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US Bethany Northeast the smallest on the phytoplankton of diversity functional and Dynamics www.pnas.org/cgi/doi/10.1073/pnas.1918439117 groups, applied (9). phytoplankton dinoflagellates been a well-defined successfully of fitting cell including has populations by of method natural estimat- observations number to This for frequent cell distribution. method to of size a model exceed independently loss matrix dif- developed and far rate size-structured therefore (5) growth is division can al. into It ing et abundance day (4). in Sosik single population changes processes. a partition the picoeukary- to of in of ficult stock grazed number standing and The the challenges. produced added otes the presents phytoplank- marine for ton of populations productivity natural monitoring observed, primary observations and of rates, of series we estimates assemblage. time Here, loss picoeukaryote including 16-y 4). rates, community, a (3, phytoplankton division their of division coastal a analysis of and of our because growth on regions cell report rapid some for in capacity productivity dom- can primary more picoeukaryotes abundance, inate numerous, lower their under- with Despite less well stood. less Compared consequently are and rates. heterogeneous, picoeukaryotes vital taxonomically and the dynamics cyanobacteria, community knowl- of requires however, edge diversity, this of significance ecological (e.g., cyanobacte- the otes functional of single a consisting (Prochlorocococcus as diverse, ria treated taxonomically often is is it class group, size this While 2). (1, M picoeukaryotes stocks standing their than productivity primary suggest. more region’s the contribute and the during control top-down lim- to mortality greater to light greater subject experience are and otes with to spring Compared night. and the at groups than fall in day Both the limited environment. in temperature abiotic despite ited and be that, biotic to the conclude appear similarly in zoo- respond and changes groups populations and timescales to their these lysis differences, long of taxonomic viral dynamics and their from the short (likely describe across rates We abundant grazing). loss roughly more plankton greater at the divide to of picoeukaryotes subject rate the the that size- twice found a dynamics We rates picocyanobacteria the used location. the division compared We of a situ and those Shelf. assemblage in with at picoeukaryote estimate US community the to time Northeast for phytoplankton model 16-y the population a a global on structured analyzed of and site we webs observations nearshore end, food key of this marine is series To dynamics in cycles. community role their biogeochemical their producers of understanding primary Knowledge 2019) to 22, abundant ocean. October review most the for (received 2020 in the 9, April are approved and Denmark, Picophytoplankton Helsingor, Copenhagen, of University Fenchel, M. Tom by Edited and 02543; MA Hole, Woods ilg eatet od oeOengahcIsiuin od oe A02543; MA Hole, Woods Institution, Oceanographic Hole Woods Department, Biology hl el nalbrtr a ecnand one,and counted, contained, be may laboratory a in cells While ylsadfr h onaino aymrn odwebs food marine many of biogeochemical foundation the global form and impact cycles picophytoplankton arine Synechococcus Micromonas | o cytometry flow b a,1 n ed .Sosik M. Heidi and , and ihe .Neubert G. Michael , and c oehn a alCne,Mrn ilgclLbrtr,WosHl,M 02543 MA Hole, Woods Laboratory, Biological Marine Center, Paul Bay Josephine (6), n h picoeukary- the and Synechococcus) | .Udrtnigthe Understanding Ostreococcus). arxmodel matrix Prochlorococcus h picoeukary- the Synechococcus, Synechococcus Synechococcus | rmr productivity primary a,1 a,b 7 ) n some and 8), (7, rse .Hunter-Cevera R. Kristen , ttesame the at n are and 3708062. aadpsto:AlMTA cit o h iiinrt oe swl stedata the as well Zenodo, as at model available rate are division manuscript the this for in scripts MATLAB presented All deposition: Data the under Published Submission.y Direct PNAS a is article This interest.y competing no declare authors The doi:10.1073/pnas.1918439117/-/DCSupplemental at online information supporting contains article This 1 H.M.S. and K.R.H.-C., B.L.F., tools; paper. the analytic K.R.H-C., wrote B.L.F., H.M.S. new and research; M.G.N., B.L.F., B.L.F., contributed performed and research; data; H.M.S. H.M.S. analyzed designed and and A.R.S., A.S., H.M.S. A.S., R.J.O., and R.J.O., K.R.H.-C., K.R.H.-C., M.G.N., M.G.N., B.L.F., contributions: Author 6 nodrt pl tt h sebaeo ml eukary- small Observatory of Coastal assemblage Vineyard the Martha’s to the it at (MVCO; apply present to otes order in (6) t,adtepoaiiyo eldvdn eed ntecell’s the on depends dividing cell a availabil- light of the probability on the depends and growing cell ity, a Methods ). of and probability (Materials division The and growth cell through classes this throughout picoeukaryotes the as community paper. this than to refer more (SI size Since this eukaryotes 87% S2). approach cells all Fig. few analysis 8 Appendix, very our approximately threshold; ( upper than in servative largest less include be diameters to to with chose tend we cells tribution, when times however, at S1F year distribution data, Figs. size and observed our day the on of of tail