations sampled in April and June 1994. Station 1; 49340@N, 66300@W, z"360 m: Station 2; 49340@N, 62300@W, z"275 m: Station 3; 47340@N, 60300@W, z"525 m: Station 4; 47305@N, 62330@W, z"60 m: Station 5; 47348@N, 64300@W, z"80 m: Station S; 42354@N, 61345@W, z"850 m: Station B; 43350@N, 62349@W, z"240 m.

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4 and 5, and every 100 m at the deeper stations. An additional sample was always taken within 5}10 m of the bottom. Samples for chlorophyll a (Chl a), which had been pre"ltered through a 200-lm Nitex mesh, were "ltered onto GF/F "lters immediately upon collection and extracted overnight with 90% acetone, after which #uorescence was measured using a Turner 111 Fluorometer. Chl a concentrations were calculated following Holm-Hansen et al. (1965). We estimated carbon content for the photosynthetic community using vertically integrated Chl a and a conversion factor of C : Chl a"62.8, which we derived from the biovolumes (BV, lm3) of the photosynthetic component of cell counts using the equation in Verity et al. (1992), where pgC"0.433(BV)0.863. BV was estimated for each taxon as outlined below. Chl a and phytoplankton C were signi"cantly correlated (linear correlation coe$cient r"0.9, n"16, data not shown). Although C : Chl a varies due to taxonomic and physiological di!erences (Booth, 1988; Christian and Karl, 1994), there were no signi"cant (2-way ANOVA) or consistent di!erences among stations or seasons and we used the same value for all samples. Photosynthetic productivity was estimated on water samples collected in conjunction with Chl a. The daily rate of photosynthesis was determined by adding 10 lCi 14C-NaHCO to 600 ml samples. The samples were incubated over 24 h (from dawn 3 to dawn) at simulated in situ irradiances in on-deck incubators. The irradiances corresponded to the depths of collection down to the 1% of the surface value, with an additional 0.1% bottle as a check on the lower limit of euphotic zone. Activity was determined using a Wallack Rackbeta scintillation counter within 2 weeks (spring) or with a Beckman LS5000CE on board the ship (summer), both counters used internal calibration standards. DPM in samples from the June cruise, counted using the two counters, were within 1% of each other (data not shown). Carbon "xation was calculated following Parsons et al. (1984). Samples for nutrient analyses were collected directly from the Niskin bottles using a syringe equipped with a pre-combusted GF/F "lter. Ammonia, PO , and 4 NO #NO were analyzed immediately on board the ship using a Technicon 3 2 Autoanalyser (Parsons et al., 1984). Samples for microbial analysis were pre"ltered through a cleaned 200-lm Nitex "lter and collected into 1}l Nalgene bottles that had been cleaned, acid rinsed, and rinsed three times with sample water prior to "lling. These were stored in the dark at ca. 23C, and all subsequent analyses were done on subsamples from these bottles. The samples for detailed phytoplankton and protozoa enumeration were preserved immediately with a mixture of bu!ered glutaraldehyde and fomaldehyde, and stored in the dark at 2}43C (Tsuji and Yanagita, 1981). 2.2. Laboratory analyses Picophytoplankton and bacterial cell numbers, ARCs, and bacterial productivity using 3H-TdR were determined as outlined in Lovejoy et al. (1996). Samples for 3H-TdR-bacterial productivity and ARCs were incubated within 23C of the in situ temperature. Bacterial carbon demand (C ) was calculated as productivity (P) conD verted to carbon: C "P(1/E ), where E is the e$ciency of carbon conversion. D 3 3

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Published values of E vary widely; 20}30% is commonly accepted (e.g. Kristiansen 3 et al., 1992; Azam et al., 1992; Kirchman et al., 1993). We used 30% as a conservative value, given that low e$ciencies would result in high carbon demand estimates. We assumed 20 fg C bacteria~1 (e.g. Fuhrman, 1992; Fagerbakke et al., 1996) and a theoretical conversion factor of 2]1018 cells per mole of 3H-TdR "xed (e.g. Robarts and Zohary, 1993). The apparent potential growth rate (Al modi"ed from Peterson, 1984; Tilzer, 1987) was estimated as

