Defining Planktonic Protist Functional Groups On

Accepted Manuscript

Title: Deﬁning Planktonic Protist Functional Groups on Mechanisms for Energy and Nutrient Acquisition; Incorporation of Diverse Mixotrophic Strategies

Author: Aditee Mitra Kevin J. Flynn Urban Tillmann John A. Raven David Caron Diane K. Stoecker Fabrice Not Per J. Hansen Gustaaf Hallegraeff Robert Sanders Susanne Wilken George McManus Mathew Johnson Paraskevi Pitta Selina Vage˚ Terje Berge Albert Calbet Frede Thingstad Hae Jin Jeong JoAnn Burkholder Patricia M Glibert Edna Graneli´ Veronica Lundgren

PII: S1434-4610(16)00004-3 DOI: http://dx.doi.org/doi:10.1016/j.protis.2016.01.003 Reference: PROTIS 25518

To appear in:

Received date: 23-3-2015 Revised date: 8-1-2016 Accepted date: 19-1-2016

Please cite this article as: Mitra, A., Flynn, K.J., Tillmann, U., Raven, J.A., Caron, D., Stoecker, D.K., Not, F., Hansen, P.J., Hallegraeff, G., Sanders, R., Wilken, S., McManus, G., Johnson, M., Pitta, P., Vage,˚ S., Berge, T., Calbet, A., Thingstad, F., Jeong, H.J., Burkholder, J.A., Glibert, P.M., Graneli,´ E., Lundgren, V.,Deﬁning Planktonic Protist Functional Groups on Mechanisms for Energy and Nutrient Acquisition; Incorporation of Diverse Mixotrophic Strategies, Protist (2016), http://dx.doi.org/10.1016/j.protis.2016.01.003

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1 ORIGINAL PAPER

1 2 2 3 3 Defining Planktonic Protist Functional Groups on Mechanisms for Energy 4 5 6 4 and Nutrient Acquisition; Incorporation of Diverse Mixotrophic Strategies 7 5 8 9 6 Aditee Mitraa,1, Kevin J. Flynna, Urban Tillmannb, John A. Ravenc, David Carond, Diane K. 10 e f g h i j 11 7 Stoecker , Fabrice Not , Per J. Hansen , Gustaaf Hallegraeff , Robert Sanders , Susanne Wilken , 12 k l m n g o 13 8 George McManus , Mathew Johnson , Paraskevi Pitta , Selina Våge , Terje Berge , Albert Calbet , 14 n p q e r 15 9 Frede Thingstad , Hae Jin Jeong , JoAnn Burkholder , Patricia M Glibert , Edna Granéli , 1610 and Veronica Lundgrens 17 1811 19 2012 aCollege of Science, Swansea University, Swansea SA2 8PP, United Kingdom 21 b 2213 Alfred Wegener Institute, Am Handelshafen 12, D-27570 Bremerhaven, Germany 23 c 2414 Division of Plant Sciences, University of Dundee at the James Hutton Institute, Invergowrie, 25 Dundee DD2 5DA, United Kingdom (permanent address) and Plant Functional Biology and 2615 2716 Climate Change Cluster, University of Technology Sydney, Ultimo, NSW 2007, Australia 28 2917 dDepartment of Biological Sciences, University of Southern California, 3616 Trousdale Parkway, 30 3118 Los Angeles, CA 90089-0371 32 e 3319 University of Maryland Center for Environmental Science, Horn Point Laboratory, P.O. Box 775, 34 3520 Cambridge MD 21613, USA 36 f 21 Sorbonne Universités, Université Pierre et Marie Curie - Paris 06, UMR 7144, Station Biologique 37 3822 de Roscoff, CS90074, 29688 Roscoff Cedex, France and also CNRS, UMR 7144, Laboratoire 39 4023 Adaptation et Diversité en Milieu Marin, Place Georges Teissier, CS90074, 29688 Roscoff cedex, 41 4224 France. 43 g 4425 Centre for Ocean Life, Marine Biological Section, University of Copenhagen, Strandpromenaden 45 4626 5, DK-3000 Helsingør, Denmark 4727 hInstitute for Marine and Antarctic Studies, University of Tasmania, Private Bag 129, Hobart, 48 Accepted Manuscript 4928 Tasmania 7001, Australia 50 5129 iDepartment of Biology, Temple University, Philadelphia PA 19122 USA 52 j 5330 Monterey Bay Aquarium Research Institute, Moss Landing, CA 95039, USA 54 k 5531 Marine Sciences, University of Connecticut, 1080 Shennecossett Rd, Groton CT USA 06340 56 l 5732 Biology Department, Woods Hole Oceanographic Institution, Woods Hole MA 02543 USA 5833 mInstitute of Oceanography, Hellenic Centre for Marine Research, P.O. Box 2214, 71003 59 6034 Heraklion, Crete, Greece 61 62 Page 1 of 23 63

64 Page 1 of 28 65 35 nDepartment of Biology and Hjort Centre for Marine Ecosystem Dynamics, University of Bergen, 36 P.O. Box 7803, 5020 Bergen, Norway 1 237 oInstitut de Ciències del Mar, CSIC, Ps. Marítim de la Barceloneta, 37-49, 08003 Barcelona, Spain. 3 438 pSchool of Earth and Environmental Sciences, College of Natural Sciences, Seoul National 5 639 University, Seoul 151-747, Republic of Korea 7 q 840 Center for Applied Aquatic Ecology, North Carolina State University, Raleigh, NC 27606 USA 9 rAquatic Ecology, Biology Institute, Lund University, Box 118, 22100 Lund, Sweden, and also at 1041 1142 Florida Gulf Coast University, Kapnick Center, Naples, Florida 34112 USA 12 1343 sDepartment of Biology and Environmental Sciences, Centre for Ecology and Evolution in 14 1544 Microbial Model Systems, Linnaeus University, SE-39231 Kalmar, Sweden 16 1745 18 19 2046 21 22 2347 Submitted March 23, 2015; Accepted January 3, 2016 24 25 2648 Monitoring Editor: Ulrich Sommer 27 28 2949 30 3150 Running title: Defining Planktonic Protist Functional Groups 32 33 3451 35 36 1 3752 Corresponding author; e-mail [email protected] (A. Mitra). 38 39 40 41 42 43 44 45 46 47 48 Accepted Manuscript 49 50 51 52 53 54 55 56 57 58 59 60 61 62 Page 2 of 23 63