threshold the arbitrary exclude individual would this 2 their only Imposing than Traditionally, on less ton. size. diameters based and with pigmentation cytometry cells including flow traits, with cell identified be owo orsodnemyb drse.Eal fwe@hieuo hsosik@ or [email protected] Email: addressed. be may whoi.edu. correspondence whom To iiain ftetn h iolntna igefunc- single a as possible picoplankton the the group. highlights tional treating and of ecosystem work important limitations This Shelf economically alone. so the US of abundance than Northeast and understanding their productivity our community from primary improves pre- inferred micrograzer region’s a be the the would be to of to more item contribute appear rapidly drive more prey They repro- that much ferred picophytoplankton. grazing) picoeukaryotes factors via other the (probably into than lost that insight are found and gain duce We monitoring to dynamics. been years have their report we many we community Here, over group. phytoplankton understudied a picoeukary- and the on diverse which a of are car- phytoplankton, is otes marine production by primary out world’s ried the of half Approximately Significance eaatdtemdldsrbdi utrCvr tal. et Hunter-Cevera in described model the adapted We u ouainmdlalw o rniin ewe size between transitions for allows model population Our ntesme)aels hn2 than less are summer) the in b y aiePlc etr od oeOengahcInstitution, Oceanographic Hole Woods Center, Policy Marine y 41 .T nueta ecpueteetr dis- entire the capture we that ensure To S2). and c ◦ 19.500 oetJ Olson J. 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ECOLOGY size. Observations of Synechococcus led Hunter-Cevera et al. (6) Results to prohibit division in the first 6 h after dawn in their model. In Model Validation. To ensure that our method can accurately contrast, the picoeukaryote size distribution frequently exhibits estimate picoeukaryote division rate, we first applied it to obser- decreases in cell size after dawn, suggesting division early in the vations from a dilution series experiment. The dilution series is day. We therefore relaxed the constraint, making the division a standard technique for estimating division and grazing rates function in our model independent of time within a day. We by comparing phytoplankton growth in a sample of seawater evaluated our method against a standard laboratory technique with that in a sample that has been diluted with filtered water for estimating division rate (Model Validation) and found that (11). Theory suggests that diluting a sample increases the dis- the agreement between the two methods was improved by this tance between organisms in the bottle and so effectively reduces change. grazing pressure on the phytoplankton. From the difference in We then applied our model to observations of picoeukary- net growth rate across the treatments, one can infer what the otes at MVCO, a dynamic location within the Northeast US growth rate would be in the absence of grazers—approximately Shelf Long-Term Ecological Research (NES-LTER) site. This the division rate. We applied the model to flow cytometric obser- observatory is open to advection from the broader continen- vations of the picoeukaryote cells within both the undiluted tal shelf system, which undergoes dramatic seasonal change and and most diluted seawater samples. We evaluated our method has been warming in recent years (10). The region is home using the concordance correlation coefficient (12). This statistic to an economically important ecosystem that relies on phyto- accounts for both precision and accuracy, with one correspond- plankton as the primary producers. It is therefore critical to ing to perfect agreement and zero corresponding to no agree- understand the structure of this plankton community and in ment. Application of the model to the undiluted and diluted particular, how it responds to changes in the physical environ- bottles led to concordance correlation coefficients with the dilu- ment. The environmental variability in this region as well as tion series method of 0.719 and 0.894, respectively. Details the scope and resolution of our observations make MVCO a of the experimental work are presented in Hunter-Cevera valuable location to study picophytoplankton ecology. Compar- et al. (6). While there is reason to doubt the generality of divi- ative work will be necessary to determine whether our conclu- sion rates measured in incubations (13–15), it is reassuring to sions about the picophytoplankton at MVCO hold throughout see that our model produced estimates that agree with those their range. obtained through direct counts of cells in a contained system Here, we describe diel, seasonal, and interannual patterns (SI Appendix, Fig. S3A). in picoeukaryote dynamics and compare them with those of Note that the division rate estimates derived from our model Synechococcus at the same location. Our analysis reveals sim- depend on changes in cell size distribution rather than changes ilarities in the responses of these populations to their shared in cell counts. Moreover, the model assumes that the size dis- environment—but also surprising differences in the ecological tribution is only altered through cell growth and division. This roles of these two picoplankton groups. assumption could be violated if there are size-dependent loss