A

B

1 Pt Ak" ln 1# , t B where t is one time unit (in this case 1 h), P the productivity (cells l~1) and B the number of cells l~1, either total DAPI stained bacteria (for Al-bacteria) or ARCs (for Al-ARCs). Growth rates have been previously estimated with the equation stated as k"ln(1#P/B), which is dimensionally incorrect. Phytoplankton and protozoa were enumerated using Fluorescence Nomarski UtermoK hl (FNU) microscopy as in Lovejoy et al. (1993), with an additional concentration step. The 500 ml samples were settled for several days, after which they were concentrated using reverse "ltration through a 5 lm Nitex net. A 5 ml sub-sample of the resulting 20}25 ml concentrate was then stained with DAPI and re-settled in 5-ml UtermoK hl counting chambers for 24 h before being examined at 400 and 1000X. The majority of organisms counted were within the size range of nanoplankton (2}20 lm), but some of the early spring samples contained diatoms such as Fragilariopsis chains with cells up to 30 lm in length, these diatoms were included in the analysis since the cells were (20 lm in other dimensions. Although we counted cells (5 lm, this part of the community was probably underestimated. The FNU method takes advantage of both #uorescence and light microscopic characteristics of the plankton, which provide information on pigment composition and cellular morphology, respectively. In addition to being able to identify strict heterotrophs quickly (by the lack of photosynthetic pigment #uorescence), this approach enables the taxonomic identi"cation of #agellates and other nanoplankton by an experienced worker. Phytoplankton and protozoa were identi"ed to the lowest taxa possible with light microscopy (Patterson and Larsen, 1991; Tomas, 1993,1996; V+rs, 1992,1993). Using this taxonomic information, we classi"ed each species by trophic status according to recent literature surveys (e.g. Jacobson and Anderson, 1986,1994,1996; Schnepf and ElbraK chter, 1992; Nygaard and Tobiesen, 1993; Keller et al., 1994; Hoek et al., 1995). We had complete nanoplankton data for a total of 7 spring and 10 summer samples. Biovolumes were calculated for individual taxa from measurements of preserved specimens using standard geometric shapes which approximated the cell shape. Since the extent or type of mixotrophy in situ was not directly determined, the term mixotroph is used in a broad sense and includes species ranging from those that are predominantly photosynthetic but rely on osmotrophic uptake of organic compounds to those that are predominately phagotrophic but capable of photosynthesis (Jones, 1994; Raven, 1997). For the correlative analysis of nanoplankton community structure, the bacterial data were from samples taken from the same water bottle as the phytoplankton-protozoan samples.

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2.3. Data analysis All available data were initially entered into a relational data base (Paradox Borland), which facilitated grouping and sorting the results by geographic, seasonal and irradiance zones. The nanoplankton data, which also had been entered into the relational data base, were also sorted by trophic category; these data were compared directly with the bacterial data taken from the same water bottle. All relationships were tested using Spearman's rank-order correlations (SRO) unless noted otherwise. This nonparametric method measures the strength of association between pairs of variables without assuming any underlying distribution or variance homogeneity.

3. Results 3.1. General The dates of sampling and the general physical and biological properties of the stations are given in Table 1. There were no di!erences between spring and summer Gulf stations in terms of mixing depth, euphotic depth and photosynthetic C "xation per unit Chl a (2-way ANOVAs; P'0.05). Picophytoplankton were always low in the Gulf compared to the Scotian Shelf, but tended to be slightly higher in summer than spring. There were no overall signi"cant correlations between Chl a and bacterial numbers (BN) or ARCs within the euphotic zone, nor was there any correlation between photosynthetic and bacterial productivity (P'0.05, n"46, data not shown). The pooled average concentrations for BN, ARCs and percent ARCs, for di!erent geographic, seasonal and irradiance zones are shown in Table 2. To facilitate Table 1 Physical and biological characteristics at the sampling stations. Euphotic depth is the 1% light level. Picophy"picophytoplankton; P/B"photosynthetic productivity/Chl a biomass calculated as :P/:B; (data were integrated to the bottom of euphotic zone); *"no data. Station

Date

Mixing depth (m)

Euphotic depth (m)

Picophy (109 cells m~2)

P/B (mg C mg~1 Chl a d~1)

1 2 4 5

12/04/94 15/04/94 17/04/94 19/04/94

20 35 38 26

26 33 31 17

2.98 2.12 8.36 1.81

* 25 70 29

1 2 3 4 5 S B

20/06/94 22/06/94 25/06/94 16/06/94 18/06/94 28/06/94 28/06/94

11 10 20 11 15 24 15

30 54 40 33 13 35 42

16.7 4.63 17.1 7.58 5.88 201 404

27 25 25 27 12 29 *

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Table 2 Mean and standard error (in parentheses) of bacterial numbers (BN) and actively respiring bacterial cells (ARCs) for the di!erent zones (seasons and '1% vs. (1% surface irradiance, euphotic depths given in Table 1). % ARCs"(ARCs/BN)]100, n"number of samples in each zone used for this analysis. Zone

n

BN (108 cells l~1)

ARCs (106 cells l~1)

% ARCs

Spring euphotic Spring deep Summer euphotic Summer deep Scotian euphotic Scotian deep

25 22 31 27 13 16

3.91 2.13 9.59 3.34 7.81 1.94

8.59 2.84 58.11 4.64 73.71 1.10

2.43 1.31 5.04 0.90 9.77 0.46

(0.24) (0.77) (1.21) (0.44) (0.90) (0.38)

(0.80) (0.51) (11.8) (2.08) (10.9) (0.35)

