Ecology of bottom ice algae: II. Dynamics, distributions and productivity

Journal of Marine Systems, 2 (1991) 279-295

279

Elsevier Science Publishers B.V., Amsterdam

Ecology of bottom ice algae: II. Dynamics, distributions and productivity Glenn F. Cota a and Ralph E.H. Smith b a Graduate Program in Ecology, University of Tennessee, Knoxville, TN 37996-1610, USA b Department of Biology, University of Waterloo, Waterloo, Ont. N2L 3G1, Canada Received September 9, 1990; revised version accepted February 11, 1991

ABSTRACT

Cota, G.F. and Smith, R.E.H., 1991. Ecology of bottom ice algae: II. Dynamics, distributions and productivity. J. Mar. Syst., 2:279-295 Spring blooms of bottom ice algae are a common feature of landfast congelation ice in polar regions. Because ice algae are usually associated with a substrate, their population dynamics can be followed with considerable confidence. Although ice algal dynamics are closely related to irradiance, their dynamics and distributions are influenced by other abiotic and biotic factors. Ice algal abundance varies horizontally over all scales examined. Factors such as grazing and nutrient availability may contribute to local and geographic differences. Loss terms for most sea ice assemblages are largely unquantified. Ice algal biomass is most concentrated near the ice-water interface in spring. Environmental factors affecting ice algal abundance and productivity are considered here, emphasizing recent results from several well-studied sites. Biomass accumulation, growth rates and productivity have been documented for spring blooms of bottom interstitial and sub-ice assemblages. On an areal basis biomass accumulation in bottom ice assemblages can be comparable with planktonic systems. At low ambient temperatures and irradiances average specific growth rates ( < 0.25 d - 1) and production rates ( < 1 . 0 mg C mg Ch1-1 h -1) for ice algae are low. Current methods of measuring productivity are compared. Results are consistently low but variable with little systematic difference among them. At present, apparent differences in productivity between bottom ice assemblages in the Arctic and Antarctic, or among different antarctic assemblages, are so confounded by methodological and other sources of variability that no firm differences can be detected.

Introduction

There are a number of advantages associated with studies of ice algal assemblages compared to planktonic systems. Ice algae are virtually fixed space and they can be revisited repeatedly over several or more generations. They are also highly concentrated in thin layers and major environmental variables, including incident irradiance, temperature and salinity, are relatively constant (Cota et al., 1991). Their growth irradiance can also be manipulated in situ (Cota, 1985; Grossi et al., 1987). There is usually little contamination by heterotrophs or detritus (see Cota and Sullivan, 1990; Cota and Smith, 1991 and references cited 0924-7963/91/$03.50

© 1991 - Elsevier Science Publishers B.V.

therein), assemblages are often dominated by relatively few species (Grossi et al., 1984; Smith et al., 1989a) and losses due to grazing appear to be of minor importance (Grossi et al., 1987; Welch and Bergmann, 1989; Welch et al., 1991). Numerous disadvantages also exist. For example, their association with a solid and complex substrate presents serious challenges. There has been little specialized sampling or experimental equipment developed to study ice biota. They occupy an extremely compressed space which ideally requires miniaturized instrumentation (e.g. microprobes and microsamplers) capable of functioning in situ in both liquid and solid phases. Otherwise, we need to establish clearly that populations removed

280

from their environment (i.e. melted from their substrate) behave the same as those in situ with systematic comparisons. With proper care and the right tools studies of sea ice systems can be models for natural populations. Quantitative studies on ice algae span at least three decades, but there has been a proliferation of effort in the 1980's. The more recent research has been process-oriented and has included multi-year studies at several sites with intensive seasonal observations (Cota et al., 1991). These recent results are compared to examine apparent differences in ice algal dynamics, distributions and productivity within and between investigations. Although there are encouraging conceptual models that successfully describe ice algal dynamics over large areas, there are important exceptions or anomalies which suggest further refinement is required. The influence of environmental factors, other than irradiance, on ice algal distributions and dynamics have not been evaluated in most cases.

Dynamics, distributions and abiotic environment Biomass of microalgae is usually expressed in terms of chlorophyll because of its specificty for autotrophs and its central role in photosynthesis. However, alternate indices of biomass such as carbon, nitrogen or more specific biochemical fractions such as neutral lipids are also useful to track physiological status and are quite reliable in many sea ice systems because of the predominance of algal materials (Smith et al., 1989b). Bloom development in natural populations of ice algae can be followed relatively easily in cells associated with congelation ice and sampling methods are reasonably quantitative if care is taken in collection.

Seasonal development Biomass accumulation of bottom ice algae generally follows the seasonal trend in solar radiation, indicating the importance of irradiance in bloom development (Cota et al., 1991). Vernal blooms commence shortly after the return of sunlight, during the winter-spring transition and usually

G.F. C O T A A N D R.E.H. S M I T H

last until the onset of ice melt in late spring-early summer. Depending on geographic location, the blooms last for about 6-12 weeks and extended time-series observations are necessary to describe bloom development seasonally. However, because sea ice is still growing by accretion at its lower margin and frazil ice is sometimes incorporated into ice sheets, biomass accumulation may reflect in situ growth as well as material scavenged from the water column (Garrison et al., 1983; Cota et al., 1991). Contamination by scavenging complicates estimates of growth and annual production (Cota and Sullivan, 1990); it is most problematic in the Antarctic where frazil ice production is more common (Maykut, 1985). Similar to the arguments for bloom initiation in the plankton, there must be sufficient light available in early spring to sustain net ice algal photosynthesis and growth. Initially, irradiance levels are very low and discontinuous with a light-dark cycle. Several reports have suggested that ice algal blooms in the Arctic and Subarctic are not initiated until a critical irradiance &tit threshold of 2.3-9.3 # E m -2 s -1 is attained (e.g. Alexander et al., 1974; Clasby et al., 1976; H o m e r and Schrader, 1982; Gosselin et al., 1985; also see reviews by Homer, 1985 and Demers et al., 1986). However, most sub-ice measurements of transmitted irradiance I z (or E u) have been instantaneous observations near solar noon and they have been made below the algae without correction for absorption by the algae (e.g. Gosselin et al., 1985; Palmisano et al., 1987a). Such measurements of sub-ice irradiance are underestimates (Smith et al., 1988; Welch and Bergmann, 1989). A mean daily photon flux, which incorporates diel variability, would be more applicable to determine the onset of blooms, because compensation intensities I c of 0.2-2 /~E m -2 s -1 for ice algal photosynthesis appear to be well below these Icrit levels (Cota, 1985; Homer, 1985; Smith et al., 1987). Furthermore, photoadaptive indices Ik, which is the irradiance where photosynthesis starts to saturate, are commonly as low as 5-10 # E m 2 s - i (Cota, 1985; Homer, 1985; Palmisano et al., 1985b, 1987b; Smith et al., 1987, 1988; Cota and Home, 1989; Cota and Sullivan, 1990). Seasonal variation in solar flux is marked and undoubtedly plays a

281

ECOLOGY OF BOTTOM ICE ALGAE, lI

60 0

A) 1983

50

6 I / I / i

40 30

o

20

o

8

t

I 10 0

fE

•

B) 1984

5O 40 30 20 10-

~IlV"

0

120

,

i

I

I

c) 1985 /

1 O0 -

/

80-

cv/

60-

\ \

\~

4.0200 90

110

130

150

DAY NUMBER

Fig. 1. Seasonal development o f chlorop.hyll a in bottom

interstitial assemblages under various snow covers for three years near Resolute, N.W.T., Canada. Points represent SIPRE ice cores, normally taken in triplicate, and lines are plotted through means for each date. Snow depth classes were clear (0 cm, dotted line with small filled circles), low (2-5 cm, dashed line with open circles), moderate (8-13 cm, solid line with filled triangles) and heavy (20-25 cm, dashed line with open squares). (A) 1983 (Cota and Anning, unpubl.), (B) 1984 (from Cota et al., 1987) and (C) 1985 (from Smith et al., 1988).