104 10

) A D -1

5 (cells mL Concentration 0 )

-1 4 B E 3 2 1

Division rate (d 0

) 4 C F -1 3 2 1

Loss rate (d 0

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 climatology

Fig. 1. Daily measurements between 2003 and 2018. (A) Cell concentration is a 48-h running average. (B) Division rate is computed by comparing initial and final population sizes in each day’s simulation, and (C) loss rate is calculated by subtracting the observed net growth rate from the division rate. (D–F) Climatological values are the averages for each day of the year across all years in the time series. Only dates with at least 23 h of FlowCytobot observations are included in this analysis (n = 3,200).

2 of 7 | www.pnas.org/cgi/doi/10.1073/pnas.1918439117 Fowler et al. Downloaded by guest on September 30, 2021 Downloaded by guest on September 30, 2021 n (C and 2. Fig. divi- peak precedes concentration cell peak climatologies, (SI the In year cells the ∼300 observed throughout dynamics diel community repro- and S1). to picoeukaryote Fig. the Appendix, distributions able toward this is of back model in range drops Our the then dawn. duce cell before and larger distribution hours toward initial daylight shifts relatively distribution during remains the distri- sizes distribution summer, size size community In the are in constant. days, rate patterns winter division diel On of daily bution. range in the differences in striking reflected These (∼2.1 again. is August ues rate in peak Division a 1). to (Fig. (∼0.1 February cycle in seasonal lowest pronounced a exhibits Seasonality. situ. in or a year picoeukaryote of in have times arise other not not at do populations be does losses cannot size-dependent we grazing that across However, system- distribution. certain that model size a the the on indicating of effect by detectable treatments, evidence produced two no estimates the found the in We treatments difference S3B). experimental atic undiluted Fig. for and estimated Appendix, this rates diluted (SI With division in the grazing. samples compared or the we sinking mind, in size-selective concern as such processes, olre al. et Fowler picoeukaryotes. the for for for productivity not primary productivity in pattern primary the C govern of centration fg 290 Values Shaded of mean. ratio series. carbon-to-volume the for time of 16-y SD Val- the 1 Synechococcus climb. for within to averages are continues climatological regions rate are on division plotted abundant picoeukaryote more ues as are even picoeukaryotes summer, 130), the to 20 than days average (year winter late -3 -1 -1 -1 Primary productivity (mg C m d ) Daily division rate (d ) Concentration (cells mL ) from rises MVCO at picoeukaryotes of concentration The 0.5 1.5 10 0 5 0 1 2 3 0 1 2 010102030360 300 240 180 120 60 0 rmr rdciiyfrpcekroe and picoeukaryotes for productivity primary ) iiinrate, division B) ( concentration, (A) in cycles seasonal of Comparison 10 C B A 5 mL u hybcm rsial unmee in outnumbered drastically become they but Synechococcus, h sebaeo iouaytsa MVCO at picoeukaryotes of assemblage The r hs eotdi e.1,wt h aiu estimate maximum the with 16, ref. in reported those are 010102030360 300 240 180 120 60 010102030360 300 240 180 120 60 −1 Synechococcus Picoeukaryotes ntewne to winter the in d −1 d −1 n nrae taiyfo April from steadily increases and ) Day ofyear ,bfr elnn owne val- winter to declining before ), µm 000cells ∼50,000 −3 oeta hne ncl con- cell in changes that Note . nthe In Synechococcus. Synechococcus mL −1 nJune. in but scl iiincnb iie ylwtmeaue 6 1.For 21). (6, temperatures low by Such limited winter. be the can in division lowest cell climates, temperate a as and in picophytoplankton summer over of typical the division is rates seasonality in and vital highest concentration are notably, and rate Most pat- composition timescales. identified community of have variety their we yet in plankton, terns diverse taxonomically of Controls. Abiotic Discussion picoplank- of throughout rates zero roughly hourly all are day. the loss the and low, winter, are division, the is rates growth, In net rate loss ton most S5). and division Fig. are Appendix, division daily (SI patterns daily when fall) the when these and in year (summer groups, value of highest peak both times a at For to evident 3B). day (Fig. the growth throughout