64 Page 2 of 28 65 53 Arranging organisms into functional groups aids ecological research by grouping organisms 54 (irrespective of phylogenetic origin) that interact with environmental factors in similar ways. 1 255 Planktonic protists traditionally have been split between photoautotrophic “phytoplankton” 3 456 and phagotrophic “microzooplankton”. However, there is a growing recognition of the 5 657 importance of mixotrophy in euphotic aquatic systems, where many protists often combine 7 858 photoautotrophic and phagotrophic modes of nutrition. Such organisms do not align with the 9 1059 traditional dichotomy of phytoplankton and microzooplankton. To reflect this understanding, 1160 we propose a new functional grouping of planktonic protists in an eco-physiological context: 12 1361 (i) phagoheterotrophs lacking phototrophic capacity, (ii) photoautotrophs lacking 14 1562 phagotrophic capacity, (iii) constitutive mixotrophs (CMs) as phagotrophs with an inherent 16 1763 capacity for phototrophy, and (iv) non-constitutive mixotrophs (NCMs) that acquire their 18 1964 phototrophic capacity by ingesting specific (SNCM) or general non-specific (GNCM) prey. 20 For the first time, we incorporate these functional groups within a foodweb structure and 2165 2266 show, using model outputs, that there is scope for significant changes in trophic dynamics 23 2467 depending on the protist functional type description. Accordingly, to better reflect the role of 25 2668 mixotrophy, we recommend that as important tools for explanatory and predictive research, 27 2869 aquatic food-web and biogeochemical models need to redefine the protist groups within their 29 3070 structures. 31 3271 33 34 3572 Key words: Plankton functional types (PFTs); phagotroph; phototroph; mixotroph; phytoplankton; 36 3773 microzooplankton. 38 39 4074 41 4275 43 44 45 46 47 48 Accepted Manuscript 49 50 51 52 53 54 55 56 57 58 59 60 61 62 Page 3 of 23 63

64 Page 3 of 28 65 76 Functional Types in Ecology

177 In ecology, organism functional categories are often more useful than taxonomic groupings because 2 378 they can be based on ecological function, rather than evolutionary history. Functional group 4 579 descriptions are commonly used by scientists to partition the numerous taxonomic classes into 6 780 categories more relevant to ecology. The concept provides “a non-phylogenetic classification 8 981 leading to a grouping of organisms that respond in a similar way to a syndrome of environmental 1082 factors” (Gitay and Noble 1997). Functional group (also referred to as “functional type”) 11 1283 classifications thus aid our understanding of ecological processes with applications from fieldwork 13 1484 through to conceptual and mathematical studies. 15 1685 The functional group approach has been embraced by researchers working on different 17 1886 organisms across biomes. Especially when applied to microorganisms, linking an ecological 19 2087 function to specific members of a community is often challenging, as individual contributions to 2188 rate processes are difficult if not impossible to measure in situ. Supplementing the classical 22 2389 plant/animal type dichotomy, one of the earliest categorizations of plankton groups was based on 24 2590 size, driven by practical approaches to plankton sampling (Lohmann 1911; Schütt 1892), as well as 26 2791 conforming to typical predator-prey allometries of 10:1 (Azam et al. 1983). Various later freshwater 28 2992 and marine studies used such allometric classifications (Sieburth et al. 1978), specifically focussing 30 on phytoplankton species (Aiken et al. 2007; Reynolds et al. 2002). Kruk et al. (2010) found easily 3193 3294 identifiable morphological differences among phytoplankton to correlate with functional properties 33 3495 and proposed six functional groups; these were based on volume, maximum linear dimension, 35 3696 surface area, and the presence of mucilage, ﬂagella, gas vesicles, heterocytes or siliceous 37 3897 exoskeletal structures. Further to morphological characteristics, Weithoff (2003) used resource 39 4098 acquisition capabilities, such as phagotrophy (bacterivory), nitrogen fixation, and silica usage, to 4199 divide phytoplankton into six functional groups. 42 43100 In the context of conceptual and mathematical studies of marine ecology, protist functional 44 45101 groups are typically divided simply into “phytoplankton” (phototrophs) and “microzooplankton” 46 47102 (phagotrophs); the former typically include photoautotrophs while the latter represent 48 103 phagoheterotrophs Accepted(e.g., Baretta et al. 1995; Fasham etManuscript al. 1990; Plagányi 2007). However, there is 49 50 51104 now an increasing recognition that many “phytoplankton” and photic-zone “microzooplankton” are, 52105 in fact, mixotrophic. A wide range of phytoplankton ingest prey while various microzooplankton 53 54106 retain chloroplasts from their prey or harbour photosynthetic endosymbionts and thus contribute to 55 56107 primary production. Furthermore, many species, when engaging in mixotrophic activity, can attain 57 58108 higher growth than when in photoautotrophic or phagoheterotrophic mode alone (e.g., Adolf et al. 59 60109 2008; Burkholder et al. 2008; Glibert et al. 2009; Jeong et al. 2010). Thus mixotrophy, defined here 61 62 Page 4 of 23 63

64 Page 4 of 28 65 110 as phototrophy plus phagotrophy, is an inherent capability of many planktonic protists rather than 111 being the exception that it was previously considered to be (see reviews by Flynn et al. 2013 and 1 1122 references therein; Stoecker et al. 2009; Jeong et al. 2010). 3 1134 Mixotrophic protists are ubiquitous, and commonly have been found to be dominant in 5 1146 freshwater as well as marine systems from the tropics to the poles (e.g., Jeong et al. 2010; Sanders 7 1158 1991; Stoecker et al. 2009; Zubkov and Tarran 2008). Yet, most plankton functional type 9 classifications make minimal reference to these mixotrophs. Pratt and Cairns (1985), in their protist- 10116 11117 centric functional groupings, emphasised strategies to acquire resources. They, thus, divided protists 12 13118 into six functional groups – (1) photo-autotrophic primary producers with no distinction made 14 15119 between those which can employ a level of heterotrophy, (2) bacti- and detritivores feeding on 16 17120 bacteria and/or detritus, (3) saprotrophs consuming dissolved material, (4) algivores primarily 18 19121 feeding on algae, (5) nonselective omnivores feeding non-selectively on algae, detritus and bacteria, 20 122 and, (6) raptorial predators feeding primarily on other protozoa and organisms from the higher 21 22123 trophic levels. There is no explicit mention of mixotrophy. In contrast, Jones (1997) and Stoecker 23 24124 (1998) specifically focussed on how groups of protists combine phototrophy and phagotrophy to 25 26125 support growth (Fig. 1). Jones (1997) primarily focussed on the mixotrophic flagellates, proposing 27 28126 four functional groups according to their photosynthetic and heterotrophic capabilities. Stoecker’s 29 30127 (1998) classification included a wider group of protists. In addition to flagellates, Stoecker (1998) 31128 accounted for ciliates, sarcodines and protists with algal symbionts – groups which had not been 32 33129 included in the studies of Pratt and Cairns (1985) and Jones (1997). 34 35130 It is now clear that the time has come to abandon the premise that protists are either "little 36 37131 plants" or "little animals", to move away from the misplaced dichotomy of “phytoplankton” versus 38 39132 “microzooplankton” (Flynn et al. 2013). How can we best reclassify them for ecological studies? 40 41133 Depending on the character of interest, there is scope to create many types of functional groups. For 42134 the application of functional classifications to mathematical models, however, a simpler approach is 43 44135 required in order to constrain computational loads while prioritising functionality to 45 46136 biogeochemistry and/or to trophic (food web) dynamics. Based on our understanding of aquatic 47 48137 ecology, coupled withAccepted improved understanding of howManuscript protists have evolved, we suggest that a 49 50138 reappraisal is required of the definition of functional group descriptions for planktonic protists, now 51 52139 explicitly including mixotrophs. We propose a new, ecologically based, functional group 53140 classification for aquatic planktonic protists. This is the first time that all the three groups of 54 55141 planktonic protists – phytoplankton, mixotrophs and microzooplankton – have been considered 56 57142 explicitly under the functional group approach. The group divisions we propose are based on both 58 59143 energy and nutrient acquisitions, and are consistent with the main drivers for conceptual and 60 61 62 Page 5 of 23 63

