Ecology, 95(4), 2014, pp. 1022–1032! 2014 by the Ecological Society of America

Circulation constrains the evolution of larval development modesand life histories in the coastal ocean

JAMES M. PRINGLE,1,5 JAMES E. BYERS,2 PAULA PAPPALARDO,2 JOHN P. WARES,3 AND DUSTIN MARSHALL4

1Department of Earth Sciences, and the Institute of Earth, Oceans, and Space, 142 Morse Hall, 8 College Road,University of New Hampshire, Durham, New Hampshire 03824 USA

2Odum School of Ecology, University of Georgia, Athens, Georgia 30602 USA3Department of Genetics, University of Georgia, Athens, Georgia 30602 USA4School of Biological Sciences, Monash University, Victoria 3800 Australia

Abstract. The evolutionary pressures that drive long larval planktonic durations in somecoastal marine organisms, while allowing direct development in others, have been vigorouslydebated. We introduce into the argument the asymmetric dispersal of larvae by coastalcurrents and find that the strength of the currents helps determine which dispersal strategiesare evolutionarily stable. In a spatially and temporally uniform coastal ocean of finite extent,direct development is always evolutionarily stable. For passively drifting larvae, longplanktonic durations are stable when the ratio of mean to fluctuating currents is small and therate at which larvae increase in size in the plankton is greater than the mortality rate (both inunits of per time). However, larval behavior that reduces downstream larval dispersal for agiven time in plankton will be selected for, consistent with widespread observations ofbehaviors that reduce dispersal of marine larvae. Larvae with long planktonic durations areshown to be favored not for the additional dispersal they allow, but for the additionalfecundity that larval feeding in the plankton enables.

We analyzed the spatial distribution of larval life histories in a large database of coastalmarine benthic invertebrates and documented a link between ocean circulation and thefrequency of planktotrophy in the coastal ocean. The spatial variation in the frequency ofspecies with planktotrophic larvae is largely consistent with our theory; increases in meancurrents lead to a decrease in the fraction of species with planktotrophic larvae over a broadrange of temperatures.

Key words: coastal oceanography; larval dispersal; life history; ocean circulation.

INTRODUCTION

In many marine species with sedentary adults,offspring disperse greater distances than in equivalentterrestrial species, with great impact on regional- andlocal-scale population dynamics (see Kinlan and Gaines2003). There is a great debate around the evolutionarypressures that encourage, in some coastal marineorganisms, the development of the long planktonicdurations that enable this dispersal (e.g., Vance 1973a, b,Christiansen and Fenchel 1979, Levitan 2000; see Plate1). Even among closely related taxa in similar habitats,larval dispersal strategies can differ dramatically. Is along planktonic duration favored primarily for thedispersal it allows or for some other advantage itconfers (Strathmann 1985)? Tempering this debate havebeen the observations that dispersal is often less thanone would expect for a given planktonic larval duration(TPLD) if we assume passive dispersal (Strathmann et al.2002, Levin 2006, Shanks 2009). Broadly, these effortshave discussed the putative advantages of the increased

dispersal caused by a longer TPLD, and found that thedispersal provided by observed TPLD’s is far in excess ofthat needed to obtain benefits of dispersal such asgenetic mixing, finding new habitat, and escapingtemporal fluctuations in habitat quality (Pechenik1999). From this, it has been surmised that long TPLD

is favored for reasons other than dispersal, even as long-distance dispersal significantly alters the population andgenetic dynamics of a species (e.g., Strathmann et al.2002, Riginos et al. 2011).The analyses cited in the previous paragraph have

largely neglected the role of coastal currents inasymmetrically dispersing larvae downstream of theirparents. Coastal regions are influenced by strong (.5cm/s) average nearshore currents (Robinson and Brink2006). A brief consideration of an extremely idealizedmodel of a coastal organism with downstream dispersalfurther suggests that any novel trait that increases thetime a larva spends in the plankton, and thus increasesthe distance mean currents transport the larva down-stream, will reduce the fitness of an individual; begin byconsidering an organism that disperses in a coastalocean in a population subdivided into demes, sensuWilkins and Wakeley (2002) (Fig. 1). Each deme exports

Manuscript received 22 May 2013; revised 20 August 2013;accepted 28 August 2013. Corresponding Editor: S. Morgan.