evening net whereby gradually pattern rises dramatic picoeukaryotes dawn rate less although the the after similar In in h a examined. observed 15 see is year and sud- pattern every 10 a same between for with The rate coincides 3E). loss night cell (Fig. at in growth suggests decrease 3A). rate population den (Fig. division net night hourly this at of that increases estimates and our concentra- with day picoeukaryote Comparison the average, during on decreases that, tion indicate MVCO at smaller volume be (cell fall to volume late (cell the tend in months cells summer Picoeukaryote the S4 ). during Fig. Appendix, (SI rate division 1 to (Fig. coupled year tightly the remaining throughout well, as 0.16 near cycle of remains seasonal rate SD size. growth an net population with daily the in zero series, changes typically time entire rates daily the division corresponding For daily Estimated the 2). exceed (Fig. far d 60 by rate sion rmtemdladcl yl-ae siae o h picoplank- the for rates estimates cycle-based division ter cell work at hourly and model previous between exam- rates the picoeukaryotes, correspondence from only vital the good process in for shown validation rates has patterns division our uncover daily Although to ined scale. able subdaily also a were we data, Patterns. Diel 2C). (Fig. year typical a 19). of (18, that to cus program equal MARMAP nearly is the productivity Picoeukaryote from aver- summer obtained on estimates based region, age the C for productivity mg 2 primary 8 total (Fig. of main- August rate and picoeukaryote steady and spring winter, roughly the the a in in tains dramatically zero rises near productivity values primary From (17). al. of et ratio multi- carbon-to-volume then approximate fg We an the 238 day). by of given product mode any this the plied on by attained distribution value size minimum volume population the cell the used and pattern of we concentration, Following product (here, annual cell the MVCO. rate, calculated the first division at we climatological estimate (16), productivity al. can et primary Hunter-Cevera we picoeukaryote rate, in division and tion, in S1D). Fig. bimodal Appendix, volumes (SI frequently cell S1A (mean is eukaryote Figs. April Appendix, but small the early unimodal the to in March rate usually of division is rela- distribution daily negative community size and a size The is cell picoeukaryotes. or there mean response composition, between physiological community tionship a in reflects change pattern a this whether mine eas icvrda nulpteni elsz distribution size cell in pattern annual an discovered also We rmteesaoa atrsi elsz,cl concentra- cell size, cell in patterns seasonal these From hntelte si lo u sgetrtruhu otof most throughout greater is but bloom in is latter the when Prochlorococcus µm −3 smaue for measured as , hnst h ihtmoa eouino our of resolution temporal high the to Thanks h iouaytsaeacmlxassemblage complex a are picoeukaryotes The .Ti aecrepnst 8 fthe of 18% to corresponds rate This C). ,afaueta u oe captures model our that feature a S2), and 7.Hul hne ncl concentration cell in changes Hourly (7). d −1 ∼1.75 B h osrt,teeoe olw a follows therefore, rate, loss The . and irmnspusilla Micromonas Synechococcus C). µm 3 .Wiew antdeter- cannot we While ). m NSLts Articles Latest PNAS −3 ∼0.5 n 16 and ∼1 d −1 µm ouain we population, ewe June between 3 n larger and ) Synechococ- yDuRand by µm | 3 (SI ) f7 of 3

ECOLOGY Picoeukaryotes Synechococcus 1,000-fold increase in concentration during the bloom, blooms A B earlier during warmer springs and later during cool springs 1 1 (20). Because the small eukaryotes do not exhibit as dramatic

) a change in concentration, it is difficult to discern a trend in -1 0 the timing of their bloom. We have, however, observed an (d 0 annual change in the cell size distribution. Each spring, the small eukaryotes initially span a wide range of cell sizes, then Net growth rate -1 -1 undergo a transition to an assemblage that is dominated by 0 5 10 15 20 0 5 10 15 20 cells less than 2 µm (SI Appendix, Fig. S2). The timing of this transition appears to relate to temperature in the same way 1.5 C 1.5 D that the timing of the Synechococcus bloom does (SI Appendix, Fig. S6). That is, warmer springs correspond to earlier changes in picoeukaryote community composition. We do not yet know ) 1 1