(0.39) (0.24) (0.66) (0.20) (1.32) (0.10)

comparisons among stations, we calculated the proportions of ARCs (PARCs"ARCs/BN). Overall 6.3% of total bacteria were classi"ed as ARCs (all stations, seasons and depths), the values from euphotic depths ranged from 1.2% at Station 2 to 4.1% at Station 1 (mean 2.4%) in spring. Summer values were higher on average (mean 5.0% Table 2); PARCs in the Gulf euphotic zone were 3}4.5% at Stations 1, 2, 3, and 4 and 10% at Station 5. There was a high proportion of ARCs at the Scotian Shelf sites (mean 9.8%) compared to the summer Gulf sites, the highest value recorded was at station S where ARCs represented 11.9% of total DAPI bacteria. Vertically integrated data over the euphotic zone was used to compare the microbiological characteristics BN, ARCs and bacterial productivity (BP), at di!erent stations and seasons. The lower limit of the integration was de"ned as extending down to the 1% irradiance level, except for Station 1 in summer (1p), which was integrated down to the 10% surface irradiance because there were no bacterial productivity data available below this depth. In the Gulf BN and ARCs were lower in spring than summer, as was BP (Fig. 2a and b). The Scotian Shelf values for BP and BN were similar to the summer Gulf values (Fig. 2a and b). Euphotic zone Chl a (converted to carbon) and photosynthetic productivity also were vertically integrated for the same samples (Fig. 2a and b). The actual Chl a values (not shown) were high in spring, i.e., 54, 95 and 129 mg Chl a m~2 at Stations 1, 2, and 5, respectively. In June, concentrations were 5}14 times lower, i.e. 11, 7, and 17 mg Chl a m~2 at the previous stations and 12 mg Chl a m~2 at Station 3. Phytoplankton biomass at Station 4, which was the lowest in April (18 mg Chl a m~2), was similar to other summer Gulf values in June (14 mg Chl a m~2). On the Scotian Shelf, values were 24 and 14 mg Chl a m~2 at Stations S and B, respectively. Photosynthetic productivity followed the same seasonal trend as biomass, with higher spring and lower summer values (Fig. 2b). Station S, the only station outside the Gulf where photosynthetic productivity was determined, had the highest rates of all stations in June (681 mg C m~2 d~1; Fig. 2b). Additional comparisons of seasons and stations showed that within the euphotic zone, bacterial carbon demand (C ) was low in spring, i.e. 5}9% of daily photosynD thetic productivity, and high in summer, 78% (Station 4) to 372% (Station 1p) in the

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Fig. 2. Vertically integrated data down to 1% irradiance for all stations, and values for part of Station 1 (1p, down to the 10% irradiance level): (a) phytoplankton Chl a, bacterial numbers and ARCs all converted to carbon (mg C m~2); (b) photosynthetic (PP) and bacterial productivity (BP); (c) theoretical C demand for photosynthetic production by bacteria assuming 30% e$ciency.

Gulf and 51% at the one station (Station S) where it was determined on the Scotian Shelf (Fig. 2c). 3.2. Bacteria, nutrients and temperature Using non-integrated data and the entire data set, we assessed relationships between nutrients and temperature, and the bacterial variables ARCs, BP and BN. We also tested relationships among these bacterial variables. The general patterns of ARCs as a function of nutrients or temperature (Fig. 3a}d) were similar to those of BP (Fig. 4a}d) and total BN (not shown). Overall, ARCs and BP were negatively related

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Fig. 3. ARCs compared to in situ (a) temperature and concentrations (lM) of (b) PO , (c) NH , and (d) 4 4 NO #NO . Samples from di!erent zones were grouped to show di!erences between spring and summer, 3 2 inside and outside the Gulf, and euphotic zone vs. below.

to PO and NO #NO and positively to temperature. BP was correlated with 4 3 2 ARCs when all data were pooled (all stations, and both seasons, not shown; r"0.76, P(0.0001, n"123) and with BN (r"0.70, P(0.0001, n"123); there was also a positive correlation between BP and PARCs (r"0.61, P(0.0001, n"123). BP generally tracked both BN and ARCs down the water column (not shown). Apart from the overall trends above, bacterial community variables were tested against the environmental variables by grouping the data by geographic, seasonal and photic zones (Table 3, data given as separate symbols in Figs. 3 and 4). The euphotic zone data showed several signi"cant trends. In the Gulf, temperature was positively correlated with BP in April, and with BP, ARCs, and BN in June. Scotian Shelf BP values were for one station only (Station S) and, with n"6, the correlation was not statistically signi"cant (P'0.05) despite r"0.83. Generally, PO and NO #NO 4 3 2 showed negative relationships with the three bacterial variables; this was statistically

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471

Fig. 4. Bacterial productivity as estimated with 3H-TdR. Same groupings as in Fig. 3.

signi"cant for all three bacterial variables for the samples taken in the Gulf. For Gulf spring and Scotian Shelf summer samples, BN and PO showed signi"cant negative 4 correlations. NH was not correlated with any variables tested. 4 Below the euphotic zone (deep) ARCs showed a signi"cant negative relationship with temperature in spring and summer. BP was also negatively correlated with temperature during summer. The three bacterial variables showed statistically signi"cant negative relationships with PO for Scotian samples. NO #NO was 4 3 2 negatively correlated with BP on the Scotian Shelf. In the Gulf, NO #NO was 3 2 statistically negatively correlated with ARCs. NH showed a signi"cant positive 4 correlation with ARCs for both seasons and with BP during summer (Table 3). 3.3. Nanoplankton and bacteria The bacterial characteristics were analyzed along with the relative abundance of phytoplankton and protozoan taxa. All nanoplankton species encountered were