5 E-mail: jpringle@unh.edu

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(1! a) of its larvae to the next deme downstream (to theright in Fig. 1) and retains a of its reproductive output.An increase in a is analogous to a decrease in TPLD or toan increase in behaviors that encourage local retention.At the upstream edge of the species range (the left-mostdeme in the figure), there is no import of larvae fromfarther upstream. Assume these demes are occupied by ahaploid population with two alleles, A and B, whichmodify the retention to be aA and aB, respectively.Adults carrying allele A produce RA larvae that settle,and those carrying allele B produce RB larvae. Gener-ations are nonoverlapping. Focus on the farthestupstream deme, which receives no larval subsidy fromupstream. The population N1 of each allele will grow ata rate set by R and the fraction a that are retained, so theratio of allele A to allele B in the population in the nextgeneration will be the ratio of NA

1 (tþ 1)¼ aARANA1 (t) to

NB1 (t þ 1) ¼ aBRBNB

1 (t)

NA1 ðt þ 1Þ=NB

1 ðt þ 1Þ ¼ ½ðaARAÞ=ðaBRBÞ'!

NA1 ðtÞ=NB

1 ðtÞ":

Thus, the ratio of allele A to B will increase in theupstream-most habitat if [aARA]/[aBRB] . 1. This resultshows that if allele A increases the downstreamtransport of larvae by decreasing aA, its abundance willdecrease unless there is corresponding increase in RA. Ifthe frequency of allele A falls in the upstream-mostdeme, it will decline in all the downstream demes as longas it does not have a fitness advantage in thosedownstream populations (Kawecki and Holt 2002). Thissimplest model hints that an allele that causes increaseddispersal is only favored if it also is linked to an increasein fecundity (cf. Holt 2003), suggesting that thepersistence of long-distance dispersal in coastal marineorganisms may be a side effect of traits that that increasefecundity or confer some other advantage.To quantify these results in terms of realistic

oceanographic and life-history parameters, we mustconsider a more realistic model that captures the trade-offs between TPLD, fecundity, and dispersal as a functionof observable ocean currents in a spatially explicitdomain that is not artificially separated into discretedemes. The biophysical conditions that allow a longTPLD to be evolutionarily stable will be directlyquantified, making it clear when and why a long TPLD

can be evolutionarily stable. The model is then extendedto study the change in fitness driven by larval behaviorsthat modify dispersal distance to explain a potentialorigin for observed larval behaviors that reducedispersal. Finally, we demonstrate that size-dependentmortality and growth are required for realistic predic-tions of larval size and TPLD, linking these results withthe prior literature. After analyzing the model, itspredictions will be compared to a global data set ofthe frequency of larval planktotrophy and other larvallife histories in order to understand how the modelrelates to observed distributions of larval strategies.

METHODS

A more realistic model of dispersal and fitness

It is unrealistic to model the distribution of mostcoastal organisms as a series of discrete demes exchang-ing a relatively small number of migrants. Instead, thereis a continuous distribution of individuals along thecoast with some probability of dispersal upstreamagainst the mean currents, even as most larvae movedownstream (Siegel et al. 2003, 2008, Mitarai et al. 2008,Pringle et al. 2011). To capture these dynamics, wemodeled a population along a finite extent of coastalocean with spatially and temporally uniform habitatquality. The finite extent of the coastal ocean can bethought to represent that region of coast where theenvironmental conditions are within the physiologicaltolerance of the organism of interest. The size of thedomain was always large enough that our results werenot due to the loss of larvae off the downstream edge ofthe domain; a larger finite domain would not change theresults.

The continuous distribution of the population wasmodeled as a series of discrete contiguous locationswhose size was always much less than the potentialdispersal distance, approximating a continuously dis-tributed population. At each location, the populationdensity and the frequency of alleles was kept as acontinuous quantity, and the population density waslimited by the spatially uniform carrying capacity of thehabitat.

The generations were nonoverlapping. Each adult wasassumed to release R larvae that would return to thecoast and recruit, if population density did not limitrecruitment. Thus, R is net of larval mortality and theloss of larvae that do not return to the coast (e.g.,Jackson and Strathmann 1981), but does not includedensity-dependent reductions in fecundity. The larvaewere moved, on average, a distance Ladv downstream ofthe parents, but with a standard deviation of Ldiff

around this distance due to variations in coastal flow(Byers and Pringle 2006). The dispersal kernel wasGaussian. Results for other kernels are presented inAppendix A.

To test how changes in dispersal affect fitness, weintroduced two alleles, A and B, into the population,

FIG. 1. A simple model of a marine coastal populationdepicted as a series of linked demes, with each deme exporting afraction (1 ! a) of its larvae to the next deme downstream (tothe right), and retaining a fraction a of the larvae within thedeme. The death’s head marks the end of the habitable domain.