dominant role in the development of the bloom, but the ice algae appear to be well adapted to the low ambient irradiances. Biomass accumulation is initiated first in areas of little or no snow and at least over the early part of the bloom growth is exponential. Rates of accumulation generally decline with increasingly heavy snow covers, so that areal chlorophyll concentrations are normally, but not always, an inverse function of snow depth (Fig. 1, also see Cota et al., 1987; Grossi et al., 1987; Smith et al., 1988; Welch and Bergmann, 1989). At high latitude sites there is little precipitation and snow depth tends be fairly constant over the bloom period, but in

southeastern Hudson Bay (Subarctic) the snow cover is much more variable during the bloom. Seasonal decreases in snow depth result in dramatic increases in irradiance (e.g. Gosselin et al., 1985; Michel et al., 1988). Bloom duration is 2-3 months at high latitude but only about 6 weeks at Subarctic sites (Cota et al., 1991). At lower latitudes blooms may start slightly later and develop more slowly because of shorter photoperiods, but they end sooner because of the onset of the melt is earlier (Gosselin et al., 1985; Michel et al., 1988). After the initial exponential growth phase, biomass levels peak or display a plateau and then finally a phase of decline. Biomass levels may also exhibit an oscillating phase with pulsed growth-decline cycles after populations become established, instead of a simple plateau phase. Only studies with replicated, high-frequency (ca. 1-3 day) sampling have successfully resolved oscillatory biomass changes (e.g. Horner and Schrader, 1982; Cota and Horne, 1989; Cota and Sullivan, 1990). Although the actual cause(s) remain unclear, the final demise of bottom ice algal blooms usually coincide with early stages of snow and ice ablation when the skeletal layer deteriorates and melt water lenses form. The decline can be abrupt, depending on prevailing climatic conditions and in particular air temperature. Seasonal biomass accumulations normally encompass 3-4 orders of magnitude over the course of the bloom, so that temporal variability (between dates) of biomass normally exceeds spatial (replicate cores from a small area with the same snow cover) and sampling or experimental variance (see below). Studies of vernal blooms with good temporal resolution have shown that large ( > 3-10 X), low frequency (4-8 days) fluctuations in biomass a n d / o r physiological rates are fairly common after the initial exponential growth phase. These types of results have been obtained for free-floating, sub-ice assemblages in the Subarctic (Rochet et al., 1986; Barlow et al., 1988) and for bottom interstitial assemblages in the high Arctic (Horner and Schrader 1982; Cota et al., 1987; Smith et al., 1987; Cota and Home, 1989) and Antarctic (Cota and Sullivan, 1990). Welch and Bergmann (1989; see their fig. 4) saw no evidence for late-season oscillations of biomass, but their

282

determinations were probably too infrequent (weekly) and variable (often 1 - 2 orders of magnitude within-date variance in May) to provide a good test. Significant low-frequency variation in biomass and physiological performance in established assemblages appears to be related to variable irradiance or nutrient fluxes ( H o m e r and Schrader, 1982; Gosselin et al., 1985; Cota et al., 1987; Smith et al., 1987; Cota and H o m e , 1989; Cota and Sullivan, 1990), but even more intensive efforts with higher frequency collections are needed to resolve interactions between environmental and biological variability. Horizontal distribution

Small scale of patchiness ice algal biomass under areas with known snow cover history has been examined at several locations. Replicate cores collected over a small area (ca. 0.5 m -2) have been used to characterize spatial variability; sampling and analytical errors are implicit in these estimates of natural variability. Alexander et al. (1974) found a mean chlorophyll concentration of 2.9 mg m -2 with a standard deviation of 1.02 mg m -2 for 6 SIPRE ice cores off Barrow, Alaska. Average coefficients of variation for means of triplicate S I P R E ice cores collected on a number of dates from low snow (0-5 cm) in McMurdo Sound were, respectively, 28.4%, 20.2% and 23.3% for chlorophyll, particulate organic carbon and nitrogen (Cota and Sullivan, 1990). In the high Arctic chlorophyll concentrations for triplicate cores from low (2-5 cm) snow cover yielded coefficients of variation averaging only 11.8% and within sample (date) variance for the bloom was only 2.1% (data from Cota and H o m e , 1989). As noted above, Welch and Bergmann (1989) reported highly variable results for biomass at low snow depth, but their data were collected from numerous sites with different ice thicknesses and the history of the snow cover was not well known. At a given point in time there is normally an inverse relationship between the depth of snow cover and chlorophyll standing crop in b o t t o m ice (Clasby et al., 1976; Sullivan et al., 1985; Welch and Bergmann, 1989). This trend is slightly more regular under stabilized snow cover near a snow

G.F. COTA AND R.E.H. SMITH SO

• UNSTABIIJZED o STABIUZED

~

4o

E ~' 30 ~ 2o

(.2

10

[]

10

2'0

3'0

40

SNOW DEPTH ( c m )

Fig. 2. Chlorophyll a as a function of snow depth for unstablized snow cover and stabilized snow from graded snow cover near a snow fence; samples were collected on June 4 and 6, 1983; respectively. Points represent SIPRE ice cores, which were replicated only at 0, 10 and 20 cm for the stablized series and lines are drawn through the means of triplicates.

fence than under randomly selected sites where the history of snow depth is not well known (Fig. 2). Snow depth-biomass surveys for several different years have been presented for the Barrow Strait region (Fig. 1; and see Cota et al., 1987; Smith et al., 1988; Welch and Bergmann, 1989). Similar results have been described from off northern Alaska (Alexander et al., 1974) and in McMurdo Sound (Sullivan et al., 1985). However, this inverse relation does not always hold. In, 1984 at Resolute, N.W.T. higher biomass levels were frequently found under moderate (ca. 8-13 cm) snow depths over the later stages of the bloom (Fig. 1B, also see fig. 6a of Cota et al., 1987, for carbon). Welch and Bergmann (1989; see their fig. 6C) also presented one late-season example where biomass was highest at moderate snow cover. These results m a y reflect the earlier demise of the populations under low snow cover or they may simply be anomalies. Snow-free ice represents a somewhat special case with regard to ice algal colonization and dynamics. Because ice has a lower albedo than snow, more light is transmitted through the ice sheet and the net heat flux may differ locally (Maykut, 1985). The influence of increased irradiance m a y cause several different results, depending on the environmental conditions and when it

ECOLOGY OF BOTTOM ICE ALGAE, I1

is increased. In late season, when bottom ice populations are established, removal of snow may result in a decrease in chlorophyll (Apollonio, 1965). In McMurdo Sound, Antarctica Grossi et al., (1987) found that both bottom interstitial and sub-ice frazil assemblages accumulated more rapidly and attained higher biomass levels earlier than populations under 5 cm of snow cover. However, the biomass of both populations also declined earlier. Both types of ice were thinnest in the region with no snow and the frazil ice layer melted well before that in adjacent snow-covered regions. By contrast, in the Canadian Arctic the biomass of bottom interstitial algae in areas kept free of snow cover may accumulate at about the same rate, but they often attain a lower maximum level and decline earlier (Fig. 1B, C). Moreover, biomass levels remained low during the latter part of the, 1985 bloom, even though populations from clear areas displayed the highest rates of photosynthesis (Cota and Home, 1989). Populations under clear areas apparently have the highest loss rates (Smith et al., 1988) and may absorb sufficient radiation to detach themselves. Sea ice, which is free of snow cover, is not common in the high Canadian Arctic (Welch and Bergmann, 1989; Cota, unpubl.), but does occur in certain windswept areas near the coast of Antarctica (C.W. Sullivan, pers. commun.). Mesoscale variability of ice algal biomass (over scales of tens of meters to kilometers) has been examined in a few studies. In a subpolar estuarine area Gosselin et al., (1986) concluded that salinity, through its influence on substrate (ice structure) availability, was most important over kilometer scales; however, snow-ice cover thickness, which limits growth irradiance, was most important in controlling patch size over tens of meters. Although there was considerable scatter, Welch and Bergmann's (1989) data for first-year ice from a fully marine environment indicate that over tens of kilometers the depth of snow cover is the principal determinant of biomass distribution, if the snow is relatively stable (i.e. little erosion or deposition) and the ice is of the same age and thickness. They also suggested that with equal snow cover older, thicker annual ice may have slightly greater biomass accumulations than newer

283

80 ~..

