Cell size and size-linked traits
The size of phytoplankton cells constrains many of their physiological rates (e.g. nutrient uptake and growth rates), biotic interactions (e.g. grazing) and behaviour within the fluid environment (e.g. sinking speed). Therefore, cell size plays a key role in determining the diversity and relative abundance of competing phytoplankton species, as well as the transfer of elements between the surface and deeper layers in the ocean and from phytoplankton to higher trophic levels (Smetacek 1985; Cushing 1989). Our approach to discussing phytoplankton community size structure is complementary to previous work (Finkel 2007; Finkel et al. 2010), but is biogeography-centric; we first ask how size structure varies in space, and then consider how size-linked functional traits help bring about the spatial variations in size structure.
Phytoplankton abundance (A; cells m−3) typically decreases with increasing cell volume (V; μm3), such that A = cVξ, where c is a constant and the scaling exponent ξ is approximately −1 but varies from roughly −2/3 to −5/3 (Cermeño et al. 2006; Finkel 2007; and references therein). Although small cells are generally more abundant than larger ones, the scaling exponent varies across environmental conditions. Compilations of in situ observations (e.g. Irigoien et al. 2004) and global satellite measurements (Uitz et al. 2006) indicate that smaller phytoplankton cells are generally present in a range of nutrient concentrations, whereas larger cells become more common under higher nutrient supply common in regions of upwelling or enhanced mixing. Using a global ocean model with a size-structured phytoplankton community, Ward et al. (2012) demonstrated that phytoplankton size spectra vary regionally, with large cells relatively rare in oligotrophic seas and relatively more common in areas of strong upwelling or in subpolar gyres (Fig. 2, points ‘A’ and ‘B’ respectively).
The co-regulation of phytoplankton populations by bottom-up (nutrient limitation) and top-down (predation) processes provides a compelling explanation for the maintenance of phytoplankton community size spectrum at a given location, and also for its global-scale variations (Armstrong 1994; Ward et al. 2012). Cell size influences a cell's uptake rate of dissolved nutrients by modifying the surface area available for uptake transporters and the diffusive flux of nutrients towards the cell (Aksnes & Egge 1991). Within taxonomic groups, smaller cells typically have higher scaled nutrient affinities (defined as the clearance rate at low nutrient concentrations, normalised by cell nutrient content) than do larger cells (Fig. 1), and therefore may maintain positive growth at lower nutrient concentrations than larger competitors (Edwards et al. 2012). In the subtropical gyres, which are characterised by consistent stratification and weak nutrient delivery to the surface, smaller phytoplankton cells are able to draw down ambient nutrient concentrations to critically low levels at which larger cells cannot survive, and the size spectra slope is steeply negative (Fig. 2, Point ‘A’).
In the subpolar gyres, coastal upwelling zones, and regions of enhanced turbulent mixing, nutrient delivery is greater (Fig. 2, Point ‘B’). The population of small phytoplankton cells increases in response to the additional nutrients, but is subject to intense grazing pressure by their predators, who themselves are relatively small and quick to respond to changes in prey density (Hansen et al. 1994, 1997). This top-down control keeps the smaller phytoplankton cells from consuming all available nutrients, and allows successively larger, less competitive size classes of phytoplankton to grow, each in turn grazed down by their successively larger, more slowly growing predators (Armstrong 1994; Ward et al. 2012). This mechanism is thought to underpin the positive correlation between total primary productivity or nutrients and average phytoplankton cell size, as well as the broadening of the cell size distribution with additional nutrients (Irigoien et al. 2004; Schartau et al. 2010). Certain taxonomic groups, such as the diatoms, have evolved to have higher growth and nutrient uptake rates than others (Edwards et al. 2012), and may thus modify the conceptual picture we have developed here.