-1 what species dominate the assemblage either before or after the (d transition. 0.5 0.5 Biotic Controls. On summer days, the picoeukaryotes at MVCO Division rate, model 0 5 10 15 20 0 5 10 15 20 appear to experience minimal resource limitation. Daily divi- sion rate is more variable in the summer than in the winter, but the magnitude of the estimates reported here is bound 2 E 2 F to surprise some plankton ecologists. The picoeukaryotes at MVCO are dividing at rates comparable with some of the highest

) 1 1 rates reported for the group in culture and incubation experi- -1 ments [1.78 d−1 (22), 2.43 d−1 (23), 3.36 d−1 (24)]. Notably, (d

Loss rate 0 0 our estimates of picoeukaryote division rate in the summer are approximately twice those estimated for Synechococcus (20). This difference in division rate is consistent with the results of 0 5 10 15 20 0 5 10 15 20 our dilution series experiments as well, where division rates were Hours after dawn Hours after dawn on average 2.5 times higher for picoeukaryotes than for Syne- Fig. 3. Hourly rates of (A and B) net growth, (C and D) division, and (E and chococcus in the same bottle (SI Appendix, Table S1). In the F) loss for the picoeukaryote and Synechococcus populations. Each curve climatology, division rates for the two groups are well aligned represents a distinct year, and hourly values are averaged across all days for the first 120 d of the year, but as the Synechococcus division of the year. Years with fewer than 180 d of data (2003 to 2006, 2014 to rate plateaus, the picoeukaryotes continue to divide more rapidly 2015) are excluded. Each bold line is the average across all years consid- for another 100 d (Fig. 2). Despite these continued high and ered. Picoeukaryotes exhibit consistently higher rates of net growth at night increasing division rates, the picoeukaryote population is held than during the day, corresponding to a decrease in loss rate. A similar pat- in check throughout summer, suggesting significant top-down tern with lower amplitude is apparent for Synechococcus. Note that the Synechococcus model from Hunter-Cevera et al. (20) excludes the first 6 h control. Their high division rates and relatively low net growth after dawn. indicate that the picoeukaryotes contribute more to primary productivity than their standing stock would suggest. In partic- ular, the annual pattern in picoeukaryote primary productivity the picoeukaryotes, daily division rate increases with increasing reflects large changes in division rate and cell size, so it is not as temperature between March and July (Fig. 4A). This relationship closely aligned with cell concentration as that of Synechococcus suggests that the picoeukaryote population growth is temper- (Fig. 2 A and C). ature limited during that period. Division rate on fall days is Synechococcus can be up to 10 times more abundant than noticeably lower than on spring days at the same temperatures, the picoeukaryotes at MVCO during summer. Given their rel- indicating another limiting factor. ative scarcity, the picoeukaryotes seem to be strongly preferred The relationship between division rate and sunlight avail- by the grazer community. This hypothesis is supported by the ability (Fig. 4B) neatly complements that between division rate results of our dilution series experiments, where picoeukary- and temperature. Between August and December, division rate otes suffered higher grazing rates than Synechococcus in all decreases linearly as daily radiation drops. It is likely that incubations (SI Appendix, Table S1), as well as by laboratory sunlight availability is responsible for the steady decrease in results that suggest that Synechococcus is a poor-quality food division rate observed in the fall and at least partially respon- source (25). sible for the decline in picoeukaryote concentration observed over the same period (Fig. 2A). It is important to note that

because our data cannot identify individual species, changes ) 3 3 January -1 in division rate may not correspond to physiological responses ABMarch within a species. Instead, the seasonal changes we observe might reflect seasonal shifts in community composition. It is 2 2 May arguably all the more noteworthy that this diverse assemblage July exhibits systematic responses to changes in temperature and sun- 1 1 September light. Moreover, these patterns are very similar to those of the November taxonomically distinct Synechococcus observed with the same

Daily division rate (d December methods (6, 16). Division in these two picoplankton groups 0 0 appears to be temperature limited in the spring and light limited 010200 100 200 300 Mean daily temperature (°C) -2 in the fall. Mean incident radiation (W m ) If division rate is limited by temperature in the spring, we Fig. 4. Relationship between daily picoeukaryote division rate, (A) tem- expect the timing of the annual spring bloom to depend on perature, and (B) incident solar radiation. Values plotted are climatological water temperature. Synechococcus, which can exhibit up to a averages for each day of the year across all years in our time series.