I

APRIL

MAY

I

70

7 E

60

~ so _~

4o >."T" n 30 0 ¢Y S 20 I ~ 10 1O0

120

140

160

DAY NUMBER

Fig. 3. Seasonal chlorophyll a development during, 1984 in Resolute Passage at five sites with low (2-5 cm) snow cover on a transect arranged along a depth gradient. Site numbers (and depths) were sequential with 1 (9 m) inshore, 2 (15 m), 3 (24 m), 4 (50 m) and 5 (90 rn) offshore.

and thinner ice because of earlier colonization of the older ice and a longer growth period. Additional controls, such as grazing (Smith et al., 1988; Welch and Bergmann, 1989; Grainger and Hsiao, 1990; Pike and Welch, 1990) or nutrient supply, may also contribute to variations in biomass accumulation in some cases. Figure 3 shows chlorophyll development for the spring of 1984 at five sites with low snow cover (2-5 cm) in Resolute Passage on an inshore-offshore transect perpendicular to shore (Cota, unpubl.). The sampiing sites on this transect were almost equidistant along a gradual gradient of water depth ranging from about 9 m nearshore to 90 m offshore. Shallow, inshore sites 1-3 (_< 25 m) always had less algal biomass than the deeper offshore locations 4 and 5 at comparable times. Surveys along this transect with a video camera also revealed that macrofaunal amphipod densities declined from about 100 animals m -2 inshore to 1 m -2 offshore. The inverse trend in ice algal biomass vs. amphipod abundance along this transect may, in part, reflect the grazing impact of amphipods, but we can not rule other possible factors which were not evaluated such as differences in algal species composition, meiofaunal abundance and nutrient fluxes. We do know that hydrographic structure and nutrient gradients differed between sites 3 and 5 (Cota et al., 1987). In this same general area Welch and colleagues have fc~und that amphipod

284

abundance is negatively correlated with depth (Pike and Welch, 1990) and ice algal biomass (Welch and Bergmann, 1989). In Frobisher Bay (Canadian Subarctic) Grainger and Hsiao (1990) have suggested that meiofaunal grazers may consume a large portion of ice algal productivity. Although the abundance of animals associated with sea ice has been documented in several studies, grazing rates in sea-ice systems are largely unknown. Other loss terms such as erosion and sinking are also poorly known. Biomass levels in land-fast sea ice appear to show substantial interannual and regional variability, but over larger scales the variance is difficult to assess because there are very few directly comparable observations. Interannual, environmental and methodological discrepancies between studies confound interpretations of regional differences. Numerous compilations of ice algal biomass from a variety of polar and subpolar sites are available (e.g. Horner, 1985; Demers et al., 1986; Smith et al., 1988), but many of these observations have been collected by different sampling methods, over a short period of time and represent different stages of blooms. Hence, they must be compared with caution. Multi-year seasonal studies have been conducted in several locations and these data sets are more suitable for characterizing regional and interannual variability of biomass. Although interannual variability in the maximum biomass at a particular location can be substantial, geographical variance appears to be at least comparable in magnitude (Clasby et al., 1976; Gosselin et al., 1985, 1986, 1990a; Smith et al., 1988; Welch and Bergmann, 1989; Cota and Sullivan, 1990). Chlorophyll concentrations in land-fast ice may surpass 100-300 mg m -2 at high latitude in areas with high nutrient availability, but at lower latitudes and in pack ice accumulations rarely exceed 25-30 mg m -2 (Palmisano and Sullivan, 1983; Demers et al., 1986; Smith et al., 1988; Welch and Bergmann, 1989; Dieckmann, pers. commun. Off northern Alaska biomass levels in land-fast bottom ice normally peak at only 20-30 mg Chl m -2 (Alexander et al., 1974; Clasby et al., 1976; Horner and Schrader, 1982). At several subarctic sites maximum biomass levels are usually less than 30

G.F. COTA AND R.E.H. SMITH

mg Chl m -2 (Hsiao 1980; Gosselin et al., 1985; Michel et al., 1988); in estuarine waters of southeastern Hudson Bay low salinity appears to reduce biomass and species composition (Poulin et al., 1983; Gosselin et al., 1986). Peak values of algal biomass under low snow cover in the Barrow Strait region range from about 20 to over 300 mg Chl m -2 (Figs. 1 and 3; also see Cota et al., 1987; Smith et al., 1988; Welch and Bergmann, 1989). Some of the year to year variability in these Barrow Strait studies may be related to site differences (see above), but we can not fully explain these differences. In analogous bottom interstitial assemblages from McMurdo Sound, Antarctica, Cota and Sullivan (1990) reported high levels of biomass (180 mg Chl m 2) for 1985 which were similar to observations from 1980 and 1981 (Palmisano and Sullivan, 1983; Sullivan et al., 1985), but they were an order of magnitude higher than concentrations found in 1982 when there was a thick ( > 1 m) frazil (platelet) ice layer (Grossi et al., 1987). Depending on the degree of consolidation, density and thickness, a frazil ice layer should retard nutrient fluxes from the water column to the congelation ice (reduced mixing and competitive utilization of nutrients by frazil ice algae) and thus limit the development of bottom ice algae. S.T. Kottmeier (pers. commun.) has suggested that there may be an inverse relationship between biomass accumulation in bottom interstitial and subice frazil assemblages. Numerous hypotheses have been advanced to explain ice algal biomass distributions in space and time, but irradiance is most commonly thought to be the dominant factor. For bottom interstitial assemblages in the Canadian Arctic and Subarctic it appears that biomass accumulation can be predicted over wide areas with snow depth, which has the largest influence on irradiance, and cumulative incident irradiance since the return of light in late winter (Welch and Bergmann, 1989; Welch et al., 1991). This approach is promising because these relationships explained about 60-80% of the observed variability in chlorophyll near Resolute, N.W.T., Canada for, 1985 and, 1986; addition of nitrate or silicate concentration in surface waters to the model had little affect on the r 2 values ( < 0.02). However, our 1984 results for low snow

285

ECOLOGY OF BOTTOM ICE ALGAE, II

sites (Fig. 3) would appear to be an exception to their model. At other high latitude sites in the Arctic (i.e. 70 ° N vs. 74 ° N), however, much lower maximum levels of biomass ( < 30 mg Chl m - 2 ) are typical in shallow waters off northern Alaska (Alexander et al., 1974; Horner and Schrader, 1982). These much lower maximum biomass levels were found in shallow water but under similar environmental conditions of snow depth, irradiance, ice thickness, nutrient concentrations and dates or season (same phase of bloom development). Therefore, local, geographical and interannual differences appear to be marked and can not be fully explained by current conceptual models based on irradiance. Moreover, in contrast to previous subpolar studies in southeastern Hudson Bay, Welch et al. (1991) found relatively high ( > 100 mg Chl m -2) maximum biomass levels in northwestern Hudson Bay at sites where mean nitrate concentrations in the water column were > 6 /~M. Their previous "Resolute model" (Welch and Bergmann, 1989) seriously overestimated biomass for sites with lower nitrate concentrations in this subarctic study and amphipod abundance explained only an additional 3% of the variance in biomass. These results led them to hypothesize that, for regions with full seawater (nonestuarine) and "adequate" dissolved inorganic nitrogen, maximum biomass was largely a function of the flux of dissolved inorganic nitrogen to the ice-water interface, which they suggested should be proportional to mean water column nitrate concentration. Other studies indicate that nutrient limitation may be common for ice algal blooms (Gosselin et al., 1985, 1990; Cota et al., 1987; Cota and Sullivan, 1990), particularly during the later stages of spring blooms. Taken together, these results suggest that such irradiance models are most applicable to the early exponential phase of blooms before biomass approaches maximal levels; self-shading and limited nutrient supply may both be important then. Factors such as latitude (e.g. seasonal duration, sun angle, photoperiod), local climate (e.g. snow cover, temperature), grazing, other loss terms (respiration, sinking), water depth (e.g. accessibility for benthic microalgae and grazers), nutrient availability (i.e. concentration and flux), hydro-