Imprinted onto this mechanism may be other size-dependent factors that impact phytoplankton fitness, including light (see review by Finkel et al. 2010 for others). All else being equal, larger cells absorb fewer photons per pigment than smaller cells of the same shape, due to increased self-shading of pigment with increasing cell volume (Duysens 1956). As a result, larger phytoplankton cells tend to have lower intracellular pigment concentrations than smaller cells under any given irradiance regime, which should cause smaller cells to have a growth advantage under low light conditions that often occur in deep mixed layers in temperate and high latitude waters (Finkel et al. 2004). Alternatively, the high levels of self-shading caused by larger cell volume can be advantageous in stratified water columns when photon flux densities and ultra-violet light doses are high (Key et al. 2010). One goal for future work should be to quantify the relationship between light conditions and size spectra across the ocean, which will require disentangling the effects of light conditions from the effects of nutrient supply.
Various other size-dependent mechanisms may be important under certain conditions, including phytoplankton sinking and swimming speeds, the impact of turbulence on nutrient uptake, and the effect of fluctuating nutrient supplies (Kiørboe 2008). Recent studies have also argued that increasing temperature may reduce phytoplankton cell volume (e.g. Hilligsøe et al. 2011), although the mechanistic link remains unclear (Atkinson et al. 2003). We also note that many phytoplankton form aggregates of cells, such as diatom chains, that modify their effective sizes and thus their interaction with the physical environment and predators. The costs and benefits of aggregation are an area of active research (Pahlow et al. 1997). Lastly, the range of photosynthetic pigments deployed by phytoplankton determines, in part, their distribution and community structure (Stomp et al. 2004), and represents an important regulatory set of traits.
Observations suggest that as oligotrophic conditions expand, so too do ecosystems dominated by smaller phytoplankton (Irwin & Oliver 2009), and coupled climate and ecosystem models indicate that warmer, more stratified future oceans may favour smaller phytoplankton (Bopp et al. 2005). Similar shifts in phytoplankton size structure due to changing nutrient availability appear in the geological record (Finkel et al. 2007). The greater extent of oligotrophic seas may weaken the ocean's biological carbon pump, or its biologically mediated export of carbon from the surface layer to deeper waters (Falkowski et al. 1998). It should be stressed, however, that the complex and sometimes competing effects of temperature, nutrient availability, turbulence, ocean acidification, grazing and light on phytoplankton fitness remain to be fully quantified.
Diazotrophs are organisms that convert nitrogen gas from the atmosphere (N2) into bioavailable ammonia, providing a globally significant source of N to the ocean. Because of this ability to fix nitrogen and their distinct cellular elemental ratios (Quigg et al. 2011), or elemental stoichiometry, the distribution of N2-fixers influences oceanic N : P ratios (Weber & Deutsch 2012). Diazotrophs impact the structure and function of marine ecosystems in the current ocean, as well as on much longer timescales (Tyrrell 1999).
Diazotrophs include both photoautotrophic cyanobacteria (members of the phytoplankton) and heterotrophic bacteria. Among the cyanobacteria, both colonial (Trichodesmium) and unicellular species (Crocosphaera) contribute to N2-fixation (Capone et al. 1997). Some heterocystous filamentous cyanobacteria also occur as symbionts of other organisms, such as diatoms, and the widely distributed but poorly understood UCYN-A group appears to be photoheterotrophic and may occur as a symbiont (Zehr 2011). N2-fixation is also carried out by some heterotrophic γ-proteobacteria (Halm et al. 2012), but much less is known about their ecology and distribution. Although these diverse N2-fixers exhibit a range of functional traits, they all use the nitrogenase enzyme complex to catalyse the conversion of N2 gas into ammonia. Therefore, we consider the ability to fix N as an ecologically and biogeochemically important functional trait, and discuss the underlying causes of its spatial distribution.
Diazotrophs are most conspicuous in warm, oligotrophic waters from c. 30°S to 30°N, although there appears to be substantial variation between regions (Luo et al. 2012; Fig. 3). Observed N2-fixation rates are higher in the North than the South Atlantic and Pacific basins, and diazotrophs appear to be common in the Baltic and Mediterranean Seas. Different diazotrophs have distinct spatial and temporal distributions (Church et al. 2008), but in the following discussion we focus on the larger scale pattern of integrated diazotroph biomass and N2-fixation rates (Fig. 3).