64 Page 5 of 28 65 144 mathematical modelling (i.e., biogeochemistry and trophic dynamics). We discuss the importance 145 of these groups as descriptors for future research on planktonic protist communities. 1 1462 3 1474 Classifying Protist Functional Groups 5 1486 In evolutionary terms, heterotrophy (originally osmotrophic or saprotrophic, later including 7 1498 phagotrophy) is the ancestral state in protists while photo-autotrophy is the derived and more recent 9 state (Raven 1997; Raven et al. 2009). The developmental lines from phago-heterotrophy to photo- 10150 11151 autotrophy have occurred through a series of evolutionary pathways with gains and losses of 12 13152 physiological functionality (Raven et al. 2009). Notably, there have been sequences of acquisition 14 15153 and then loss of the capability to photosynthesize (e.g., Delwiche 1999; Saldarriaga et al. 2001; Van 16 17154 Doorn and Yoshimoto 2010; Wisecaver and Hackett 2010). That capability, and the nature of its 18 19155 expression in extant protists, is of such fundamental importance that it usefully forms the basis of a 20 156 functional group classification. 21 22157 Broadly following the direction of protist evolutionary pathways, we propose a division of 23 24158 protists according to the schematic shown in Figure 2; differences in physiological processes 25 26159 between the different groups are highlighted in Figure 3. All protists appear to be osmotrophic to 27 28160 some degree, if only for certain vitamins and to re-acquire leaked primary metabolites such as 29 30161 protein amino acids (Flynn and Berry 1999). Accordingly, we do not use osmotrophy as a 31162 functional group characteristic. In contrast, the presence or absence of phagotrophy and/or of 32 33163 phototrophy are clear defining characteristics that have profound consequences for biogeochemistry 34 35164 and trophic dynamics through the operation of predator-prey interactions (Flynn et al. 2013; Mitra 36 37165 et al. 2014a). In what follows, we thus place emphasis on photo- and phagotrophy as classifying 38 39166 processes. 40 41167 We identify functional groups at the extreme ends of the spectrum as (i) phagotrophs, which 42168 conform to the common concept of “microzooplankton” (including heterotrophic nano-flagellates; 43 44169 Figs 2 and 3A), and, (ii) phototrophs incapable of phagocytosis that conform to the common 45 46170 concept of “phytoplankton” (Figs 2 and 3B). The mixotrophic protists, combining phago- and 47 48171 phototrophy in a Acceptedsingle cell, are first divided with Manuscript respect to phototrophy between constitutive 49 50172 (inherent or innate) versus non-constitutive (acquired) capabilities. Constitutive mixotrophs (CMs; 51 52173 Figs 2 and 3C) have the innate ability to photosynthesize – that is, they have vertical transmission 53174 of plastids and, presumably, the ability to regulate plastid function via protist nuclear-encoded 54 55175 genes. Non-constitutive mixotrophs (NCMs, Fig. 2), in contrast, acquire the capability to 56 57176 photosynthesize from consumption of phototrophic prey. They depend on horizontal transmission 58 59177 of plastids or symbionts. The NCMs can then be divided into generalists and specialists. Generalist 60 61178 non-constitutive mixotrophs (GNCMs; Figs 2 and 3D) can use photosystems sequestered from a 62 Page 6 of 23 63

64 Page 6 of 28 65 179 broad range of phototrophic prey. Specialist non-constitutive mixotrophs (SNCMs; Fig. 2) have 180 developed a need to acquire the capacity for photosynthesis from one or a few specific sources. This 1 1812 SNCM grouping can then be further divided into those which are plastidic (pSNCMs, Figs 2 and 3 1824 3E) and those which contain endosymbionts (eSNCMs, Figs 2 and 3F). 5 1836 Constitutive mixotrophs (CMs, Fig. 3C) conform to the common perception of mixotrophic 7 1848 protists as unicellular algae that can consume other organisms (Sanders and Porter 1988). The CM 9 group includes representatives from a wide range of eukaryotic “phytoplankton” (almost all major 10185 11186 phototrophic protist groups excluding diatoms; Flynn et al. 2013; Jeong et al. 2010), ingesting 12 13187 various prokaryotic (e.g., cyanobacteria, bacteria) and eukaryotic prey (e.g., ciliates, dinoflagellates, 14 15188 cryptophytes, amoebae; Burkholder et al. 2008; Jeong et al. 2010; Stoecker et al. 2006; Tillmann 16 17189 1998; Zubkov and Tarran 2008). 18 19190 Non-constitutive mixotrophs (NCMs, Fig. 3D-F) lack an inherent (constitutive) ability to 20 191 fully synthesize, repair and control the photosynthetic machinery (Flynn and Hansen 2013). 21 22192 Mechanisms differ among representatives, but they all engulf photosynthetic prey. They may then 23 24193 either retain the prey as symbionts through a process termed endosymbiosis. Alternatively, they 25 26194 retain parts of the ingested prey necessary for photosynthesis – chloroplasts (kleptoplastidy), along 27 28195 with, sometimes, the prey nucleus (karyoklepty) and mitochondria, making use of these for a period 29 30196 of time (see reviews by Johnson 2011a,b and references therein; Stoecker et al. 2009). The retention 31197 time (for kleptoplastids) varies from hours to days or longer, depending on the mixotroph and the 32 33198 prey. 34 35199 The GNCM group (Fig. 3D) uses chloroplasts derived from several to many prey types (e.g., 36 37200 Laval-Peuto and Febvre 1986; Laval-Peuto et al. 1986; Schoener and McManus 2012; Stoecker et 38 39201 al. 1988, 1989). About a third of the ciliates (by numeric abundance) inhabiting the marine photic 40 41202 zone fall within this GNCM functional group (Blackbourn et al. 1973; Calbet et al. 2012; Dolan and 42203 Pérez 2000; Jonsson 1987; Laval-Peuto and Rassoulzadegan 1988; McManus et al. 2004; Pitta and 43 44204 Giannakourou 2000; Pitta et al. 2001; Stoecker et al. 1987). The ability to maintain an acquired 45 46205 photosynthetic capacity by GNCMs is very poor, and frequent re-acquisition is required. 47 48206 In contrast Accepted to the GNCM group, SNCMs acquire Manuscript photosystems from only specific prey. 49 50207 Specialization ranges from harbouring only plastids to harbouring intact cells (protists or 51 52208 cyanobacteria) as symbionts. Maintenance of the acquired photosystems is usually good, so that 53209 SNCMs can modulate photosynthesis (photoacclimate and undertake damage repair) similar to that 54 55210 seen in CMs but absent in GNCMs. Among the SNCMs, the pSNCM sub-group (Fig. 3E) includes 56 57211 ciliates such as Mesodinium rubrum (Garcia-Cuetos et al. 2012), which feed on several prey types, 58 59212 but acquire photosynthetic apparati (and nuclei) only from specific cryptophyte clades (Hansen et 60 61213 al. 2012; Johnson 2011a, b;Johnson et al. 2007), the dinoflagellate Dinophysis, which sequesters 62 Page 7 of 23 63