graphic regime (e.g. stratification, salinity, currents) and ice type (e.g. crystalline structure, sediment load) may all influence biomass accumulation. Much more work is needed to clarify the relative importance of these environmental factors and their interactive effects over the course of blooms. Vertical distributions There has been relatively little work on finescale vertical distributions of ice algal populations, although the distribution of cells has important ecological implications such as resource availability for the algae and accessibility to grazers. Ice algal assemblages may occur at all levels (e.g. surface, interior and bottom assemblages) in sea ice and have been reviewed recently (Horner, 1985; Horner et al., 1988). However, most observations on surface and interior assemblages are descriptive with poor temporal and spatial resolution. At most high latitude sites algae associated with landfast annual ice in spring are most concentrated in the lower few centimeters of " b o t t o m ice" (Homer, 1985; Horner et al., 1988; Welch and Bergmann, 1989; Smith et al., 1990). Although a few cells are scattered throughout sea ice, there is little direct evidence to indicate that populations, which are well removed from the interface and the moderating influence(s) of seawater, are actively growing (Cota et al., 1991). The vertical gradients of major physico-chemical factors through the annual ice sheet (1-2.5 m) are relatively well understood (Maykut, 1985; Cota et al., 1987, 1991) and it is known that distinct taxonomic groups may occur in the ice at different times or depths throughout annual ice sheets (Hoshiai, 1985; Hsiao, 1980). However, knowledge of the microenvironment(s) of the algae is still very limited with few direct observations of physico-chemical gradients within the thin layers of bottom ice. With a relatively coarse resolution of 5 cm, Grossi and Sullivan (1985) showed that the taxonomic composition of algae varied throughout the 20 cm thick bottom ice assemblage in McMurdo Sound, consistent with a speciesspecific response to vertically-varying growth conditions or seasonal succession. Such vertically

286

G.F. COTA A N D R . E H . SMITH

stratified species composition may additionally reflect the history of colonization of the ice as it grew, as Demers et al. (1984) concluded in their study of annual sea ice in the Gulf of St. Lawrence. Incorporation of algal cells scavenged from the water colunm may also contribute to depth-dependent changes in species composition (Garrison et al., 1983). Throughout the high arctic locations studied to date the overwhelming majority of the algal biomass in spring is restricted to a layer 1 or 2 cm in thickness (Clasby et al., 1976; Homer and Schrader, 1982; Cota et al., 1987; Welch and Bergmann, 1989; Smith et al., 1990). The bottom interstitial assemblage in the Antarctic is largely confined to a layer < 5 cm (SooHoo et al., 1987; Cota and Sullivan, 1990), but in some cases there may also be a sub-ice frazil assemblage which is 0.2-2,0 m thick (Grossi et al., 1987). Possible biological and physico-chemical gradients through this layer have not been reported. In southeastern Hudson Bay, bottom interstitial algae are also highly concentrated in the lower few cm (Poulin et al., 1983), but there is also an unattached sub-ice population, floating free at the ice-water interface (Michel et al., 1988) in a layer about 2 cm thick

NOON IRRADIANCE (,~mol phofons.m -2. s-1 ) 10 ,

5 J

60

15 ,

(L. Lengendre and M. Gosselin, pers. commun.). In the high Arctic attached sub-ice strand assemblages usually occur much later in the growth season than interstitial communities (Apollonio, 1985; Homer et al., 1988), but they may co-occur in spring with bottom interstitial assemblages in the Antarctic (McConville and Wetherbee, 1983; Homer et al., 1988). Despite the compressed vertical distribution, layers of bottom interstitial algae contain large amounts of biomass and generate steep gradients in physico-chemical conditions (Fig. 4). These gradients evolve seasonally because they are subject to density-dependent changes in biomass and ice accretion (Smith et al., 1990). During early spring, the ice sheet grows at rates of about 0.5-1.5 cm d -] (Cota et al., 1987; Welch and Bergmann, 1989; Cota and Sullivan, 1990). Nevertheless, most of the biomass remains at or near the ice-water interface and increases several orders of magnitude over the course of the bloom. Smith et al., (1990) have shown that arctic ice algae maintained peak concentrations in the bottom 1 cm while the ice sheet grew by 20 cm or more. The motility of these ice algal populations, dominated by colonial

PHOSPHATE, SILICATE CONC. (MICROMOLAR) 10 i

20

20 i

30 t

40 E

50

50

\

< hJ 40

', 0 Qf h-

30

~ '"',

Si05~

E

E Z

20

-r

10

0 5

I0

1,5

20

25

.30

CHLOROPHYLLa CONCENTRATION (mgChla. 1-1)

I O0

200

300

400

NITRATE CONCENTRATION (MICROMOLAR)

Fig. 4. Schematic vertical profiles of chlorophyll a, light and inorganic nutrients through bottom interstitial algal assemblages in the Canadian high arctic. Shown are median values for 7 profiles collected at or near the peak of the algal bloom (200 to 250 mg m - 2 of chlorophyll a) in land-fast annual sea ice near Resolute, N.W.T. during May, 1987.

ECOLOGY

O F B O T T O M I C E A L G A E , 11

pennates, has not been studied. The mechanisms, cues and rates involved in these movements are likely to be critical in controlling ice algal dynamics in many locations. Similarly, it is not known how unattached sub-ice assemblages manage to remain floating near the interface for weeks (L. Legendre, pers. commun.). The vertical structure of light quantity and quality is strongly influenced by the algal biomass itself and is thus an important eco-physiological factor. Light attenuation through layers of bottom ice algae can exceed 90% when biomass levels are near their seasonal maxima in areas of high algal abundance (Palmisano et al., 1987a, Smith et al., 1988; Welch and Bergmann, 1989). The spectral quality of the light can also be heavily modified by algal pigments, from predominantly blue under ice uncolonized by algae to predominantly green under heavily colonized ice (Maykut and Grenfell, 1975; Maykut, 1985; Palmisano et al., 1987a; SooHoo et al., 1987). Sub-ice frazil (brash or platelet) assemblages, living below the bottom interstitial (congelation) algae in McMurdo Sound, Antarctica in a relatively green light environment, display enhanced blue-green absorption compared to the congelation ice algae (SooHoo et al., 1987). Such differences in absorption, consistent with adaptation to altered light spectra, might also be expected through the bottom interstitial assemblages themselves, but have yet to be reported. Inorganic nutrients have also been shown to form steep gradients through bottom-ice communities in the high Arctic (Fig. 4) and may do so wherever similarly concentrated algal communities develop (Smith et al., 1990). Much, if not most, of the inorganic N and P measured in the lower 2 cm of ice in the Arctic is probably derived from intracellular stores of the algae (Cota et al., 1990; Smith et al., 1990). N and P reach phenomenally high concentrations in arctic bottom ice (up to 400 and 70 /~M respectively), reflecting the ability of algal cells to store excess N and P. In contrast, Si is usually not enriched to the same degree in bottom ice compared to underlying seawater and its vertical gradients through the algal layer are neither so strong nor so closely correlated with chlorophyll concentrations (Cota et al., 1990; Smith et al., 1990). The pattern of Si distribution

287

probably reflects the fact that excess soluble Si cannot be stored in the same manner. As a result, at times, Si may limit ice algal productivity (Cota and Horne, 1989; Cota and Sullivan 1990; Gosselin et al., 1990). The principal source of nutrients for bottom ice algae associated with annual ice sheets is the underlying water column (Cota et al., 1987, 1991; Demers et al., 1989; Cota and Sullivan, 1990), so we may expect gradients of nutrient availability and status from the ice-water interface upwards, as suggested by the fine-scale profiles seen in the high Arctic (Smith et al., 1990). Thus, over a spatial scale of a few cm, bottom-ice algae will frequently encounter strong and opposing gradients of light and nutrient availability. A major difficulty with the foregoing nutrient observations is that they pertain only to the bulk composition of melted ice sections, which may have lost varying amounts of their interstitial water in the process of sampling. Such concentrations are at best proportional to those actually existing in the microenvironment of the cells. Analyses of interstitial waters are difficult and will require in situ microsamplers capable of obtaining undisturbed pore waters. Near Barrow, Alaska inorganic nitrogen concentrations in waters from the bottom 2 cm of diver-collected ice cores were 2-10 times greater than seawater beneath the ice and concentrations increased with algal biomass, suggesting these algae were also pooling nitrogenous nutrients (Clasby et al., 1976). It is important to pursue such measurements further and to devise better means of measuring the expected strong vertical structure of chemical concentrations in the algal microenvironment. Dissolved organic carbon (DOC) concentration and composition, is an almost untouched aspect of the algal environment despite suggestions that some form of heterotrophy may be important to the ice algae (e.g. Palmisano and Sullivan, 1985). In the high Arctic DOC concentrations in bottom ice algal communities appear to be elevated, compared with typical concentrations in seawater of around 1.0 mg C 1-1 or less. Apollonio (1980) reported DOC levels of 2.2-6.6 mg C 1-1 at relatively low (0.12-27.1 /~g Chl a 1-1) chlorophyll concentrations and we have found 4.7-5.4 mg C 1-1 in bottom few centimeters of melted ice