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Table 3 Spearman's rank-order correlation coe$cients (r) between bacterial and environmental variables analyzed by zone as described in the text. BP (Fig. 3) and ARCs (Fig. 4); BN data not shown. *P:(0.05, **P:(0.001. Variable and zone

Temperature

PO 4

NO #NO 3 4

NH 4

BP Spring euphotic Spring deep Summer euphotic Summer deep Scotian euphotic Scotian deep

0.55** 0.25 0.79** !0.80** 0.83 0.26

!0.34 0.31 !0.56** !0.14 0.26 !0.71**

!0.12 0.07 !0.64* !0.32 0.24 !0.71**

!0.02 !0.04 !0.10 0.67** !0.27 !0.03

ARCs Spring euphotic Spring deep Summer euphotic Summer deep Scotian euphotic Scotian deep

0.35 !0.79** 0.74** !0.84** 0.11 0.29

0.03 !0.76** !0.51** !0.31 !0.43 !0.63**

0.05 !0.85** !0.67** !0.80** !0.22 !0.32

!0.22 0.76** !0.13 0.74** 0.12 !0.36

BN Spring euphotic Spring deep Summer euphotic Summer deep Scotian euphotic Scotian deep

0.20 !0.03 0.75** !0.29 !0.27 0.50

!0.55* !0.02 !0.46** 0.16 !0.70** !0.67**

!0.21 !0.12 !0.61** !0.14 0.33 !0.25

0.09 !0.08 !0.06 0.31 !0.33 !0.45

classi"ed into functional trophic categories as outlined in the methods. The total nanoplankton cell concentrations (Table 4) tended to be higher in spring than summer, and covered a wide range of values within each season. To facilitate statistical analysis and "nd trends despite the large di!erences in total biomass between seasons and stations, PARCs were compared to the proportions of di!erent trophic categories, PPhotos (proportion of phototrophs), PMixos (proportion of mixotrophs), and PHeteros (proportion of heterotrophs; Fig. 5a}c). The means of spring and summer data for ARCs and BN (Table 4) of samples with corresponding information on nanoplankton were similar to the overall means of the respective euphotic zone groups given in Table 2. The dominant phototrophs were both large chain-forming (e.g. Fragilariopsis spp. and Thalassiosira spp.) and small (Minidiscus spp., 4 lm diameter and Chaetoceros minimus, 2}3 lm diameter) diatoms, while mixotrophic taxa came from a wide range of algal groups. The most frequently encountered heterotrophs were small bodinids and bicosoecids (e.g. Cafeteria spp., 2}4 lm). There was an overall positive correlation between PMixos and PARCs, which was stronger in summer than spring (Table 5, Fig. 5a). There was no signi"cant trend between PPhotos and PARCs (Fig. 5b). The

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Table 4 Details of samples used for the nanoplankton community analysis. Bact. is total DAPI stained particles, ARCs (actively respiring cells) are bacteria which had taken up the #uorogenic CTC. Mixos are #agellates likely to be mixotrophic in a broad sense (chrysophytes, euglenoids, prymnesiophytes, dino#agellates, rhaphidophytes, non-scaly prasinophytes). Heteros are aplastic #agellates, and Photos are diatoms, coccolithophores and scaly prasinophytes, considered to have minimal to no heterotrophic capability. All data expressed as cells l~1. Season

Station (depth, m)

Bact. (108 l~1)

Spring Spring Spring Spring Spring Spring Spring Mean (SD)

1 (8.0) 1 (13.0) 2 (16.5) 4 (7.5) 4 (31.0) 5 (5.1) 5 (8.5) Gulf

3.76 3.15 3.17 3.37 4.74 5.09 3.49 3.83 (0.78)

1.36 1.37 0.45 0.86 0.55 1.21 1.01 0.97 (0.37)

Summer Summer Summer Summer Summer Summer Summer Summer Summer Mean (SD)

1 (4.2) 1 (15.0) 1 (30.0) 2 (7.5) 2 (20.0) 3 (12.0) 4 (4.5) 4 (33.0) 5 (13.0) Gulf

22.40 11.67 6.66 7.02 4.48 6.04 8.43 2.77 9.47 8.77 (5.75)

6.59 2.42 0.81 6.05 0.72 5.03 2.56 0.62 10.58 3.93 (3.39)

Summer

S (18.0)

9.19

ARCs (107 l~1)

12.40

Mixos (105 l~1)

Heteros (105 l~1)

Photos (105 l~1)

8.11 6.10 1.67 1.05 0.61 1.25 1.02 2.83 (2.99)

3.30 0.30 0.84 0.80 0.79 0.64 1.25 1.13 (1.00)

2.49 0.98 0.71 2.16 1.43 7.46 12.24 3.93 (4.32)

1.97 0.92 0.24 0.41 0.57 4.13 0.99 2.17 3.00 1.60 (1.32)

1.77 0.76 0.37 0.28 1.23 2.91 0.94 2.41 1.16 1.31 (0.89)

0.27 0.45 0.18 0.18 0.25 0.30 0.36 0.60 1.01 0.40 (0.27)