64 Page 7 of 28 65 214 plastids from the ciliate M. rubrum (Park et al. 2006), and, an undescribed Karlodinium-like 215 dinoflagellate that acquires plastids from the haptophyte Phaeocystis antarctica (Gast et al. 2007; 1 2162 Sellers et al. 2014). 3 2174 The photosymbiotic eSNCM sub-group (Fig. 3F) includes, within marine systems, the 5 2186 biogeochemically important and cosmopolitan Foraminifera and Radiolaria (Acantharia and 7 2198 Polycystinea). These mixotrophs harbour and maintain dinoflagellate, haptophyte, or green algal 9 endosymbionts. The endosymbionts are acquired during the juvenile stages and maintained 10220 11221 throughout most of the life cycle (Caron et al. 1995). The presence of these endosymbionts is 12 13222 obligatory for normal growth and reproduction in eSNCMs (Caron et al. 1995; Decelle et al. 2012; 14 15223 Langer 2008; Probert et al. 2014). Freshwater ciliates (Paramecium bursaria, Vorticella spp, 16 17224 Stentor spp, Frontonia spp, Stokesia spp and Euplotes spp) specifically harbour the microalga 18 19225 Chlorella as endosymbionts and thus falls within the eSNCM category (Berninger et al. 1986). 20 226 However, in contrast to the marine eSNCMs, the freshwater mixotrophs do not require the 21 22227 symbionts for reproduction (Dolan 1992). 23 24228 25 26229 Proposed versus other functional group classifications 27 28230 Our proposed grouping strikes at the very basis of ecophysiology - whether an organism is a 29 30231 primary producer, a consumer, or some combination of the two (mixotrophic). These are key 31232 features affecting contributions to biogeochemistry and/or trophic interactions. We now compare 32 33233 our proposal to earlier classifications of protists that considered mixotrophy. 34 35234 Comparison of the mixotrophic functional groups of Jones (1997) to our proposed grouping 36 37235 (Fig. 1 versus Fig. 2) reveals that all the groups proposed by Jones are constitutive mixotrophs (CM, 38 39236 Fig. 3C) because they have an innate capability to photosynthesize. In contrast, the groupings by 40 41237 Stoecker (1998) include both constitutive (Stoecker’s Types IIA, B, C and IIIA in Fig. 1; CM, Fig. 42238 3C) and non-constitutive mixotrophs (Stoecker’s Type IIIB in Fig. 1; NCM, Fig. 3D-F). The Types 43 44239 IIA, B and C of Stoecker (1998, Fig. 1) could thus in essence be phytoflagellates within the 45 46240 constitutive functional group. 47 48241 The prime discriminatorsAccepted for the functional group Manuscript descriptions of Jones (1997) and Stoecker 49 50242 (1998) are the balancing of energy and nutrient supply and demand. Thus, groups were split 51 52243 according to the proportion of phototrophy versus phagotrophy, with the lesser activity “topping 53244 up” the least abundant resource (carbon, nitrogen, phosphorus, iron etc.). However, now we view 54 55245 mixotrophy as likely performing a synergistic rather than a complementary role in nutrition (Adolf 56 57246 et al. 2006; Wilken et al. 2014a; and as modelled by Flynn and Mitra 2009). Repression and de- 58 59247 repression across the range of nutrient and energy acquisition options modulate expression of 60 61248 phototrophic versus phagotrophic activities. There is great variation across the constitutive 62 Page 8 of 23 63

64 Page 8 of 28 65 249 mixotrophs (CM group) in this regard, and also in growth rate potential. For example, it has been 250 shown that when conditions are optimal for mixotrophy (i.e., sufficient light and prey are available), 1 2512 some dinoflagellates have a higher growth rate compared to their growth when functioning as 3 2524 phototrophs (low or no prey available) or phagotrophs (under light limitation) (Jeong et al. 2010). 5 2536 The conditions specified by Jones (1997) and Stoecker (1998) could, therefore, be viewed as a 7 2548 secondary level of classification to that we now propose, describing placement of mixotrophs upon 9 sliding scales of phototrophy versus phagotrophy, depending on their physiological capabilities and 10255 11256 resource availabilities. 12 13257 We can thus envision a series of functional group descriptions ranging from the potential to 14 15258 engage mixotrophy (our proposal), to expression of mixotrophy according to physiological stressors 16 17259 (cf. Jones 1997; Stoecker 1998), to utilizing carbon dioxide or particulate food (bacteria/ detritus, 18 19260 algae, heterotrophic protists and animals) as a source of carbon (Pratt and Cairns 1985). The first 20 261 division, however, must be between protist groups that are non-phagotrophic phototrophs, 21 22262 phagotrophs with no phototrophic capacity, or mixotrophs with some combination of the two (i.e., 23 24263 between the CM, GNCM and SNCM groups). 25 26264 27 28265 Ecological Implications – a Demonstration 29 30266 The purpose in grouping organisms according to functionality is to aid our understanding of 31267 ecology. Arguably, the most fundamental ecological division is between primary producers and 32 33268 their consumers. Interactions between these two groups and higher trophic levels form cornerstone 34 35269 components in ecological research and modelling (e.g., Cohen et al. 1993). The mixotrophic protists 36 37270 combine facets of both primary producer and consumer in one organism. The ability to express 38 39271 these facets allows, and may actually require, us to divide them into CM, GNCM and SNCM 40 41272 functional groups (Figs 1 and 2). Each of these groups displays different interactions and dynamics 42273 with other plankton. As an example, we show here the contrasting behaviour of a simple trophic 43 44274 food web, in which a particular protist is operating as a strict phagotroph (“microzooplankton”), as 45 46275 a GNCM, or as a CM. 47 48276 Method – the foodwebAccepted model framework. To demonstrate Manuscript the potential impact of the different 49 50277 protist functional groups on trophic dynamics, we compare the outputs from three contrasting in 51 52278 silico plankton foodweb structures operating in a mesotrophic setting: 53279 (i) Scenario A: traditional foodweb structure (Fig. 4A). This framework includes photo-autotrophic 54 55280 (non-phagotrophic) protist phytoplankton as primary producers, the phago-heterotrophic 56 57281 microzooplankton (µZ) which graze on these phytoplankton and bacteria as decomposers. 58 59282 (ii) Scenario B: an alternative food web framework incorporating GNCMs (Fig. 4B). This food web 60 61283 structure includes the same components as Scenario A, except that the µZ are replaced with 62 Page 9 of 23 63