288

at moderate (ca. 50 mg Chl a m -2) biomass levels (Cota, unpubl.). Dissolved free amino acids (micromolar range), can be up to several orders of magnitude more concentrated in ice than in the underlying seawater or in weakly colonized ice in the Arctic (S. Macko, pers. commun.) and in the Antarctic (D. Manahan, pers. commun.). The amino acids, like glucose, are actively cycled (Smith and Clement, 1990; Smith unpubl.). Their apparent association with the algae suggests that vertical gradients would be found through the bottom ice layer, but no measurements have been reported. Because of possible osmotic shock when ice cores are melted (with or without seawater) and other disturbances (e.g. light, temperature and pressure changes) associated with sampling, distributions of soluble compounds should be interpreted with caution. Clearly, steep gradients in a variety of important growth conditions are to be expected through highly concentrated ice algal assemblages. As yet, there are few published data to describe the consequent physiological responses of the algae. Bottom ice algae in the high Arctic display increasing POC : PON and POC : Chl a ratios over small (cm) vertical scales (Smith et al., 1990), but no information on species composition or other compositional aspects of the community has been published relevant to such fine scales. At the same site vertical variations in photosynthesis-irradiance relationships through the lower 20 mm of ice were small (Smith and Herman, 1991), but nothing is known of other physiological rate processes or at other locations.

Photosynthesis and productivity Photosynthetic rates for ice algae have been determined by a variety of simulated in situ and in situ methods. Artificial light-gradient incubators have also become increasingly popular, providing a third type of production estimate. Because of varying methods, rates are not often directly comparable among locations or investigators. The great majority of measurements to date has been made on bottom ice assemblages, but these include at least three physically distinct types as described above. Here we compare the various types of

G.F. C O T A A N D R . E . H . S M I T H

productivity measurements that have been applied to bottom ice assemblages. Our purpose is to identify systematic differences among methods and between different assemblages.

Methodology The structure of ice algal habitats makes in situ methods for measuring primary productivity difficult. True in situ methods require experimental incubation of the study population entirely in situ, with any retrieval to the surface occurring only after the incubation is concluded. The advantages i of in situ methods include the avoidance of algal exposure to surface light or temperature and minimal disturbance of the community (Clasby et al., 1973), natural quantity and quality of light (cf. Palmisano et al., 1987a; SooHoo et al., 1987) and natural nutrient and chemical regime. The major disadvantages of in situ methods are inconvenience (e.g. limited replication, expensive equipment development or time intensive with divers) and that production may be underestimated because of inadequate tracer diffusion. If the tracer, whether bicarbonate or dissolved oxygen, does not quickly and completely equilibrate between the interstitial fluid bathing the ice algal cells and the adjacent seawater then it cannot participate fully during the experiment (Booth, 1984; Grossi et al., 1987; Smith and Herman 1991). Alternatively, some tracer may diffuse too far in the ice and be lost altogether (Homer and Schrader, 1982). Other potential problems are associated with mechanical or chemical disturbances during deployment, incomplete recovery of sample and tracer, measuring the irradiance dose received and inadequate nutrient fluxes from water column in a static environment. Very few studies have used true in situ methods (Clasby et al., 1973, 1976; Homer and Schrader, 1982; Smith and Herman, 1991). Modified in situ methods carry out the experimental incubation in situ but require prior retrieval to the surface for tracer addition and possibly other manipulations. The sample may be collected under the ice by divers (McConville et al., 1985; Palmisano et al., 1985a,b; Kottmeier and Sullivan, 1988) or from the surface using coring augers (Booth, 1984; Grossi et al., 1987; Hsiao, 1988). If

289

E CO L O GY OF BOTTOM ICE ALGAE, II

Smith and Herman, 1991). The convenience of the artificial incubator approach has lead to its predominance in studies of ice algal primary production processes.

cores are extracted from the ice sheet and taken to the surface, then the hydrostatic equilibrium between interstitial water and surrounding media is unavoidably altered, with drainage and subsequent replacement of interstitial water and disruption of the natural chemical microenvironment. Modified in situ methods thus can offer the advantage of a natural light regime (only if there is no overlying algal layer) but none of the other advantages of in situ methods. Tracer diffusion may not be a problem in modified in situ methods, depending on the physical structure of the sample (e.g., congelation vs. frazil ice layers in McMurdo Sound, Palmisano et al., 1985 a,b). Systematic comparisons between in situ and other methods have been conducted recently (Smith and Herman, 1991). A popular alternative to in situ methods, based on a procedure first used with phytoplankton, entails small volume (1-2 ml), short-term ( < 1 h), incubations of samples in an artificial light-gradient incubator (Lewis and Smith, 1983; Cota, 1985; Palmisano et al., 1985b, Lewis et al., 1985; Bates and Cota, 1986; Barlow et al., 1988; Michel et al., 1988; Smith et al., 1988; Cota and Horne, 1989; Cota and Sullivan 1990;

Comparative productivity of bottom ice assemblages Production rates based on the incubator approach successfully account for the observed seasonal biomass increase in both arctic and antarctic bottom ice communities (Smith et al., 1988; Cota and Sullivan, 1990) with, if anything, an apparent excess of production over the observed accumulation of biomass. Thus it does not seem likely that incubator methods grossly underestimate the actual in situ rates. The only direct, published comparison of incubator production estimates with in situ production rates (as opposed to biomass accumulation) indicated that the incubator rates were much higher during the declining phase of a bottom interstitial bloom in the Arctic (Smith and Herman, 1991). No such comparisons have been published for earlier bloom stages or at other polar locations.

1.0 Jr~

DAVIS STRAIT

i 0.8

_C

RESOLUTE PSOE '88

/ / /

7 _C

BEAUFORT SEA

[]

RESOLUTE PSOE '87

0.6

(.9 C~

E o C~

D~3

0.4

+~

[]

[]

[]

E rn n

0.2 / ~_~

o

0

+ +

....... %

,

10 20 50 40 IRRADIANCE ( / ~ m o l p h o f o n s . m - 2 . s - 1 )

50

Fig. 5. Biomass-specific primary production rates (pa) of arctic bottom interstitial algae versus simultaneous irradiance as determined by in situ measurementsat various sites (symbols)or by experimentsin light-gradient incubators (lines). The upper and lower lines represent the approximateextremesobservedin incubator experimentsover three years of observation at a high arctic site near Resolute, N.W.T., while the central solid line is the median response.