April 2014 1023CIRCULATION CONSTRAINTS ON LARVAL MODE

and for simplicity, we assumed the organisms arehaploid, with no mutations. The allele frequency at alocation after settlement was equal to the allelefrequency in the larvae that recruit to that location.The frequency of A and B were inversely correlated dueto zero-sum competition for space among the individ-uals carrying these alleles, a function of the densitydependence in the model as in Wares and Pringle (2008).In each run of the model, A and B differed only slightlyin dispersal and other characteristics. The model wasrepeatedly run to determine the relative fitness of thetwo alleles, sensu the ‘‘invasion fitness’’ of Metz et al.(1992). Details of model numerics and implementationare given in appendix B

Fitness and TPLD; understanding trade-offs

To understand the effect on fitness of a change inTPLD, it is necessary to understand the trade-offsbetween TPLD, the mean and standard deviation ofdispersal distance, and the realized fecundity of anorganism (sensu Caswell 1981). There are three reasonsto include these trade-offs in our study: First, the simplemodel presented in the Introduction hints that there aresignificant interactions between these parameters. Sec-ond, there is empirical evidence and theoretical supportlinking TPLD and dispersal distance (Siegel et al. 2003 fora physical perspective, and Shanks 2009 for a biologicalperspective). Third, there is evidence linking TPLD tofecundity through the interactions of TPLD and theinitial size of larvae, and, for related species, the initialsize of larvae and fecundity (Strathmann 1985).We first considered a sessile organism whose plank-

tonic larvae drift passively with the currents. The larvaeare obligate planktotrophs, and must reach a specificsize to settle. If the larvae are large enough upon release,they will be able to settle directly; this represents directdevelopment.If larvae are released into a coastal ocean whose flow

statistics are statistically stationary over the time larvaeare in plankton, and over the path they travel, then Ladv

and Ldiff can be estimated from observable oceanicproperties (Siegel et al. 2003) as follows:

Ladv ¼ UTPLD ð1Þ

with a random spread around this mean distancespecified by

Ldiff ¼ ðr2sLTPLDÞ0:5: ð2Þ

U is the mean alongshore current, r is the standarddeviation of the alongshore currents around that mean,and sL is the timescale of the fluctuations of thealongshore currents around the mean. More details onthese parameters can be found in Siegel et al. (2003). Allphysical parameters are measured along the path oflarvae, and can be affected by any larval behavior thatalters that path, such as vertical migration, or bychanges in the season that the larvae are released (Byersand Pringle 2006).

Following Vance (1973a) and Levitan (2000), welinked both the time the larvae spend in the planktonand the realized fecundity to the initial size of the larvae;support for these assumptions and descriptions of theirweaknesses can be found in Strathmann (1985) andChristiansen and Fenchel (1979). Their parameteriza-tions for time spent in plankton will be modified to aform that is both easier to relate to the observations inthe literature and is more realistic. In appendix C, weshow how our parameterization relates to theirs, and asa consequence, we make explicit the origin of theapparent disagreement between the results of Vance(1973a, b) and Levitan (2000). The first assumption isthat there is a finite amount of maternal mass that canbe allocated to reproduction, such that if the larvaehalve their mass, then there will be twice as many larvaereleased:

Nrel ¼ Mmat=Slarv ð3Þ

where Nrel is the number of larvae released, Mmat is themass the mother can allocate to reproduction, and Slarv

is the mass of the larvae released. The larvae areassumed to have a mortality m per time in the plankton,and they gain mass at a rate of g per time. The variablesm and g are assumed not to vary with larval size; this isrelaxed in the third section of the Results. The mortalitym includes all non-density-dependent mechanisms thatprevent a larva from successfully recruiting; thus, itincludes drifting offshore away from suitable habitat(Jackson and Strathmann 1981), as well as predationand other sources of direct mortality. At a time t afterrelease, the number and size of larvae are

NðtÞ ¼ Nrel expð!mtÞ and SðtÞ ¼ Slarv expðgtÞ:

If the larvae must reach a critical mass, Scrit, to settle soS(TPLD)¼ Scrit, the TPLD is

TPLD ¼ g!1 lnðScrit=SlarvÞ ð4Þ

and since N(TPLD)¼R, the number of larvae that reachthis mass and thus are competent to settle will be