64 Page 9 of 28 65 284 GNCMs. The GNCMs demonstrate acquired phototrophy through sequestration of the 285 photosynthetic apparatus from the phytoplankton prey. 1 2862 (iii) Scenario C: the third alternative food web framework incorporates CMs (Fig. 4C). Again, the 3 2874 food web structure includes the same components as Scenario A, except that the µZ are replaced 5 2886 with CMs. The CMs photosynthesize using their constitutive chloroplasts and attain additional 7 2898 nutrition (C,N,P) through the ingestion of the phytoplankton prey. 9 The food web model structure for the three scenarios was adapted from Flynn and Mitra 10290 11291 (2009). In brief, this consists of a mixed layer depth of 25 m, inorganic N of 5 µM, and inorganic P 12 13292 of 0.625 µM, with an effective cross mixing-layer dilution rate of 0.05 d-1. The model includes 14 15293 variable stoichiometric (C:N:P) acclimative descriptions of the plankton. When we first explored 16 17294 modelling the ecophysiology of mixotrophic protists, we found that we had to split the potential for 18 19295 mixotrophy into groupings of what we now term here as CMs and NCMs. The “perfect beast” 20 296 model of Flynn and Mitra (2009) contained switch functions that could configure between these 21 22297 types, together with acclimation descriptions to enable them to represent all the functional groups 23 24298 described by Jones (1997) and Stoecker (1998). This model is used here (Fig. 5). For further details 25 26299 of the description of the model configurations, please see the Supplementary Material. 27 28300 Results from in silico experiments. The temporal and spatial development of biomass of the 29 30301 different functional groups within the simulated communities are very different under the three 31302 scenarios (Fig. 5A-C); additional plots are presented in Supplementary Material Figures S1-S3. In 32 33303 scenario A, the dynamics follow those expected from a typical predator-prey system. However, in 34 35304 both scenarios B and C, the mixotroph functional groups outcompete the phototrophic 36 37305 phytoplankton (hereafter, phytoplankton). Indeed, in scenario C, the CMs ultimately become the 38 39306 dominant functional group (akin to a bloom situation). In scenario B, in contrast, the GNCMs could 40 41307 only attain a limited productivity due to their dependency upon the phytoplankton for the supply of 42308 plastids to allow photosynthesis. 43 44309 The implementation of a GNCM versus a CM mixotroph thus generates an interesting 45 46310 dynamic to their phototrophic ecology. The GNCMs can never dominate the system. Due to their 47 48311 dependency on preyAccepted to acquire phototrophic capabilities Manuscript (Figs 2 and 3D), GNCM blooms would 49 50312 always terminate through exhaustion of prey (Supplementary Material Fig. S2). CMs, however, 51 52313 through a combination of phagotrophy and phototrophy have the advantage and the capability to 53314 dominate a system, ultimately forming successful blooms. Indeed, harmful algal bloom species are 54 55315 typically CMs (Burkholder et al. 2008). In essence, CMs act as intraguild predators, both feeding on 56 57316 and competing with their prey; thus in contrast to specialist predators (i.e., NCMs) dependent on 58 59317 specific prey items, CMs can suppress their prey much more strongly (Wilken et al. 2014b). For 60 61318 CMs and for phytoplankton, self-shading resulting in light limitation may become of consequence 62 Page 10 of 23 63

64 Page 10 of 28 65 319 for primary productivity; for the final days of production in a GNCM system, this light limitation is 320 of lesser importance as the pigment content of the water column degrades rapidly during the final 1 3212 stages of the bloom (see Flynn and Hansen 2013). 3 3224 Comparison of the cumulative primary productivity, by phytoplankton and the mixotrophs 5 3236 (phyto and mixo, respectively, bottom panel in Fig. 5) over the 30-day simulation period under the 7 3248 three alternative scenarios, showed a substantially higher amount of primary production when CMs 9 were implemented (Fig. 5; C-fix in Supplementary Material Figs S1-S3). Production of dissolved 10325 11326 organics originating directly from primary production was similarly enhanced for CMs 12 13327 (Supplementary Material Fig. S3; cf. Figs S1 and S2). The regeneration of dissolved inorganics, 14 15328 typically associated with predatory activities, was enhanced where GNCMs were implemented 16 17329 (scenario B; Supplementary Material Fig. S2; cf. Figs S1 and S3). 18 19330 As yet we know little detail about the mechanisms used by mixotrophs to modulate their 20 331 photoauto- vs phagoheterotrophic capabilities. Different species may occupy different regions of 21 22332 the continuum from a phototrophic extreme to a phagotrophic extreme, while the ecophysiology of 23 24333 others will be predominately photoauto- or predominantly phagoheterotrophic. The critical issue, 25 26334 then, is whether the protists are dependent upon other organisms (i.e., NCMs, Fig. 3D-F) for the 27 28335 acquisition and continuation of their mixotrophic potential, or if they possess the full genetic and/or 29 30336 physiological capacity to undertake both modes of nutrition all of the time (i.e., CMs, Figs 2 and 31337 3C). 32 33338 34 35339 Discussion 36 37340 38 39341 A major reason for dividing the protists into the proposed functional groups (Figs 2 and 3) is the 40 41342 recognition of the differences in the consequential population dynamics and role of the groups in 42343 ecosystems (Figs 4 and 5). The roles of the non-phagotrophic and non-phototropic forms 43 44344 (representative of traditional “phytoplankton” and “microzooplankton”) are established. A role of 45 46345 CMs is largely acknowledged in the literature, although discussions are dominated by alternate 47 48346 energy supply options,Accepted while we suggest the roles ofManuscript photo- and phago-trophy are more likely 49 50347 linked to synergy in energy and nutrient supply routes (see also Wilken et al. 2014a, b). The CMs 51 52348 have nonetheless drawn only limited attention of modellers. The scope for a revision in the 53349 ecological role of CMs is illustrated by their suggested relationship with bacteria, wherein 54 55350 especially nano-sized CMs promote bacterial growth by release of DOM, and thereby gain nutrients 56 57351 they would otherwise be unable to acquire (Mitra et al. 2014a). The GNCM group is expected to 58 59352 have quite different population dynamics from other mixotrophs, being dependent (within a 60 61353 generation time) on a repeated ingestion of phototrophic prey for chloroplasts. Flynn and Hansen 62 Page 11 of 23 63