290

G.F. COTA

[ []

3.0 I

R.E.H. SMITH

production estimates, it is difficult to see a consistent difference, although the in situ results seem curiously low. Photosynthetic parameters for bottom interstitial algae undergo at least five-fold variations on the scale of days to weeks (Gosselin et al., 1985; Cota and Horne, 1989; Cota and Sullivan, 1990), and maximal rates exceed 1.0 mg G mg Chl-1 h-1 (see table 2 of Cota and Smith, 1991). Even the highest in situ production rate (1.86 mg C mg Chl - t h - l ; Alexander et al., 1974) that we are aware of for arctic ice algae is thus encompassed by the known range of incubator rates. It is impossible with available data to determine which estimate, in situ or incubator, is the more accurate. In situ production rates are consistent with the simultaneous accumulation of algal biomass in bottom ice at a site near Resolute in the Canadian Arctic (Smith, unpubl.), as were incubator estimates in a different year of comparison at the same site (Smith et al., 1988) and in the Antarctic (Cota and Sullivan, 1990). Therefore, both methods appear to meet the minimum criterion of reliability. The situation appears different in the Antarctic, but is complicated by the different methods that

We have attempted here to broaden the comparative base by plotting all available in situ production estimates against irradiance for comparison with the rates expected from incubator experiments (e.g., Fig. 5). Four studies provided suitable paired values for in situ production per biomass and irradiance for arctic ice algae, of which three ( H o m e r and Schrader, 1982; Smith and Herman, 1991 plus unpublished data) used true in situ methods. The in situ production rates were generally low and with little, if any, relationship to irradiance (Fig. 5). The modified in situ study (Davis Strait; Booth, 1984) did not appear to yield production rates systematically different from the true in situ results at other sites, considering the variability within individual studies. For comparison, production-irradiance relationships have been determined with incubators for four years of observations at an arctic site near Resolute (Cota, 1985; Smith et al., 1987, 1988; Cota and Home, 1989; Smith and Herman, 1990; Smith, unpubl.) giving a reasonable idea of the variability that might be expected at one site at least. Figure 5 shows the approximate upper and lower limits for P - I curves, as well as the mean response over the four years. Given the variability in both types of

3.5

AND

INTERFACE

A

PLATELET

0

CONGELATION

c

2.5 Io I cO

2.0

E (.D 1.5

A

En

£

m

[]

1.o cl

[]

A 0.5

0

]

0

.---

5

[]

[] . .-

. ..................

•

[] ~

..

... . .......... LI

I0 IRRADIANCE

CONGELATION .....................

.

.

PLATELET

' 15 (/_zmol

2'0

' 25

photons.m

30'

35~

180

-2-s -I)

Fig. 6. Biomass-specificprimary production rates (pa) of antarctic ice algae versus simultaneous irradiance as determined by in situ measurements (symbols)or by experimentsin light-gradient incubators. The lines for platelet (sub-ice frazil) and congelation(bottom interstitial) algae represent the approximate upper limits to the values reported from incubator experimentsfor those communities.

291

ECOLOGY OF BOTTOM ICE ALGAE, II

have been preferentially applied to different types of ice communities. Much higher in situ rates have been reported from the Antarctic and they are better related to irradiance (Fig. 6), but all have been obtained with modified methods and most pertain to sub-ice frazil (platelet) assemblages. Frazil ice assemblages have no counterpart in the Arctic, but similar bottom interstitial (congelation) assemblages are common to both polar regions. Photosynthetic parameters (Palmisano et al., 1985b; Palmisano et al., 1987b; Cota and Sullivan, 1990) for bottom interstitial assemblages indicate relatively low production rates compared to those in situ (Fig. 6), but rates up to 1.4 mg C mg Chl-1 h-1 have been obtained (see Table 2 of Cota and Smith, 1991). However, there are prob-

ably too few in situ measurements on bottom interstitial assemblages to conclude that they are really discrepant with the incubator results. P - I parameters for sub-ice frazil (platelet) algae are somewhat higher than for bottom interstitial algae (Fig. 6), but the modified in situ rates are substantially higher yet. Again, the number of points available for comparison is probably too limited to permit firm conclusions, although the direction o f the discrepancy is consistent with arctic data. Direct comparisons, controlling for the influence of site, season and ice type appear to be warranted to explore the apparent discrepancies further. Attention will need to be given to the substantial temporal variability in photosynthesis-irradiance relationships (Cota and Sullivan, 1990).

TABLE 1 Growth rates for ice algae from various sites. Type indicates: I, interval increase in biomass indice; R, regression slope; C, laC-carbon fixation; and N, l~N-nitrogen uptake Site

Mean snow cover (cm)

Mean growth rate (d - a)

Type

Source

Chukchi Sea, 1972 Chukchi Sea, 1973 Beaufort Sea, 1980 Barrow Strait, 1983 Resolute Passage, 1984 Resolute Passage, 1985 Resolute Passage, 1985 Resolute Passage, 1985 Resolute Passage, 1986 Barrow Strait, 1985 Barrow Strait, 1986 Barrow Strait, 1986 Barrow Strait, 1986 M c M u r d o Sound, 1981 M c M u r d o Sound, 1981 M c M u r d o Sound, 1981 M c M u r d o Sound, 1981 M c M u r d o Sound, 1982 M c M u r d o Sound, 1982 M c M u r d o Sound, 1982 M c M u r d o Sound, 1982 M c M u r d o Sound, 1982 M c M u r d o Sound, 1985 M c M u r d o Sound, 1985 M c M u r d o Sound, 1985

< 5 < 5 < 5 2-26 0-25 < 5 < 5 < 5 < 5 < 5 4.8 10.1 21.4 7 70 7 70 0 5 10 25 100 < 5 < 5 < 5

0.13 0.16 0.26 0.25 0.08 0.08 0.23 0.18 0.45 0.15 0.08 0.06 0.08 0.10 < 0.00 0.01-0.09 0.00-0.03 0.29 0.10 0.09 0.07 0.03 0.11-0.20 0.13 0.02

I I I I I I C N N R R R R I I C C I I I I I I C N

Alexander et al., 1974 Alexander et al., 1974 H o m e r and Schrader, 1982 Cota et al., 1987 Cota et al., 1987 Cota and H o m e , 1989 Cota and H o m e , 1989 Harrison et al., 1990 Harrison et al., 1990 Welch and Bergmann, 1989 Welch and Bergmann, 1989 Welch and Bergmann, 1989 Welch and Bergmann, 1989 Grossi et al., 1984 Grossi et al., 1984 Sullivan et al., 1985 Sullivan et al., 1985 * Grossi et al., 1987 Grossi et al., 1987 Grossi et al., 1987 Grossi et al., 1987 Grossi et al., 1987 Cota and Sullivan, 1990 * * Cota and Sullivan, 1990 Cota and Sullivan, unpubl.

*

* value of 0.27 should presumably be 0.027 in Sullivan et al., (1985). * range for means of chlorophyll a, particulate organic nitrogen and carbon.

292

G.F. COTA AND R.E.H. SMITH

algae appear to have lower growth rates based on biomass changes, even though carbon fixation rates are normally greatest for these populations (Smith et al., 1988; Cota and Horne, 1989). Algae under clear patches may not attain high levels of biomass, because they alter their habitat and have the highest rates of export (Apollonio, 1965; Smith et al., 1988; Cota and Horne, 1989; Lewis and Cota, unpubl.).

Growth rates

Algal growth rates derived from the observed dynamics (e.g., cell abundance or biomass changes) of populations in situ are less ambiguous, in most senses, than instantaneous tracer measurements. Exponential growth models have been fitted to biomass data with regression methods (e.g., Smith et al., 198%; Welch and Bergmann, 1989) and fixed interval calculations (e.g., Grossi et al., 1984, 1987; Cota et al., 1987) to estimate specific in situ growth rates/~ (d 1). These two approaches differ primarily in that the latter has usually been applied to shorter time intervals (days), whereas the regression approach yields average estimates for longer periods (weeks to months) representing much of the bloom. Hence, higher frequency variability in growth rates can not be resolved with the regression estimates. Instantaneous growth rates have also been computed with 14C- or 15Nincorporation rates and reasonable agreement has been found between instantaneous and interval growth rate estimates (Cota and Sullivan 1990; Harrison et al., 1990). Ice algal growth rates based on biomass changes, whether based on changes in standing stocks or on carbon (14C) and nitrogen (15N) incorporation, are low. They span a range from about 0.01 to 0.50 d - l , but most values are below 0.25 d-1 (Table 1). Ice algal growth rates are quite comparable with average values for polar phytoplankton (e.g. Smith and Sakshaug, 1990), especially if comparisons are made at the same low temperature and irradiance. Eppley's (1972) relationship for temperature-dependent growth predicts a maximum microalgal growth rate of about 0.52 d -1 at the ambient temperatures of - 1 . 8 to - 1 . 9 ° C and mean values for either ice algae or polar phytoplankton rarely exceed this limit. Over the first month of the algal bloom in McMurdo Sound, Grossi et al., (1987) found that growth rates were inversely related to snow depth (Table 1). This is largely consistent with our results from stable snow fields in the Arctic, except that there is considerable variability from year to year and populations from cleared areas do not conform to this trend (Fig. 1; Smith et al., 1988; Welch and Bergmann, 1989). In areas kept free of snow the