Understanding what drives the large-scale biogeographical patterns of diazotrophs is challenging due to the fact that temperature, light and nutrients co-vary across latitude. Trichodesmium possess a high optimal temperature, a high light requirement and low susceptibility to photoinhibition (Capone et al. 1997), which may constrain their distribution to low latitudes. It has also been proposed that diazotrophs such as Trichodesmium and Crocosphaera are restricted to warm waters due to temperature-dependence of respiration and flux of O2, which inhibits nitrogenase (Staal et al. 2003).
Recent modelling studies suggest that the availability of N and Fe, in addition to temperature and light, regulate the global-scale distribution of diazotrophs, with the availability of phosphorus (P) playing an additional, regional regulatory role (Monteiro et al. 2010; Dutkiewicz et al. 2012). At higher latitudes with greater availability of bioavailable N, models show that diazotrophs are outcompeted by non-diazotrophs because of their relatively slow maximum specific growth rates, which may stem from the energetic cost of breaking the N2 gas triple bond (Monteiro et al. 2010). At lower latitudes, diazotroph distribution appears to be constrained by the relative availability of N and Fe. Because of their relatively high demand for Fe due to the Fe-rich nitrogenase enzyme complex, in a global model diazotrophs were numerous in the subtropical North Pacific, where Fe was relatively high but N was low, and rare in zones where both N and Fe were low (Dutkiewicz et al. 2012). These studies are supported by observations that show an inverse correlation between the abundance of nitrogenase reductase genes and nitrate concentrations in the Pacific (Church et al. 2008), but a positive correlation with Fe concentrations along the Atlantic Meridional Transect (AMT; Moore et al. 2009). An additional constraint on the distribution of diazotrophs is the bioavailability of P. For example, in low N and high dissolved Fe conditions in the tropical and subtropical North Atlantic, N2-fixation has been found to also closely track concentrations of bioavailable P (Sanudo-Wilhelmy et al. 2001). Diazotrophs have a high P requirement relative to non-diazotrophs (Quigg et al. 2011), and are thus sensitive to P limitation of growth.
These mechanisms indicate several potentially conflicting paths by which diazotroph distributions may shift under global environmental change. Rising temperatures and CO2 concentrations in the ocean surface may facilitate increased N2-fixation and/or growth rate of N2-fixers and expand their geographical distribution (Hutchins et al. 2007; Stal 2009). Changes in the hydrological cycle in a warmer climate may reduce the atmospheric deposition of Fe into the ocean and limit the range and abundance of diazotrophs (Berman-Frank et al. 2001). Although rising temperatures are expected to increase the extent of oligotrophy (Sarmiento et al. 2004), we have a poor understanding of how the supply ratio of N, P, and Fe will change. If changes in nutrient availability lead to increased P limitation, this may restrict N2-fixers due to their high P requirements. Alternatively, if N limitation is increased, N2-fixers may have a competitive advantage over non-N2-fixers and increase their dominance and range. Unravelling which, if any, of these possibilities may play out will require incorporation of diazotrophs with realistic physiology and nutrient requirements into trait-based plankton community models (e.g., Monteiro et al. 2010; Dutkiewicz et al. 2012) that are run with environmental forcing consistent with expected future changes. Although we have focussed on diazotrophs in particular, phytoplankton exhibit a range of N : P requirements, and this trait is likely to be crucial for interpreting how plankton communities respond to, and feed back on, global change (Finkel et al. 2010; Weber & Deutsch 2012).