9.69

1.32

26.53

overall correlation between PHeteros and PARCs was not signi"cant but, when spring and summer samples were analyzed separately, there was a strong negative correlation between PHeteros and PARCs in summer (Fig. 5c, Table 5), but not in spring because of fewer data. The proportion of phototrophic taxa showed no signi"cant correlation with the proportion of heterotrophic nanoplankton (not shown). There was a statistically signi"cant relationship between PPhotos and PMixos, which corresponded to a negative exponential model (Fig. 5d). Since the biomass (i.e. volume) of heterotrophic protists should be supported by bacterial production rates, we correlated the total volume of all heterotrophic micro- and nanoplankton, which included a few ciliates and larger non-photosynthetic dino#agellates (Protoperidinium spp), with bacterial production as a check on the validity of the method for trophic classi"cation. The two were positively correlated (Fig. 6; r"0.60, P(0.05). There was no signi"cant correlation (P'0.05) of BP with the number of heterotrophs or the numbers and volumes of mixotrophs or phototrophs. The apparent potential growth rates based on ARCs (Al-ARCS, an underestimate viable bacteria) showed statistically signi"cant negative correlations with PMixos,

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Fig. 5. Relationships between the proportions of di!erent trophic groups and the proportion of ARCs (PARCs): (a) proportion of mixotrophs (PMixos), regression on all data; (b) proportion of phototrophs (PPhotos), no statistically signi"cant correlation; (c) proportion of heterotrophs (PHeteros), the regression line is for summer data only; and (d) PPhotos vs. PMixos. Lines correspond to model II linear regressions (a, c) and exponential model (d).

and was signi"cantly positively correlated with PPhotos. There was no signi"cant correlation with PHeteros (Table 5; Fig. 7a}c). The apparent potential growth rate of based on total DAPI stained bacteria (Al-bacteria, an overestimate viable bacteria) showed no signi"cant correlations with the proportions of di!erent nanoplankton (Table 5, Fig. 7d}f ). A general schematic model of the signi"cant relationships among the bacterial and nanoplankton community proportions (Fig. 8) and will be explained below.

4. Discussion 4.1. Bacteria and nanoplankton communities The availability of DOC has frequently been credited with limiting bacterial production (e.g. Cole et al., 1988; Kirchman et al., 1993). DOC is part of the DOM

C. Lovejoy et al. / Deep-Sea Research II 47 (2000) 461}487

475

Table 5 Spearman's rank-order Correlation coe$cient (r) between bacterial variables and community structure: *P(0.05, **P(0.001. PMixos, PPhotos, and PHeteros as described in text. The number used for each correlation is n. Type and season Total (April and June) PMixos

PARCs

r n

0.718* 16

PPhotos

r n

!0.332 16

PHeteros

r n

!0.153 16

r n

0.464 7

PPhotos

r n

!0.357 7

PHeteros

r n

!0.679 7

April only PMixos

June only PMixos

r n

0.850** 9

Al-ARCs

Al-Bacteria

!0.696* 15

!0.0607 15

0.557* 15

0.264 15

!0.232 15

!0.254 15

!0.893** 7

!0.429 7

0.857* 7

0.464 7

!0.179 7

!0.643 7

!0.524 8

0.214 8

PPhotos

r n

!0.167 9

0.238 8

0.262 8

PHeteros

r n

!0.817* 9

0.548 8

!0.286 8

pool. The major sources of DOM used by bacteria for growth are: photosynthetic extra-cellular release (Sharp, 1977; Obernosterer and Herndl, 1995), sloppy feeding and faeces production by zooplankton (Lampert, 1978) and microzooplankton (ElbraK chter, 1991; Nagata and Kirchman, 1992), and viral lysis (Procter and Fuhrman, 1990; Fuhrman, 1992; Suttle, 1994; Garza and Suttle, 1995). Other factors also have been proposed as limiting bacterial productivity in marine systems, such as inorganic nutrients (Kirchman, 1994; Pomeroy et al., 1995; Thingstad and Rassoulzadegan, 1995), temperature (Pomeroy and Deibel, 1986; Shiah and Ducklow, 1994), and grazing by heterotrophic nano#agellates limiting bacterial populations (Sherr and Sherr, 1991; Gasol and VaqueH , 1993). In the present study, we tested correlative relationships between bacterial variables and these di!erent potential controlling factors. Initially, we investigated phytoplankton}bacteria relationships using

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Fig. 6. Production rate of bacteria compared to the volume of all heterotrophs, including ciliates and dino#agellates. Line corresponds to model II regression.