C o n c l u s i o n s

The distribution and dynamics of bottom ice algae most commonly indicate a limiting role for light, with greater and and more rapid biomass accumulation at higher light levels under thin snow cover. Biomass can also be depressed by excessive light levels and may be influenced by other factors such as grazing or nutrient supply. Spatial variability, both vertical and horizontal, is still an understudied aspect of ice algal assemblages and hinders further interpretation of distributions and dynamics. Conceptual models based on irradiance explain only part of the observed variability in biomass. The microenvironment of ice biota is poorly characterized, but probably changes dramatically over small ( m m - c m ) vertical spatial scales in bottom and sub-ice assemblages. The effects of such steep physico-chemical gradients in the algal microenvironment need to be assessed. Productivity and growth rates for ice algae are low, consistent with the low temperature and irradiance levels of their habitats. Direct measurements of productivity sometimes depend strongly on the methods used, especially on the choice of in situ versus other methods. However, there is also a wide variation in production rates over time and among sites when measured with a single technique. The discrepancies among production methods will probably not be resolved until the related uncertainties about the algal microenvironment and spatial variability of the assemblages are addressed. Important outstanding questions include: are ice algae motile and if so, what factors control their movements? what are the magnitude of grazing and other loss terms? -

-

ECOLOGY OF BOTTOMICE ALGAE, 11 -

what

293

f a c t o r s , b e s i d e s i r r a d i a n c e , i n f l u e n c e ice

algal distributions and dynamics? -

d o ice a l g a l a s s e m b l a g e s a d a p t stratified microenvironment, ferences in species and

to their highly

so there are dif-

activities along these

steep gradients? Acknowledgments This work was supported by the United States (National Science Foundation Research) and Canada gineering

Research

Canadian

Foundation).

W.G.

Harrison,

and Office of Naval

(National Science and EnCouncil

and

the

Donner

We thank our colleagues

R. H o m e r ,

L. L e g e n d r e

a n d T.

Platt for insightful discussion.

References Alexander, V., Homer, R. and Clasby, R.C., 1974. Metabolism of arctic sea ice organisms. Inst. Mar. Sci. Rep., R74-4. Univ. Alaska, Fairbanks, 120 pp. Apollonio, S., 1965. Chlorophyll in arctic sea ice. Arctic, 18: 118-122. Apollonio, S., 1980. Microflora of Arctic Sea ice. Nat. Geogr. Soc. Res. Rep., 12: 13-20. Apollonio, S., 1985. Arctic marine phototrophic systems: functions of sea ice stabilization. Arctic, 38: 167-173. Barlow, R.G., Gosselin, M., Legendre, L., Therriault, J-C. Demers, S. Mantoura, R.F.C. and Llewellyn, C.A., 1988. Photoadaptive strategies in sea-ice microalgae. Mar. Ecol. Prog. Ser., 45: 145-52. Bates, S.S. and Cota, G.F., 1986. Fluorescence induction and photosynthetic responses of Arctic ice algae to sample treatment and salinity. J. Phycol., 22: 421-429. Booth, J.A,, 1984. The epontic algal community of the ice edge zone and its significance to the Davis Strait ecosystem. Arctic, 37: 234-243. Clasby, R.C., Alexander, V. and Homer, R., 1976. Primary productivity of sea ice algae. In: D.W. Hood and D.C. Burrell (Editors), Assessment of the Arctic Marine Environment: Selected Topics. Inst. Mar. Sci., Univ. Alaska, Fairbanks, pp. 289-304. Ciasby, R.C., Homer, R. and Alexander, V., 1973. An in situ method for measuring primary productivity of Arctic Sea ice algae. J. Fish. Res. Board Can., 30: 835-838. Cota, G.F., 1985. Photoadaptation of high arctic ice algae. Nature, 315: 219-222. Cota, G.F., Anning, J.L., Harris, L.R., Harrison, W.G. and Smith, R.E.H., 1990. The impact of ice algae on inorganic nutrients in seawater and sea ice in Barrow Strait, NWT, Canada during spring. Can. J. Fish. Aquat. Sci., 47: 14021415. Cota, G.F. and Home, E.P.W., 1989. Physical control of ice

algal production in the high Arctic. Mar. Ecol. Prog. Ser., 52: 111-121. Cota, G.F., Legendre, L., Gosselin, M. and lngram, R.G., 1991. Ecology of bottom ice algae. 1. Environmental controls and variability. J. Mar. Syst., 2:257-277 Cota, G.F., Prinsenberg, S.J., Bennett, E.B., Loder, J.W., Lewis, M.R., Anning, J.L., Watson, N.H.F. and Harris, L.R., 1987. Nutrient flux during extended blooms of arctic ice algae. J. Geophys. Res., 92(C): 1951-1962. Cota, G.F. and Smith, R.E.H., 1991. Ecology of bottom ice algae. II1. Comparative physiology. J. Mar. Syst, 2: 297-315. Cota, G.F. and Sullivan, C.W., 1990. Photoadaptation, growth and production of bottom ice algae in the Antarctic. J. Phycol., 26: 399-411. Demers, S., Legendre, L., Maestrini, S.Y., Rochet, M. and Ingram, R.G., 1989. Nitrogenous nutrition of sea-ice microalgae. Polar Biol., 9: 377-383. Demers, S., Legendre, L., Therriault, J.C. and lngram, R.G., 1986. Biological production at the ice-water ergocline. In: J.C.J. Nihoul (Editor), Marine Interfaces Ecohydrodynamics. Elsevier, Amsterdam, pp. 31-54. Demers, S., Therriault, J.C. and Descolas-Gros, C., 1984. Biomasse et composition sprcifique de la microflore des glaces saisonnirres: influences de la lumirre et de la vitesse de congrlation. Mar. Biol., 78: 185-191. Eppley, R.W., 1972. Temperature and phytoplankton growth in the sea. Fish. Bull., 70: 1063-85. Garrison, D.L., Ackley, S.F. and Buck, K.R., 1983. A physical mechanism for establishing algal populations in frazil ice. Nature, 306: 363-365. Gosselin, M.L, Legendre, E.J., Demers, S. and Ingram, R.G., 1985. Reponses of sea-ice microalgae to climatic and fortnightly tidal energy inputs (Manitounuk Sound, Hudson Bay). Can. J. Fish. Aquat. Sci., 42: 999-1006. Gosselin, M.L., Legendre, L., Therriault, J-C., Demers, S. and Rochet, M., 1986. Physical control of the horizontal patchiness of sea ice microalgae. Mar. Ecol. Prog. Ser., 29: 289-298. Gosselin, M., Legendre, L., Therriault, J-C. and Demers, S., 1990. Light and nutrient limitation of sea-ice microalgae. J. Phycol., 26: 220-232. Grainger, E.H. and Hsiao, S.I.C., 1990. Trophic relationships of the sea ice meiofauna in Frobisher Bay, Arctic Canada. Polar Biol., 10: 283-292. Grossi, S.M., Kottmeier, S.T., Moe, R.L., Taylor, G.T. and Sullivan, C.W., 1987. Sea ice microbiol communities. VI. Growth and primary production in bottom ice under graded snow cover. Mar. Ecol. Prog. Ser., 35: 153-64. Grossi, S.M., Kottmeier, S.T. and Sullivan, C.W., 1984. Sea ice microbial communities. III. Seasonal abundance of microalgae and associated bacteria, McMurdo Sound, Antarctica. Microb. Ecol., 10: 231-42. Grossi, S.McG. and Sullivan, C.W., 1985. Sea ice microbial communities. V. The vertical zonation of diatoms in an antarctic fast ice community. J. Phycol., 21: 401-409. Harrison, W.G., Cota, G.F. and Smith, R.E.H., 1990. Nitrogen