Mixotrophs are organisms that combine both autotrophic and heterotrophic nutrition, and this blending may be a much more common strategy than previously imagined (Hansen 2011). This trait is particularly common among the dinoflagellates, but is found in a wide range of microbes (Hansen 2011). Mixotrophs have been shown to increase the efficiency of nutrient drawdown in aquatic systems (Tittel et al. 2003), and can account for much of the bacterial grazing in pelagic and coastal zones (Havskum & Riemann 1996; Zubkov & Tarran 2008). Despite their importance, there are no quantitative estimates of the global importance of mixotrophy with regard to primary production and nutrient cycling. Thus, improved understanding of mixotroph ecology and the resulting implications for marine food webs and biogeochemical cycles is an important goal.
Mixotrophy has the advantage of broadening the pool of available resources (Tittel et al. 2003), but there are also certain physiological ‘trade-offs’ associated with maintaining two trophic machineries. In comparison with obligate photoautotrophs such as diatoms, the dinoflagellates, many of whom are mixotrophic, are typically associated with slow maximum specific growth rates and a low affinity for inorganic nutrients (Edwards et al. 2012). In a similar fashion, growth and grazing rates in some mixotrophs have been shown to be slower than in similar, heterotrophic specialists (Jeong et al. 2010). Given these relatively uncompetitive traits, how is it that mixotrophs are able to coexist with, or even outcompete, their apparently superior competitors?
Competition between specialists and mixotrophic plankton can be thought of in terms of the principle of opportunity costs (Stephens & Krebs 1987). Strictly autotrophic and heterotrophic plankton are able to exploit certain resources more efficiently through specialisation, but to do so they reduce their resource opportunities. Mixotrophs increase their resource opportunities by consuming both inorganic and organic resources, but in doing so they are less efficient. In oligotrophic environments, where resources are relatively scarce, there is less advantage in specialisation. Mixotrophs are able to thrive in these regions (Havskum & Riemann 1996; Zubkov & Tarran 2008), because they are able to take advantage of both inorganic and organic resource encounters (Ward et al. 2011). Specialists, in contrast, gain an advantage in eutrophic conditions, where resources (either dissolved inorganic nutrients or prey) are so abundant that they can afford to be selective. Thus, it is conceivable that this oligotrophic niche for mixotrophs may expand poleward as stratification increases and nutrient delivery to the surface decreases under climate warming scenarios (Sarmiento et al. 2004).
Mixotrophic generalism can also be thought of as a ‘bet-hedging’ strategy, through which the mixotrophs experience less risk because they do not rely on just one resource (Stoecker 1998). In a changing environment, mixotrophs are able to bridge the gap between bloom periods, where inorganic resources are abundant, and post-bloom periods, where inorganic resources are scarce, prey are abundant, and production is driven by grazing and recycling of organic matter. This bet-hedging mechanism yields a succession of trophic strategies, from autotrophs, through mixotrophs, to heterotrophs, as has been observed in the North Atlantic Bloom Experiment (Sieracki et al. 1993) and Continuous Plankton Recorder data (Barton et al. 2013).
We currently have limited understanding of mixotroph biogeography, but there are at least three ways this uncertainty can be decreased. First, field studies should quantify mixotrophic distribution, but also prey ingestion and photosynthetic rates as a function of environmental conditions such as temperature, light, nutrients and prey availability. Second, knowledge of the distribution of mixotrophic taxa can be paired with laboratory and field-based estimates of the prevailing trophic strategy for each taxa to make predictions about the spatial and temporal distribution of mixotrophs in the ocean (Barton et al. 2013). Third, trait-based plankton community models that allow for a range of trophic strategies (Ward et al. 2011) should be implemented on a global scale and employed to quantify the affects of mixotrophy on marine food webs and biogeochemical cycles. In each approach, it should be recognised that organisms may acquire essential nutrients independently through different trophic pathways: photosynthesis, uptake of organic nutrients, assimilation of organic detritus, or grazing or predation on other living organisms. The traditional definition of plankton as either heterotrophs or autotrophs needs to be broadened to include such trophic plasticity. Ultimately, mixotrophs may be considered an important plankton group distinct from either phytoplankton or zooplankton in terms of their functional traits, ecology and biogeochemical functions.