4 of 7 | www.pnas.org/cgi/doi/10.1073/pnas.1918439117 Fowler et al. Downloaded by guest on September 30, 2021 Downloaded by guest on September 30, 2021 iiinrt siae eotdhr sta ftmn.Acon- A timing. of that 3 is of rate here division reported tinuous estimates Loss. rate and division Growth of Timing incubation-free developing continue to ours. in need like of approaches the importance and the work emphasize findings situ does natu- These dilution their would rate. underestimated it division If have picoeukaryotes, ral may sample. of studies growth previous diluted the that on mean more which effect a of an have in benefits indeed reduced the be shared mutualisms, leaki- in would “accidental” that Lastly, result suggests can and lysis. 36) production resources and (13, resource picoplankton’s colleagues grazing in and through bot- ness Morris cycling undiluted of work nutrient in the to stimulated due be tles the even that in affect suggested may (14) results negatively al. picophytoplankton et filtrate which Weinbauer of rate. aldehydes, growth preparation phytoplankton polyunsaturated the that of Stoecker found growth release (35). (15) the picoeukaryotes inhibit al. including may et seawater phytoplankton, of the is sample of mortality a sug- diluting while work that recent dilution, phytoplank- However, gests of dilution. that by independent is affected the is proportionately method of rate One series division bottles. dilution ton undiluted the from of are assumptions model-derived interest- highest estimates situ is the rate in experiments, It these division which highest. in that, are during note rates to period ing loss the and include division not picoeukaryote did they October, two these pro- between carbon distinguish of cannot or fate methods lysis pathways. the our to for but due implications duced, phytoplankton is important their mortality has of phytoplankton grazing those Whether match (27). roughly rates prey to growth per seen microzooplankton grazing popu- been and predator (34), have more in activity and and fluctuations size rates seasonal lation be contact can increased There to predator. phytoplank- lead of lysis. can in viral concentrations As in ton higher 33). increase (26, experiments, an summer dilution to in higher due the generally rate part also loss in are increased least rates that at Grazing then is likely summer seems the It in rate (32). loss lysis that with viral found correlated from positively experiments is series rate picophytoplankton dilution division other phytoplankton to of than (0 meta-analysis lysis A widely viral (31). range to susceptible may to picoeukaryotes more smallest observed be the been that evidence has some with lysis 100%), mor- viral Picoeukaryote from (29–31). lysis tality with viral and correlated grazing be zooplankton would processes unlikely is physical it to rate. since division due patchiness, loss spatial or that causes biological advection to cal- than primarily that attributed rather be assumption consis- picophytoplankton can our rates is other supports loss coupling culated also of annual tight It observations the (26–28). This and tracks communities 1). theory closely (Fig. with that rate rate tent there division loss Indeed, daily in magnitude. in expect in change pattern would similar seasonal be one a to days), is rate (e.g., loss and timescales division short on stant olre al. that et Fowler is which the phytoplankton, in eukaryotic size in succession knowl- division in current in cell given doubling rapidly of unlikely is edge dividing than scenario to then this more us However, and evening. are lead day cells might the information during individual 0.57 this that to the together, 1.74 decreases MVCO, believe Taken from dramatic At (e.g., S1C). show (37). size Fig. can dark cell primarily distribution after mode division size hours in that in few suggest patterns field first picoeukary- diel the the of in Observations in and h. occurs culture 24 of in course otes the over divisions eas u iuineprmnswr odce nJn and June in conducted were experiments dilution our Because micro- are picoplankton in loss of drivers biological main The con- relatively remains concentration cell picoeukaryote Since d −1 n usinrie ytehigh- the by raised question One orsod oapoiaeyfour approximately to corresponds µm 3 in IAppendix, SI h atta h antd ftepteni osi greater is loss in pattern observe. the we of for pattern the than magnitude loss during picoeukaryotes the the active for explain that more could fact it are The night, MVCO If at day. at than the grazers day during of rates majority grazing across increased the (48–50) consistent reported internal decreased have not and or studies (45–47) is (43) different and behavior night stimulation however, This at light species, rate (44). than to loss rhythms day due graz- circadian that in the whether patterns during indicates activity, diel exhibit higher ing analysis microzooplankton average Many our 3E). on (Fig. and