294 utilization in ice algal communities of Barrow Strait, NWT, Canada. Mar. Ecol. Prog. Ser., 67: 275-283. Horner, R.A., 1985. Ecology of sea ice microalgae. In: R.A. Homer (Editor), Sea Ice Biota. CRC Press, Cincinnati, pp. 83-103. Homer, R.A. and Schrader, G.C., 1982. Relative contributions of ice algae, phytoplankton and benthic micralgae to primary production in nearshore regions of the Beaufort Sea. Arctic, 35: 485-503. Homer, R.A., Syvertsen, E.E., Thomas, D.P. and Lange, C., 1988. Proposed terminology and reporting units for sea ice algal assemblages. Polar Biol., 8: 249-253. Hoshiai, T., 1985. Autumnal proliferation of ice-algae in Antarctic sea-ice. In: W.R. Siegfried, P.R. Condy and R.M. Laws (Editors), Antarctic Nutrient Cycles and Food Webs. Springer, Berlin, pp. 89-92. Hsiao, S.I.C., 1980. Quantitative composition, distribution, community structure and standing stock of sea ice microalgae in the Canadian Arctic. Arctic, 33: 768-793. Hsiao, S.I.C., 1988. Spatial and seasonal variations in primary production of sea ice microalgae and phytoplankton in Frobisher Bay, Arctic Canada. Mar. Ecol. Prog. Ser., 44: 275-285. Kottmeier, S.T. and Sullivan, C.W., 1988. Sea ice microbial communities. IX. Effects of temperature and salinity on rates of metabloism and growth of autotrophs and heterotrophs. Polar Biol. 8: 293-304. Lewis, M.R. and Cota, G.F., 1991. Radiation absorption by ice algae: Influences on the heat budget of Arctic sea ice. J. Geophys. Res. (in review). Lewis, M.R., Warnock, R.E., Irwin, B. and Platt, T., 1985. Measuring photosynthetic action spectra of natural phytoplankton populations. J. Phycol., 21: 310-315. Lewis, M.R. and Smith. J.C., 1983. A small volume, short-incubation-time method for measurement of photosynthesis as a function of incident irradiance. Mar. Ecol. Prog. Ser., 13:99-102. Maykut, G.A., 1985. The ice environment. In: R.A. Homer (Editor), Sea Ice Biota. CRC Press, Cincinnati, pp. 22-82. Maykut, G.A. and Grenfell, T.C., 1975. The spectral distribution of light beneath first-year sea ice in the Arctic Ocean. Limnol. Oceanogr., 20: 554-563. McConville, M.J. and Wetherbee, R., 1983. The bottom-ice microalgal community from annual ice in the inshore waters of east Antarctica. J. Phycol., 19: 431-439. Michel, C., Legendre, L., Demers, S. and Therriault, J-C., 1988. Photoadaptation of sea-ice microalgae in springtime: photosynthesis and carboxylating enzymes. Mar. Ecol. Prog. Ser., 50: 177-185. Palmisano, A.C. and Sullivan, C.W., 1985. Pathways of photosynthetic carbon assimilation in sea ice microalgae from McMurdo Sound, Antarctica. Limnol. Oceanogr., 30: 674678. Palmisano, A.C., Kottmeier, S.T., Moe, R.L. and Sullivan, C.W., 1985a. Sea ice microbial communities. IV. The effect of light perturbation on microalgae at the ice-seawater

G.F. COTA AND R.E.H. SMITH interface in McMurdo Sound, Antarctica. Mar. Ecol. Prog. Ser., 21: 37-45. Palmisano, A.C., SooHoo, J.B., Moe, R.L. and Sullivan, C.W., 1987a. Sea ice microbial communities. VII. Changes in under-ice spectral irradiance during the development of Antarctic sea ice microalgal communities. Mar. Ecol. Prog. Ser., 35: 165-173. Palmisano, A.C., SooHoo, J.B. and Sullivan, C.W., 1985b. Photosynthesis-irradiance relationships in sea ice microalgae from McMurdo Sound, Antarctica. J. Phycol., 21:341346. Palmisano, A.C., SooHoo, J.B. and Sullivan, C.W., 1987b. Effects of four environmental variables on photosynthesisirradiance relationships in Antarctic sea-ice microalgae. Mar. Biol. (Berl.), 94: 299-306. Palmisano, A.C. and Sullivan, C.W., 1983. Sea ice microbial communities (SIMCO) I. Distribution, abundance and primary production of ice microalgae in McMurdo Sound, Antarctica in, 1980. Polar Biol., 2: 171-177. Pike, D.G. and Welch. H.E., 1990. Spatial and temporal distribution of sub-ice macrofauna in the Barrow Strait area, Northwest Territories. Can J. Fish. Aquat. Sci., 47: 81-91. Platt, T., Gallegos, C.L. and Harrison, W.G., 1980. Photoinhibition of photosynthesis in natural assemblages of marine phytoplankton. J. Mar. Res., 38: 687-701. Poulin, M., Cardinal, A. and Legendre, L., 1983. Reponse d'une communaute de diatomees de glace a un gradient de salintie (baie d'Hudson). Mar. Biol., 76:, 191-202. Rochet, M., Legendre, L. and Demers, S., 1986. Photosynthetic and pigment responses of sea-ice microalgae to changes in light intensity and quality. J. Exp. Mar. Biol. Ecol., 101: 211-26. Smith, R.E.H., Anning, J., Clement, P. and Cota, G., 1988. Abundance and production of ice algae in Resolute Passage, Canadian Arctic. Mar. Ecol. Prog. Ser., 48: 251-63. Smith, R.E.H. and Clement, P., 1990. Heterotrophic activity and bacterial productivity in assemblages of microbes from sea ice in the high arctic. Polar Biol., 10: 351-357. Smith, R.E.H., Clement, P. and Cota, G.F., 1989a. Population dynamics of bacteria in Arctic Sea ice. Microb. Ecol., 17: 63-76. Smith, R.E.H., Clement, P., Cota, G.F. and Li, W.K.W., 1987. Intracellular photosynthate allocation and the control of arctic marine ice algal production. J. Phycol., 23: 124-132. Smith, R.E.H., Clement, P. and Head, E., 1989b. Biosynthesis and photosynthate allocation patterns of arctic ice algae. Limnol. Oceanogr., 34: 591-605. Smith, R.E.H., Harrison, W.G., Harris, L.R. and Herman, A.W., 1990. Vertical fine structure of particulate matter and nutrients in sea ice of the high Arctic. Can. J. Fish. Aquat. Sci., 47: 1348-1355. Smith, R.E.H. and Herman, A.W., 1991. Productivity of sea-ice algae: in situ vs incubator methods. J. Mar. Syst., 2: 97-110. Smith, W.O., Jr. and Sakshaug, E. 1990. Polar Phytoplankton. In: W.O. Smith, Jr. (Editor), Polar Oceanography Part B. Academic Press, San Diego, pp. 477-525.

ECOLOGY OF BOTTOMICE ALGAE. II SooHoo, J.B., Palmisano, A.C., Kottmeier, S.T., Lizotte, M.P., SooHoo, S.L. and Sulhvan, C.W., 1987. Spectral light absorption and quantum yield of photosynthesis in sea ice microalgae and a bloom of Phaeocystis pouchetii from McMurdo Sound, Ancarctica. Mar. Ecol. Prog. Ser., 39: 175-189. Sullivan, C.W., Palmisano, A.C., Kottmeier, S., Grossi, S.B. and Moe, R., 1985. The influence of light on growth and development of the sea-ice microbial community of McMurdo Sound. In: W.R. Siegfried, P.R. Condy and R.M.

295 Laws, (Editors), Antarctic Nutrient Cycles and Food Webs. Springer, Berlin, pp. 78-83. Welch, H.E. and Bergmann, M.A., 1989. The seasonal development of ice algae and its prediction from environmental factors near Resolute, N.W.T., Canada, Can. J. Fish. Aquat. Sci., 46: 1793-1804. Welch, H.E., Bergmann, M.A., Siferd, T.D. and Amarulik, P.S., 1991. The seasonal development of ice algae near Chesterfield Inlet, N.W.T. Canada. Can. J. Fish. Aquat. Sci. (in press).