R ¼ ðMmat=ScritÞ3 exp½ðg! mÞTPLD': ð5Þ

(Post-settlement mortality can reduce R; if spatiallyuniform, it would have the same effect as reducingMmat/Scrit. As we will see in Eqs. 6–8 below, this did not affectour results and we will neglect this mortality for now).There are two important corollaries to the aboveassumptions: First, from Eq. 5, the realized fecundityR increases with TPLD if (g! m) . 0. Second, from Eqs.1 and 2, both the mean and stochastic components oflarval transport increase as TPLD increases.The dispersal and fecundity trade-offs described in

Eqs. 1–5 are for nonoverlapping generations; in Byersand Pringle (2006), these results are extended to specieswith overlapping generations; the main differences arean increase in effective fecundity caused by reproductionover multiple years, and a potential increase in thestochastic component of larval transport due to

JAMES M. PRINGLE ET AL.1024 Ecology, Vol. 95, No. 4

interannual variability in the mean larval transport ineach year.Understanding the impact on fitness of changes in

TPLD in this model can seem daunting, for there are nineparameters to consider: U, r, sL, TPLD, g, m, Mmat, Scrit,and Slarv. This can be simplified greatly with dimension-al analysis (Price 2003). The numerical model onlydepends on the three parameters (Ladv, Ldiff, and R), andthese are functions of only five parameters or combina-tion of parameters (U, r2sL, TPLD, g ! m, and Mmat/Scrit) in two fundamental units (time and length). TheBuckingham-P theorem says all possible solutions ofthis model can then be defined by three nondimensionalparameters (Price 2003). The choice of nondimensionalparameters is not prescribed, and we find the most usefulchoices are:

P1 ¼ TPLDðg! mÞ ð6Þ

P2 ¼ U2=!ðg! mÞr2sL

"ð7Þ

P3 ¼ Mmat=Scrit: ð8Þ

In the numerical modeling, we found that P3 influenceswhether a species can persist by controlling R (Byers andPringle 2006). It does not control the relative fitness ofchanges in TPLD. We did not consider it further exceptto note that the modeling confirms that, all other thingsbeing equal, an increase in P3 increases fitness; i.e., thatif an allele can increase the resources applied toreproduction or decreases the size a larva must reachto settle successfully at no other fitness cost, it willimprove fitness.

P1 is a ‘‘scaled larval duration’’; the TPLD scaled bylarval growth rate less mortality g! m. From Eq. 5, if g! m is negative, an increase in TPLD will decreaserealized fecundity, and if it is positive, an increase inTPLD will increase realized fecundity. P2 is a ‘‘scaledadvection’’; it is the ratio of the fundamental biologicaltime scale of the system (g ! m)!1 to r2sL/U

2, theadvective/diffusive timescale of the system. If the TPLD isgreater than r2sL/U

2, the mean coastal current (‘‘advec-tion’’) dominates the transport of the larvae, and if it isless than r2sL/U

2, the transport by stochastic eddies andother flow variations dominate the transport of larvae.Where the scaled advection P2 is large, the meandownstream transport of the larvae will dominate thedynamics of larval dispersal.The model was run iteratively to determine the fitness

change caused by an allele that leads to a slightlychanged TPLD (numerical details in Appendix B). Allbehavior of this model can be explained by the twoparameters P1 and P2; it does not matter whichcombination of U, r2sL, TPLD, g ! m leads to aparticular set of values for P1 and P2. Doubling (g! m)and halving r2sL and TPLD would produce a model with

the same behavior as leaving those parameters unmo-lested because this change leaves P1 and P2 unchanged.The model was run for P1¼!1.5 to 1.5 and P2¼!2.5 to2.5, and the dimensional parameters are recovered byholding U and r2sL constant and varying TPLD and g!m (this parameter range encompasses the range typicallyencountered by coastal larvae; an expanded range isshown in Appendix A).

Do life-histories patterns in the sea match predictions?

It has long been noticed that there are large-scalepatterns in the distribution of different life-historymodes in the sea (Thorson 1950), but there has beenrelatively little explanatory work linking them to thephysical dynamics of the ocean aside from temperature(Clarke 1992, Pearse and Lockhart 2004, Fernandez etal. 2009, and recently reviewed in Marshall et al. 2012[hereafter DM]). To examine how currents modify thefrequency of larval planktotrophy, we used life-historydata from DM. They gathered life-history data from alarge number of marine invertebrates distributed glob-ally to understand the environmental variables thatconstrain life-history strategies in these organisms; weconstrained our analysis to their records that areadjacent to continental coastlines. Details on the dataselection and geographical distribution can be found inDM and in Appendix D. Circulation and sea-surfacedata from surface drifters compiled by Lumpkin andGarraffo (2005) were used to calculate the circulationcomponents of P2. Following DM, annual averages ofthe monthly mean currents and monthly currentvariability were used; further details are found inAppendix D.