is rate, MVCO at loss and sion from 3A). little (Fig. surprisingly year varies to rate year The growth days. net many diel in over pattern that average resulting such we MVCO after noisy, clear At and become 42). variable only (41, patterns are envi- abundant concentrations coastal less cell are in well, discern that as especially taxa to however, for hard time, or are ronments of patterns periods Consistent short 40). over 39, experimental (7, with abundance validated daily been to opposed yet as not rate, methods. have division rate, hourly Note hypothesis. of division the estimates test work directly our pattern to Our that necessary experimen- the be but largest. would picoeukaryotes, explain work are of tal could diversity cells the sunset mechanism across the circadian observed at this when or divide that is cue might demonstrates that environmental picoeukaryotes The because any the sunlight. of simply instead, of therefore, result but day picoeukaryotes, the full clock, the prac- be a in in not after and division may largest volumes, peak of is larger timing will at size consistent division are cell cells construction, mean early of tice, the by majority in because, highest the still when is is occurs rate This simulations division our evening. yet in day, division division the the is, throughout That though to availability. even able sunlight are dynamics (Eq. simulations daily function separated model observed phases the the distinct Additionally, match in (38). occur gaps synthesis by DNA and mitosis hl hr r oiebeproso iewe ycrn is synchrony when and time increases typically of population picoeukaryote periods the evident, noticeable not are there and 2 While (Fig. series time our throughout tures a be and to picoeukaryotes seem and community. micrograzer division the rapid of item extremely prey with of preferred Compared capable series. are time they the productiv- throughout primary long picoeukaryotes the region’s ity the the and detail stock, to short in disproportionately standing contribute over describe their to and community Relative discern picoplankton observa- timescales. to the situ able of From in environment. are behavior of variable we highly days dataset, a many 3,200 in this to years analyzed 16 hours spanning have from tions, we exhibit of ranging Here, site periods rates years. MVCO over vital NES-LTER changes the and systematic at composition, picophytoplankton community the abundance, The Conclusions export. carbon to for implications investigation their in further and patterns causes warrant diel their The have rates determine (54). others growth dependent still net light and be picoplankton not picoeukaryote 53), less to (52, rendered the shown radiation been or lyse ultraviolet destroyed was to by are activity infective however, virus photosynthetic viruses, particular Other that pusilla. a found (51) for al. required et the Brown on lysis. effect stronger a have grazers that picoeukaryotes. idea the with sistent hne naudneaetersl fcagsi ohdivi- both in changes of result the are abundance in Changes picoplankton in patterns diel for looked have studies Several ept hs ifrne,tecnetaintaetre of trajectories concentration the differences, these Despite viral from arise could loss in pattern same the Alternatively, 1, osntdpn on depend not does Methods) and Materials Synechococcus Synechococcus tMC hr ayfea- many share MVCO at NSLts Articles Latest PNAS i.S7). 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ECOLOGY decreases at the same time as that of Synechococcus. We inter- Cevera et al. (6) assumed that cells smaller than twice the minimum size, pret this synchrony to be a result of the two groups’ similar vmin, could divide. The two resulting daughter cells would be placed into responses to abiotic conditions. Warm sunny days that support the smallest size bin. This produces an increase in biomass through division, the growth of cyanobacteria also support picoeukaryote growth. which, though very small, is physically unreasonable. To prevent this prob- Conversely, poor environmental conditions lead to less popu- lem, we prohibit division of cells with volume less than v*, the volume of the largest size class that is less than 2v : lation growth in both groups. Thus, even with different vital min  rates, grazers, and population sizes, the two communities roughly ≤ 0 for vi v*, track one another in terms of their changes in concentration. b δ(i; θ) = (vi − v*) [1] For this reason, it is reasonable to model the picophytoplank- δmax otherwise.  