64 Page 11 of 28 65 354 (2014) indicate some differences in these dynamics, but there likely is much more to explore, 355 related to the effects of mixotrophy on assimilation efficiency and of photon dose on the longevity 1 3562 of acquired plastids. The SNCMs at first sight may be considered similar to CMs, but there are 3 3574 sharp contrasts in the nature of the host (ciliate, Foraminifera etc.) in comparison with that of CMs 5 3586 (phytoflagellates, dinoflagellates etc.) and of the main prey types. While the need for donors of 7 3598 phototrophy (as plastids or as endosymbionts) is less frequent for SNCMs than for GNCMs, the 9 specialism in that need places an additional dynamic in their relationship with other planktonic 10360 11361 members of the ecosystem. 12 13362 The ecology of CMs is in some ways relatively simple, as they do not need to acquire their 14 15363 mixotrophic potential (for phototrophy) from another organism. Nevertheless, there are sound 16 17364 reasons to sub-divide CMs into those that consume bacteria (Hartmann et al. 2012; Zubkov and 18 19365 Tarran 2008; Unrein et al. 2014) versus those capable of (also) consuming non-bacterial prey 20 366 (Burkholder et al. 2008; Stoecker et al. 2006). This is especially true if the latter are competitors in 21 22367 terms of phototrophy, or even potential predators of the mixotrophs (Thingstad et al. 1996). The 23 24368 simulations run here (Fig. 5) were configured for a mesotrophic system where phagotrophy by µZ, 25 26369 GNCMs and CMs predominantly involves ingestion of phytoplankton prey. Within the three 27 28370 scenarios (Figs 4 and 5), it was assumed that the predators consumed only phytoplankton. The 29 30371 range of size of the protist phytoplankton group in these systems could vary by orders of magnitude 31372 (e.g., nano- to micro- sized). Likewise, their protist grazers could occupy a large size spectrum. For 32 33373 example, the size spectrum for the prey for GNCMs (15-60 µm ESD) can vary between 1-40 µm 34 35374 ESD (McManus et al. 2012; Stoecker et al. 1987). Divisions between those capable of consuming 36 37375 different prey sizes may be achieved via allometric considerations. However, there are plenty of 38 39376 examples of mixotrophs feeding on prey larger than themselves and, also, of larger species feeding 40 41377 on bacteria or picocyanobacteria (Glibert et al. 2009; Granéli et al. 2012; Jeong 2011; Jeong et al. 42378 2005, 2012; Lee et al. 2014; Seong et al. 2006). Accordingly, functional group divisions that either 43 44379 partition protists solely according to predator-prey allometrics (e.g., Sieburth et al. 1978), or have a 45 46380 sliding scale for photoauto- versus phagohetero- trophy (e.g., Jones 1987), appear insufficiently 47 48381 robust from an ecologicalAccepted perspective. Below we consider Manuscript each group in more detail. 49 50382 CM group. In the photic zone plankton, CMs (Fig. 3C) often dominate eukaryotic microbial 51 52383 biomass (cf. Supplementary Material Fig. S3), both in eutrophic and oligotrophic systems across all 53384 climate zones (Burkholder et al. 2008; Hartman et al. 2012; Havskum and Riemann 1996; Li et al. 54 55385 2000a, b; Sanders and Gast 2012; Stoecker et al. 2006; Unrein et al. 2007, 2014). Mixotrophic 56 57386 phytoflagellates have accounted for 50% of the pigmented biomass during non-bloom conditions 58 59387 off Denmark (Havskum and Riemann 1996). Constitutive mixotrophy has been identified as a major 60 61388 mode of nutrition for harmful phytoflagellate species in eutrophic coastal waters (Burkholder et al. 62 Page 12 of 23 63

64 Page 12 of 28 65 389 2008; Jeong et al. 2010; Stoecker et al. 2006) and CMs can account for significant and occasionally 390 dominant predation pressure on bacteria (Hartmann et al. 2012; Sanders et al. 1989; Unrein et al. 1 3912 2014; Zubkov and Tarran 2008). For example, it has been shown that mixotrophy plays a vital role 3 3924 in the trophic dynamics of the oligotrophic gyres (Hartmann et al. 2012; Zubkov and Tarran 2008). 5 3936 Modelling this ecosystem using the traditional paradigm (Scenario A, Fig. 4) would fail to portray 7 3948 the correct dynamics and, thus, would be misleading. Most of the phytoplankton in these systems 9 are bacterivores, and without mixotrophy (photoautotrophy plus bacterivory), primary production 10395 11396 would be much lower due to N and P starvation. 12 13397 The differences between CMs and NCMs are clear and unambiguous. While each group 14 15398 includes examples of the sliding scale and allometrics, we justify the split based on the definition of 16 17399 the source of the phototrophic potential (innate versus acquired), because this has profound impacts 18 19400 for the ecophysiology of the organisms. 20 401 GNCM vs SNCM groups. Up to about one-third of photic zone ciliate microzooplankton are 21 22402 GNCMs (Calbet et al. 2012; Dolan and Pérez 2000; McManus et al. 2004; Pitta et al. 2001; Fig. 23 24403 3D). In summer stratified surface waters, more than 50% of ciliates have on occasion been found to 25 26404 be mixotrophic (Calbet et al. 2012; Putt 1990; Stoecker et al. 1987). The contribution of these 27 28405 GNCMs to “phytoplankton” biomass (as chlorophyll) can thus be substantial (Stoecker et al. 2013; 29 30406 see also Fig. 2 and Supplementary Material Fig. S2). They can comprise a significant proportion of 31407 all zooplankton, and their ecology is not only linked to their mixotrophic capabilities, but also 32 33408 limited by their need to consume phototrophic prey in order to acquire chloroplasts. 34 35409 The SNCMs (Fig. 3D-F), requiring specific prey, present a different ecological dynamic in 36 37410 comparison with the CMs and GNCMs. They do not need to interact with specific prey often, but 38 39411 when they need to do, they must consume one of only a few prey options in order to acquire 40 41412 phototrophy. That restriction has important implications for the SNCMs and for their specific prey. 42413 In blooms, the cosmopolitan SNCMs Mesodinium rubrum and M. major can account for 43 44414 approaching 100% of plankton biomass (Crawford et al. 1997; Garcia-Cuetos et al. 2012; Herfort et 45 46415 al. 2012; Montagnes et al. 1999; Packard et al. 1978). This is possible as the need for plastids by the 47 48416 red Mesodinium spAcceptedecies is occasional (Johnson and Manuscript Stoecker 2005; Johnson et al. 2006), and 49 50417 acquired cryptophyte plastids can even replicate within the ciliate (Hansen et al. 2012; Johnson et 51 52418 al. 2007). 53419 The Foraminifera and Radiolaria (Acantharia and Polycystinea) eSNCMs (Fig. 3F) 54 55420 contribute significantly to primary production and trophic dynamics in oligotrophic oceanic gyres, 56 57421 and thus play a vital role in marine biogeochemistry (Caron et al. 1995; Decelle et al. 2013; Dennett 58 59422 et al. 2002; Gast and Caron 2001; Michaels et al. 1995; Stoecker et al. 2009; Swanberg 1983). 60 61423 These eSNCMs, the dominant large planktonic predators in the subtropical gyres, probably could 62 Page 13 of 23 63