traditional techniques where photosynthetic and bacterial productivity and biomass were compared (Fig. 2). We then assessed bacterial productivity and biomass relative to temperature and inorganic nutrients within di!erent geographical, seasonal and photic zones (Fig. 4, Table 3). To this standard approach, we added a relative estimate of active bacteria (ARCs) and found correlative relationships not detected using estimates of total (i.e. DAPI stained) bacterial numbers. We then assessed relationships between bacterial variables and di!erent trophic components of the nanoplankton (phytoplankton and small protists) in a subset of samples. The phytoplankton}protozoa species composition for the two seasons was quite di!erent. A major component of the phytoplankton consisted of small #agellates that are thought to in#uence bacterial dynamics (e.g. Rassoulzadegan and Sheldon, 1986; Weisse and Sche!el-MoK ser, 1991; Wikner and HagstroK m, 1988). Recent studies have discriminated between HNAN (heterotrophic nano#agellates) and PNAN (phototrophic nano#agellates) collected on "lters using epi#uorescence microscopy. Unfortunately, this approach ignores diversity among heterotrophs (V+rs et al., 1995; Zubkov and Sleigh, 1995) and phototrophs. PNANs have been found to be potential predators of bacteria (Hall et al., 1993), but both phototrophic and mixotrophic #agellates may be found within a sample and without identi"cation it is not possible to classify the cells by trophic status since neither size nor pigment content is reliable for determining the potential for autotrophy, mixotrophy, or heterotrophy (e.g. Jones, 1994; Jacobson and Anderson, 1996). Identi"cation to species level often requires cultivation and electron microscopy, but characteristics for identi"cation to the level of family or genus can be observed with light microscopy. Identi"cation at this level is a major step towards trophic grouping of photosynthetic, as well as non-photosynthetic #agellates and dino#agellates, which may be saprotrophic or phagotrophic. The combination using #uorescence, UtermoK hl and Nomarski microscopy (Lovejoy et al., 1993) enabled us to separate the nanoplankton into taxonomic and functional trophic groups and estimate the proportion of mixotrophs.

C. Lovejoy et al. / Deep-Sea Research II 47 (2000) 461}487

477

Fig. 7. Bacterial growth rates and nanoplankton groups as in Fig. 5. (a) Al-Arcs and PMixos, line corresponds to model II regression for all data; (b) Al-Arcs PPhotos, line corresponds to model II regression for all data; (c) Al-Arcs and PHeteros; (d) Al-bacteria and PMixos; (e) Al-bacteria and PPhotos; (f) Al-bacteria and PHeteros. Statistically signi"cant relationships are given in Table 5. Open symbols are for Spring Gulf samples, closed symbols are for Summer samples.

4.2. Spring conditions During spring, both Chl a and primary productivity were high. The sea ice was either thin or recently melted, and the phytoplankton assemblage included such cold-water species as Fragilariopsis oceanica ("Nitzschia grunowii in Poulin, 1990).

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C. Lovejoy et al. / Deep-Sea Research II 47 (2000) 461}487

Fig. 8. Conceptual model describing four nanoplankton domains in relation to environmental and bacterial variables. The nanoplankton communities are distinguished by the dominance of mixotrophic (M), phototrophic (P) or heterotrophic (H) species. PARCs"proportion of actively respiring bacteria as measured by CTC; Al-ARCs"the apparent speci"c growth rate of the actively respiring bacteria (see text). The present study encompassed the M, H and P#H conditions, but conditions with high nutrient and high irradiance input were not encountered.

Nutrient concentrations were high, and with the disappearance of ice cover and with the onset of spring, irradiance was also high, so that phytoplankton were growing under ideal conditions. Bacterial carbon utilization represented a very low proportion of primary productivity (Fig. 2c). Since nutrient concentrations were high, inorganic nutrients would not have likely limited bacterial production (Fig. 4b}d). However DOC may have been limiting due to some or all of the following: (1) algae in logarithmic growth phase in the absence of physiological stress are believed to excrete only a low percentage of the carbon "xed (Sharp, 1977; Wood et al., 1992; MalinskyRushansky and Legrand, 1996); (2) the biomass of zooplankton relative to phytoplankton was lower in spring than later in the season (Roy et al., 2000) so that release of fresh DOC by grazing would also have been less; (3) protozoan numbers (Fig. 5c) were low relative to phytoplankton, and microbial predation on phytoplankton and DOM release by cell rupture would have been limited (e.g. Lessard, 1991; Jacobson and Anderson, 1996). Bacterial productivity in the euphotic zone was correlated with water temperature (Table 3), but for the same period euphotic zone ARCs and bacterial numbers showed no such correlation. There was a gradient in the relative proportions of phototrophs and mixotrophs in the spring samples (Table 4, Fig. 5d, circles). Apparent potential growth rates for the respiratory active population (Al-ARCs) showed a negative correlation with the proportion of mixotrophs and a positive correlation with the proportion of phototrophs (Table 5), which could be interpreted as more rapid bacterial growth in phototroph dominated samples compared to mixotroph dominated samples. Both total bacteria and ARCs were low