1 + (v − v*)b ton as a single group in many scenarios. If one is interested, i however, in the role that organisms play in their ecosystem or Here, δ(i; θ) is the proportion of cells in size class i that will divide, and b the transfer of carbon through the food web, our work illus- and δmax are elements of the parameter vector, θ. The growth function we trates that the picoeukaryotes and cyanobacteria have striking use is the same as that in Hunter-Cevera et al. (6). differences. As in Hunter-Cevera et al. (6), the model accommodates two distinct populations, each with its own size distribution and growth and division Materials and Methods functions. This choice was made in order to accommodate days when the observed cell size distribution is bimodal. On different occasions at MVCO, Data Collection. The MVCO offshore tower is the inner shelf study site of the we see the fit model describe 1) two relatively distinct populations (SI NES-LTER. Observations were made by two autonomous submersible flow Appendix, Fig. S9), 2) two populations with overlapping size distributions cytometers, FlowCytobots, which have been alternately deployed at the (SI Appendix, Fig. S10), or 3) one clear population and a second widely dis- MVCO offshore tower since 2003. The resulting time series includes hourly tributed population, which may account for background noise (SI Appendix, records of cell concentrations as well as light scattering and fluorescence of Fig. S11). While the two-population construct does not represent the actual individual cells. These signals can be used in combination to identify Syne- chococcus and the picoeukaryotes and to estimate cell volumes. Olson et al. diversity of the picoeukaryote assemblage, it is sufficient to capture the cell (55) has details on FlowCytobot design and operation. FlowCytobot data size distributions we observe. were processed according to methods described in Sosik et al. (5). Environ- The dynamics of the two populations are simulated simultaneously, and mental data were also collected from MVCO, including water temperature the sum of the two size distributions at each hour is used to define the recorded by MicroCat conductivity, temperature, and pressure sensor and probability vector in a Dirichlet-multinomial distribution. The model has 14 incident short-wave radiation recorded by an Eppley pyranometer at the parameters in total. For each day, we fit the model to the observed size MVCO meteorological mast (41◦ 20.9960 N, 70◦ 31.600 W). Short gaps in distributions by finding a maximum likelihood estimate for θ. When fit to the environmental data were filled according to the methods described in simulated data, our model correctly identifies each of the subpopulation’s Hunter-Cevera et al. (16). growth and division functions (SI Appendix, Figs. S9–S11). Given the vector of most likely parameters and the observed solar radia- Matrix Model. We use a model to estimate division rate by following the tion, we use the matrix model to project our simulated populations forward same steps described in Hunter-Cevera et al. (6). Cells are classified into dis- for one full day. We then use the simulated cell concentrations at 0 and 24 h crete size classes based on the log of their volumes. The probability of a to calculate the daily division rate for the assemblage. Daily net growth cell dividing in half is assumed to depend only on cell size, and the prob- rates are calculated similarly from smoothed cell concentration observa- ability of a cell growing into the next size class is assumed to depend tions. We used a 48-h running mean in order to reduce tidal effects and on the immediate light availability. Any cells that do not grow or divide noise. Because our model does not include any cell mortality, we then com- remain in the same size class until the next time step. The volume bins pare the estimated division rate with the observed net growth rate and take and the size of the time step (10 min) were chosen so that cells could the difference to be the loss rate for the assemblage. be expected to undergo only one transition at a time. We use 66 volume bins, ranging from 0.03 to 256 µm3, to accommodate the range of small Data and Code Availability. All MATLAB scripts for the division rate model as eukaryotes observed at MVCO. The transition matrix is a function of time, well as the data presented in this manuscript are available online (56). t, and the model parameters, θ; its structure is summarized in SI Appendix, Fig. S8. ACKNOWLEDGMENTS. We thank E. T. Crockford, E. E. Peacock, J. Fredericks, Z. Sandwith, the MVCO Operations Team, and divers of the Woods Hole The model we use here differs from that of Hunter-Cevera et al. (6) in two Oceanographic Institution diving program. This work was supported by NSF ways. First, we allow the eukaryotes to divide at any time of day. The tran- Grants OCE-0119915 (to R.J.O. and H.M.S.) and OCE-1655686 (to M.G.N., sition matrix is therefore only indirectly dependent on time of day through R.J.O., A.R.S., and H.M.O.); NASA Grants NNX11AF07G (to H.M.S.) and the amount of light present. Second, the division function was modified NNX13AC98G (to H.M.S.); Gordon and Betty Moore Foundation Grant slightly to prohibit the division of cells in the smallest size classes. Hunter- GGA#934 (to H.M.S.); and Simons Foundation Grant 561126 (to H.M.S.).

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ECOLOGY