64 Page 13 of 28 65 424 not survive and grow in this nutritionally dilute environment without the C supplement from their 425 symbionts (Caron et al. 1995), suggesting a major role of mixotrophy in shaping the trophic 1 4262 structure of subtropical gyre ecosystems. 3 4274 5 4286 Conclusion 7 4298 9 Functional group descriptors are specifically intended to aid our understanding of ecology (Gitay 10430 11431 and Noble 1997; Smith et al. 1997). Arguably the ultimate test of that understanding comes from an 12 13432 ability to construct and use mathematical models which display behaviours that align with 14 15433 expectations gained from empirical knowledge. 16 17434 Based on experimental and modelling studies, we now realise that mixotrophy in protists 18 19435 can be a synergistic process and does not just provide a “top-up” or “survival” mechanism (Adolf et 20 436 al. 2006; Mitra and Flynn 2010; Mitra et al. 2014a; Våge et al. 2013). The nature of that synergism 21 22437 between photo- and hetero-trophy is ultimately modulated by whether the phototrophic capacity is 23 24438 constitutive (innate) or acquired. Accordingly, we propose that the functional group descriptors for 25 26439 planktonic protists should align with the innate capacity, or otherwise, for phototrophy and/or 27 28440 phagotrophy (Fig. 2). A division on these grounds makes sense for modelling, both from 29 30441 evolutionary and ecological perspectives, in that these groups are clear and unambiguous. Such 31442 traits are important features in functional group definitions. Within this division, the groups 32 33443 described by Jones (1997) and Stoecker (1998) form important secondary functional group 34 35444 descriptions, while those by Pratt and Cairns (1985) form a tertiary level of description for both 36 37445 mixotrophic and heterotrophic protists. 38 39446 Over the past decade there has been a drive to modify biogeochemical and aquatic food web 40 41447 models through incorporation of the functional group approach. Within these models, plankton 42448 functional types are increasingly deployed to aid descriptions of processes from biogeochemistry to 43 44449 fisheries (e.g., end-to-end models; Rose et al. 2010). The primary focus has been on splitting the 45 46450 “phytoplankton” into several groups – for example, into “diatoms” requiring Si, “calcifiers” 47 48451 requiring calcium, Acceptedetc. – with each group having its ownManuscript state variables (e.g., Baretta et al. 1995). 49 50452 Far less emphasis has been placed on expanding the “zooplankton” component (see Mitra et al. 51 52453 2014b and references therein), while “mixotrophic” groups are typically ignored altogether. 53454 Modellers typically start with an attempt to simplify the system sufficiently to enable or assist 54 55455 computation and analysis. That simplification process must not be so great that the critical linkage 56 57456 to reality is lost. Given our renewed appreciation of mixotrophy (Flynn et al. 2013 and references 58 59457 therein), we suggest that a complete overhaul of the core structure of biogeochemical and plankton 60 61 62 Page 14 of 23 63

64 Page 14 of 28 65 458 food web models may be warranted, in order to provide a more accurate ecological perspective on 459 ecosystems functioning that acknowledges the existence of mixotrophs. 1 4602 3 4614 4625 Acknowledgements 6 7 4638 This work was funded by grants to KJF and AM from the Leverhulme Trust (International Network 9 10464 Grant F00391V) and NERC (UK) through its iMARNET programme NE/K001345/1. The 11 12465 University of Dundee is a registered Scottish charity, number SC015096. AM would like to thank 13466 Rohan Mitra-Flynn for his patience and co-operation. 14 15467 16 17468 18 19469 References 20 21470 22 23471 Adolf J, Stoecker D, Harding L, Jr (2006) The balance of autotrophy and heterotrophy during 24472 mixotrophic growth of Karlodinium micrum (Dinophyceae). J Plankton Res 28:737-751 25 26473 Aiken AC, DeCarlo PF, Jimenez JL (2007) Elemental analysis of organic species with electron 27 28474 ionization high-resolution mass spectrometry. Anal Chem 79:8350-8358 29 30475 Azam F, Fenchel T, Field JG, Gray JS, Meyer-Reil LA, Thingstad F (1983) The ecological role of 31 32476 water-column microbes in the sea. Mar Ecol Prog Ser 10:257-263 33 34477 Baretta JW, Ebenhöh W, Ruardij R (1995) The European regional seas ecosystem model, a 35478 complex marine ecosystem model. Nether. J Sea Res 33:233-246 36 37479 Berninger U-G, Finlay BJ, Canter HM (1986) The spatial distribution and ecology of zoochlorellae- 38 39480 bearing ciliates in a productive pond. J Protozool 33:557-563 40 41481 Blackbourn DJ, Taylor F, Blackborn J (1973) Foreign organelle retention by ciliates. J Protozool 42 43482 20:286-288 44 Burkholder JM, Glibert PM, Skelton HM (2008) Mixotrophy, a major mode of nutrition for harmful 45483 46484 algal species in eutrophic waters. Harmful Algae 8:77-93 47 48485 Calbet A, MartínezAccepted RA, Isari S, Zervoudaki S, Nejstgaard Manuscript JC, Pitta P, Sazhin AE, Sousoni S, 49 50486 Gomes A, Berger SA, Tsagaraki TM, Ptacnik R (2012). Effects of light availability on 51 52487 mixotrophy and microzooplankton grazing in an oligotrophic plankton food web: evidences 53 54488 from a mesocosm study in Eastern Mediterranean waters. J Exp Mar Biol Ecol 424–425:66- 55 489 77 56 57490 Caron DA, Michaels AF, Swanberg NR, Howse FA (1995) Primary productivity by symbiont- 58 59491 bearing planktonic sarcodines (Acantharia, Radiolaria, Foraminifera) in surface waters near 60 61492 Bermuda. J Plankton Res 17:103-129 62 Page 15 of 23 63