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479

(Table 2, Fig. 2a), which suggests high loss rates. The temperature e!ect on bacterial production characteristics was similar to that found o! the coast of Newfoundland in early spring (Pomeroy and Deibel, 1986; Pomeroy et al., 1991), with low bacterial activity and high phytoplankton production rates. 4.3. Summer conditions In summer, there was lower photosynthetic productivity than in spring and theoretical C demand by the bacterial population exceeded photosynthetically "xed C at most stations. The maintenance of bacterial productivity indicates that there was a mechanism for recycling C within the system (Amon and Benner, 1996). Euphotic zone characteristics were similar to those found in many systems dominated by microbial food-web processes (e.g. Azam et al., 1994). Bacterial biomass estimated from total bacterial numbers was near or in excess of photosynthetic biomass estimated from Chl a (Fig. 2a). Bacterial production was similar to photosynthetic production (Fig. 2b). Phytoplankton were generally experiencing conditions of low nutrients, especially N (Figs. 3 and 4d, closed squares, with only 4 of the summer points above 5 lM), which may have led to increased extracellular carbon release (Obernosterer and Herndl, 1995). The most likely source of labile DOC however, was, sloppy grazing, since zooplankton biomass was high relative to phytoplankton carbon (Roy et al., 2000). These factors suggest that bacteria were well supplied with fresh DOM during the June sampling period. Given either non-signi"cant or negative correlations of euphotic zone BP, ARCs, and BN with inorganic nutrients (Table 3), there is no evidence that bacteria themselves were limited by the availability of either N or P, despite low nutrients concentrations, especially NO #NO , which was often 3 2 undetectable (as noted above, relative to photosynthetic productivity). It follows that N was probably available in a rapidly recycled form for bacterial use (e.g. Suttle et al., 1990; Glibert, 1993; Nakano, 1994). While bacterial productivity was high compared to photosynthetic productivity in summer, the total proportion of ARCs was negatively correlated with the proportion of heterotrophic nanoplankton (Fig. 5c, Table 5) which supports the notion of preferential grazing (Van Houten, 1988; GonzaH lez et al., 1993; Schuster and Levandowsky, 1996) of active prey by heterotrophic #agellates in these samples. The dominant photosynthetic nanoplankton in summer samples, both inside and outside the Gulf, were mixotrophic #agellates (Table 4, Fig. 5d). The proportion of mixotrophic #agellates was positively correlated with PARCs (Fig. 5a, Table 5). There have been reports linking mixotrophs with high bacterial numbers and productivity (Wood and Van Valen, 1990; Paran et al., 1991). The increased proportion of respiratory active bacteria, high bacterial productivity (Fig. 2a) but lower Al-ARCS suggest that mixotrophs and bacteria interact other than as predator and prey. Such results can be interpreted by one or several of four mechanisms: (1) mixotrophic species stimulate bacterial activity by releasing substrate for bacterial use; bacteria take up and concentrate inorganic nutrients more e$ciently than mixotrophs (Malinsky-Rushansky and Legrand, 1996), after which the latter access these nutrients indirectly via phagotrophy (Paran et al., 1991); (2) mixotrophic species in general may be less selective in their prey choice than strict heterotrophs (Epstein

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C. Lovejoy et al. / Deep-Sea Research II 47 (2000) 461}487

and Shiaris, 1992), or prefer phototrophs (Jones et al., 1993), so that active bacteria are able to maintain high populations in mixotroph dominated systems; (3) DOM released by phototrophs or mixotrophs, derived predominately from photosynthesis, is more readily utilized by bacteria than DOM derived predominantly from heterotrophic processes by either mixotrophs or heterotrophs (Tranvik, 1994); (4) a high proportion of active bacteria promote some species of organotrophic mixotrophs by releasing easily assimilated sources of organic nutrients (Glibert, 1993). In June, mechanisms 1 and 4 were consistent with the higher numbers of mixotrophs and lower Al-ARCs compared to spring. In spring, the negative correlation between PMixos and Al-ARCs (and the converse positive correlation between PPhotos and Al-ARCs) suggests mechanisms 2 and 3 may have been dominant. 4.4. Deep water Deep-water samples did not show similar bacterial responses to temperature and nutrients as in the euphotic zone, indicating that di!erent mechanisms were operating in controlling growth and production. Signi"cant correlations were often the opposite of those for the euphotic zone. Bacterial productivity was negatively correlated with temperature for the deep summer Gulf, and ARCs were negatively correlated with temperature in both spring and summer (Table 3). Concentrations of NH were 4 positively correlated with ARCs and BP, whereas NH did not correlate with any of 4 the bacterial data in the euphotic zone. Without supporting data to the contrary, it seems that the above di!erences were likely due to di!erent water masses (Bugden, 1991) for which we failed to "nd relevant controlling variables. The generally low proportion of active bacteria (Table 2) may re#ect low concentrations of available substrate, consistent with low numbers of nanoplanktonic cells in deeper waters. We cannot, however, rule out the possibility that the protocol for ARCs, which was developed using water from the euphotic zone, may need to be modi"ed for bacterial populations from deeper waters (e.g., Grossmann, 1994). 4.5. General trends Bacterial biomass often exceeds phototrophic biomass seasonally in many marine systems, and may be the norm in oligotrophic regions of the open ocean (e.g. Dortch and Packard, 1989; Li et al., 1992,1993; Buck et al., 1996; Carlson et al., 1996). Excess bacterial C compared to phytoplankton C is referred to as an &inverse pyramid' (Fuhrman et al., 1989). A major contributor to heterotrophic biomass is always the high and relatively constant number of bacteria (108}109 cells l~1) that are found across di!erent aquatic systems (Hobbie, 1994). In summer, some of the Gulf stations seemed to correspond to the de"nition of an inverted trophic pyramid. Kalmbach et al. (1997) found that CTC positive bacteria, which were in the range of 2}4% of total DAPI-stained particles in drinking water, increased by about 10-fold in nutrientamended samples. This was still well below the number of total DAPI-stained particles. While we made no attempt to estimate total numbers of viable bacteria, it is reasonable to assume that the numbers of viable bacteria were less than total