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64 Page 21 of 28 65 698 Van Doorn WG, Yoshimoto K (2010) Role of chloroplasts and other plastids in ageing and death of 699 plants and animals: A tale of Vishnu and Shiva. Ageing Res Rev 9:117–130 1 7002 Weithoff G (2003) The concepts of ‘plant functional types’ and ‘functional diversity’ in lake 3 7014 phytoplankton– a new understanding of phytoplankton ecology? Freshwater Biol 48:1669- 5 7026 1675 7 7038 Wilken S, Schuurmans JM, Matthijs HC (2014) Do mixotrophs grow as photoheterotrophs? 9 Photophysiological acclimation of the chrysophyte Ochromonas danica after feeding. New 10704 11705 Phytol 204:882-889 12 13706 Wilken S, Verspagen JMH, Naus‐Wiezer S, Van Donk E, Huisman J (2014) Comparison of 14 15707 predator–prey interactions with and without intraguild predation by manipulation of the 16 17708 nitrogen source Oikos 123:423-432 18 19709 Wisecaver, JH, Hackett JD (2010) Transcriptome analysis reveals nuclear-encoded proteins for the 20 21710 maintenance of temporary plastids in the dinoflagellate Dinophysis acuminata. BMC 22711 Genomics 11:366 23 24712 Zubkov MV, Tarran GA (2008) High bacterivory by the smallest phytoplankton in the North 25 26713 Atlantic Ocean. Nature 455:224-227 27 28714 29 30715 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 Accepted Manuscript 49 50 51 52 53 54 55 56 57 58 59 60 61 62 Page 22 of 23 63

64 Page 22 of 28 65 716 Legends 717 1 7182 Figure 1. Traditional classification of mixotrophic protists according to Stoecker (1998; open 3 7194 boxes) and Jones (1997; grey boxes). “Groups” proposed by Jones (1997) have been aligned 5 7206 against “Types” proposed by Stoecker (1998). DIN, dissolved inorganic nutrients. 7 7218 9 Figure 2. Flow chart showing the pathways used to derive the functional groups we propose to 10722 11723 classify the planktonic protists. See also Figure 3. 12 13724 14 15725 Figure 3. Schematic illustrating the different levels in complexity among different types of protist. 16 17726 (A) phagotrophic (no phototrophy); (B) phototrophic (no phagotrophy); (C) constitutive 18 19727 mixotroph, with innate capacity for phototrophy; (D) generalist non-constitutive mixotroph 20 728 acquiring photosystems from different phototrophic prey; (E) specialist non-constitutive 21 22729 mixotroph acquiring plastids from a specific prey type; (F) specialist non-constitutive 23 24730 mixotroph acquiring photosystems from endosymbionts. DIM, dissolved inorganic material 25 26731 (ammonium, phosphate etc.). DOM, Dissolved organic material. See also Figure 2. 27 28732 29 30733 Figure 4. Three contrasting simple food-web structures. Scenario A portrays the classic paradigm 31734 where phytoplankton and microzooplankton are the two protist plankton functional types. 32 33735 Within Scenarios B and C, the microzooplankton functional type is replaced by the non- 34 35736 constitutive mixotrophs (NCMs) and constitutive mixotrophs (CMs) respectively. The 36 37737 release and uptake of dissolved inorganic matter (DIM, ammonium, phosphate etc.) is 38 39738 indicated. 40 41739 42740 Figure 5. Temporal pattern of the development of the biomass in the simulated communities under 43 44741 the 3 scenarios. Also, shown the cumulative primary productivity by phytoplankton (phyto) 45 46742 and mixotroph (mixo) over the 30-day simulation period under the three alternative 47 48743 scenarios. NoAccepted mixotrophs are present in Scenario Manuscript A. See also Figure 4. 49 50744 51 52 53 54 55 56 57 58 59 60 61 62 Page 23 of 23 63

64 Page 23 of 28 65 Figure 1 TYPE I “Ideal” mixotroph; Balanced phototrophy and phagotrophy

TYPE II Phagotrophic “algae”; Primarily Phototrophic

TYPE IIA TYPE IIB TYPE IIC Feed when DIN is limiting Feed under trace organics growth Feed under light limitation e.g., Prorocentrum minimum factor limitation e.g., Chrysochromulina brevifilum e.g., Uroglena americana GROUP B GROUP C Primarily phototrophic; Primarily phototrophic; feed for feed under light limitation essential element (e.g., iron) or e.g., Chrysochromulina growth substance (e.g., brevifilum phospholipids) e.g., Uroglena americana GROUP D Primarily phototrophic; very low ingestion rate; ingestion of prey and/or uptake of organics to aid TYPE III cell maintenance under severe Photosynthetic “protozoa”; Primarily Phagotrophic light limitation e.g., Cryptomonas ovata

TYPE IIIAAccepted ManuscriptTYPE IIIB C-fix under prey limitation; have plastids Protozoa with acquired phototrophy through & assimilates DIN harbouring endosymbionts, plastid sequestration e.g., Poterioochromonas malhamensis C-fix to supplement C nutrition e.g., plastid retaining Laboea strobilia, GROUP A symbiont harbouring green Noctiluca scintillans Growth dependent on heterotrophy; phototrophy supplements growth rate e.g., Poterioochromonas malhamensis Page 24 of 28 Figure 2 START WITH PROTIST Phago- Capable of heterotrophs/ NO Phagocytose? YES carbon (C) NO Osmotrophs e.g., Oxyrrhis, fixation? Fig. 3(A) YES Photo-autotrophs e.g., diatoms Fig. 3(B) plastidic Constitutive/innate Specialist Non-Constitutive YES capability for NO C-fixation? Mixotrophs C-fixation e.g., Mesodinium, mediated by Dinophysis NO pSNCM; Fig. 3(E) symbionts? Constitutive Mixotrophs YES e.g., Karlodinium, endosymbiotic Prymnesium Specialist CM; Fig. 3(C) YES AcceptedC- fixation Manuscript Non-Constitutive capabilities Mixotrophs acquired from Generalist e.g., Collozoum, green Noctiluca specific prey? Non-Constitutive eSNCM; Fig. 3(F) Mixotrophs NO e.g., Laboea strobila, Strombidium capitatum Page 25 of 28 GNCM; Fig. 3(D) Figure 3 (A) Phago-heterotroph (B) Photo-autotroph (C) Constitutive Mixotroph; CM

Phototrophy Phototrophy Phagotrophy Phagotrophy

CO2 CO2

DIM DIM DIM Growth Growth Growth DOM DOM DOM

(D) Generalist Non-Constitutive Mixotroph; (E) plastidic Specialist (F) endosymbiotic Specialist GNCM Non-Constitutive Mixotroph; pSNCM Non-Constitutive Mixotroph; eSNCM Phototrophy Phagotrophy Phototrophy Phagotrophy CO2 Phagotrophy

CO Accepted Manuscript2 Phototrophy

DIM DIM DIM Growth CO2 Growth Growth DOM DOM DOM

Page 26 of 28 Figure 4 (A) Bacteria DOM

Phytoplankton

DIM

μZ

(B) Bacteria DOM

Phytoplankton

DIM

GNCM (C) Bacteria DOM Accepted Manuscript Phytoplankton

DIM

CM Page 27 of 28 Figure 5

Accepted Manuscript

Page 28 of 28