C. Lovejoy et al. / Deep-Sea Research II 47 (2000) 461}487

481

DAPI-stained particles. The paradox of the inverse pyramid arises from the assumption that all bacterial C is productive and reliant on current photosynthetic productivity. BP and phytoplankton productivity may be easier to balance for a small and rapidly growing population of bacteria, somewhere between the underestimate provided by ARCs and the overestimate provided by DAPI bacteria. 4.6. Conceptual framework The seasonal di!erences in response of ARCs to temperature and negative correlations with nutrient levels suggest that other factors were in#uencing the overall growth and proportion of ARCs in the euphotic zone. It appears that the proportional abundance of di!erent trophic groups of nanoplankton strongly in#uenced bacterial biomass characteristics and productivity. The nanoplankton species composition and types of organisms capable of photosynthesis (phototrophs vs. mixotrophs) were di!erent in samples from spring and summer (Fig. 5d). The greatest di!erence was in the proportional occurrence of phototrophs. In spring phototrophs represented '50% of total nanoplankton in 4 of the 7 samples, while in summer they were never more than 25% (Fig. 5d). Our correlative relationships were consistent with the predictions of Rothhaupt (1996,1997) on the dominance of mixotrophs under lower nutrient conditions during summer. The growth characteristics of the in situ respiratory active bacterial populations were found to be an additional variable in food web complexity. Our results were consistent with recent theoretical suggestions on the rapid use of fresh DOM (Amon and Benner, 1996; Carlson and Ducklow, 1996), strong grazing pressure on bacteria (Wright and Co$n, 1984), and known bacterial growth characteristics (Eguchi et al., 1996). The main correlative relationships between the variables tested (Figs. a, c, 7a and b) are consistent with the existence of four trophic domains, separated by their protozoan and bacterial characteristics as described in the following paragraph. A conceptual framework that summarizes the above discussion is shown in Fig. 8. In that framework, the domains in summer samples where nutrients were low were predominately forced by the balance between PMixos and PHeteros. In the "rst case, Domain M, mixotrophs exerted the strongest in#uence on bacteria, characterized by high PARCs, low Al-ARCs, high PMixos, low PHeteros, and low PPhotos. Mixotrophs would in#uence bacteria by mechanisms (1}4) discussed above. Samples with the highest proportions of mixotrophs tended to occur in summer (Table 4). The second case, Domain H, corresponds to samples with proportionally larger numbers of heterotrophs. Grazing would have been high enough to crop active bacteria, but under conditions of low bacterial substrate, that is DOM would be in short supply since photosynthesis and #ow on DOM supply mechanisms are limited. This domain is characterized by low PARCs, low Al-ARCs, low PMixos, high PHeteros, and low PPhotos. Samples meeting these conditions also occurred for the most part in summer, but deeper in the water column under lower light conditions than for Domain M (Table 4) but still above the pycnocline with relatively low nutrient supply. The third case, Domain P#H, with forcing by higher PPhotos and PHeteros and a near absence of mixotrophs, occurred in some of the early spring samples under

482

C. Lovejoy et al. / Deep-Sea Research II 47 (2000) 461}487

conditions of high nutrients, low temperatures and weak strati"cation (Doyon and Ingram, 2000), which would result in low average light availability. This case implies high grazing and high bacterial substrate availability; low PARCs, high Al-ARCs, low PMixos, high PHeteros, and high PPhotos. The data set from the present study was not extensive enough to test the whole framework in Fig. 8, where a fourth potential domain of high PARCs and high Al-ARCs did not correspond to observed correlations. We speculate that this outcome would be found under conditions that would sustain a persistent algal bloom, Domain P"Phototrophs. That is, where nutrient supply and light were constant and nanoplankton and bacterial populations would be able to maintain both high standing stock and high growth rates. None of the relationships described for domains M, H and P#H, in Fig. 8 were apparent using DAPI estimates of total bacteria.

Acknowledgements This work was conducted as part of the Canadian JGOFS Programme. Financial support was provided by the Natural Sciences and Engineering Research Council (NSERC) of Canada, the Department of Fisheries and Oceans (DFO) Canada and by grants to GIROQ (Groupe interuniversitaire de recherches oceH anographiques du QueH bec) from NSERC and FCAR QueH bec. This is a contribution to the programmes of GIROQ and of the Ocean Productivity Division of the maurice Lamontagne Institute (DFO). We acknowledge the support and help of the O$cers and Crew of the CSS Hudson (DFO) and the Sir =ilfrid ¸aurier (Canadian Coast Guard). We are indebted to Alain GagneH , Mary-Lynn DubeH , and Natalie Simard for assistance in the laboratory and "eld as well as L. Guy Millette and Joel Wesson for physical data analysis and Fabrice MespleH for data compilation. We thank three anonymous reviewers for valuable criticisms and suggestions. We are also grateful to W.F. Vincent, UniversiteH Laval, for discussions and encouragement to C.L.

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