P2 is a composite of physical parameters controllingthe mean and stochastic components of transport (U anr2s, respectively) and the biological parameter growthless mortality (g ! m). This latter term is poorlyconstrained. We assumed that its spatial variation isdominated by temperature; this is plausible (Houde1989, Rumrill 1990, Pepin 1991, Hoegh-Guldberg andPearse 1995), but there are surely other environmentalconstraints on growth, and the functional form of therelationship between (g!m) and temperature is unclear.To cope with this uncertainty we made multiple logisticregressions, each within a narrow temperature range, forthe presence of a planktotrophic larval stage against thelog of U2, r2s, and P2 (Table 1; the log-transformationenhances normality and makes P2 an additive functionof the log of its components). By focusing on data fromwithin narrow temperature ranges, we could focus onthe effects of the physical variables U and r2sindependently of temperature and its effects on growthand mortality. Even within these temperature bands, thevariability of (g! m) must still be estimated to estimateP2. The increase in growth with temperature among abroad range of species is assumed to vary as describedfor within-species variation by O’Connor et al. (2007).Data on the variability of larval mortality with

April 2014 1025CIRCULATION CONSTRAINTS ON LARVAL MODE

temperature is scarce. We assumed that mortality isdominated by predation, and the metabolism ofpredators, and thus, the rate of predation, scales asgrowth does (e.g., Houde 1989, Pepin 1991, both for fishlarvae). These assumptions are hard to formally justify,but no better choice is apparent (see Rumrill 1990).From this, we could estimate how (g ! m) varied withtemperature, but not its absolute value. Further detailsare given in Appendix D.

RESULTS

The relative fitness of a longer TPLD

The results of the modeling are presented in Fig. 2A asa scaled selection coefficient s0. An s0 of 1 indicates that a10% increase in TPLD leads to an s ¼ 0.1 for the allele,and likewise, an s0 of !1 leads to an s ¼!0.1. Thus, s0can be thought of as approximately the slope of a fitnesssurface, where an s0 greater than zero indicates a longerTPLD is favored, and less than zero indicates a shorterduration is favored. The solid curved line in Fig. 2Amarks the boundary between positive and negative s0

and marks a valley in the fitness surface (as indicated bythe arrows). Organisms that start above the line will tendto increase their time in plankton, and thus themagnitude of the scaled time in plankton P1, whilethose that are below it will tend to decrease their time inplankton and the magnitude of P1.An organism with a small TPLD, so the scaled larval

duration P1 ’ 0, is in an evolutionary stable statebecause s0 is negative everywhere around this line. Anyallele that causes a small increase in TPLD will be selectedagainst. Thus, the absence of a planktonic stage isalways evolutionarily stable, and we would expect thatin this model any organism that has a very short TPLD toevolve toward a direct-development strategy, or someother strategy with no planktonic development.

The scaled advection P2 approaches zero where themean current U is zero: This is essentially the limit of noocean currents studied by Vance (1973a) and Levitan(2000). As they found, in this limit, a longer TPLD isfavored (s0 . 0) when the growth rate of the larvae gexceeds the mortality rate of the larvae in the planktonm so P1 . 0. (Their debate over the uni- or bi-modaldistribution of larval sizes is resolved in Appendix C.)When is a longer TPLD evolutionarily stable in the

presence of mean currents? Nowhere that P1 , 0, thus,nowhere that (g ! m) , 0 and a longer TPLD reducesrealized fecundity. However, where P1 . 0 and thescaled advection P2 , ’1.9 (either mean current U issmall or the effective diffusivity caused by stochasticflows r2sL is large), there is a portion of Fig. 2A where s0

is positive. (The limiting threshold of P2 for large P1 isshown in Appendix A: Fig. A1. The precise threshold ofP2 depends on the dispersal kernel; other kernels arealso shown in that appendix). In this region, there is anevolutionary pressure for an even longer TPLD. Thissuggests an evolutionary instability leading to infinitelymany infinitely small larvae (Eq. 3), leading to an infinitefecundity (Eq. 5).These results suggest that, where mean currents are

small or the flow is variable and where larval growthcan exceed mortality, long planktonic durations canendure. Direct development is always an evolutionarilystable strategy. However, this model has severaltroubling aspects. It assumes larvae that are purelypassive, despite much evidence that mean dispersal isless than would be expected for passive larvae. It alsopredicts larvae with either no planktonic dispersal, oran infinitely long planktonic duration and infinitelysmall larvae, which neglects the finite size of actualplanktonic larvae and the presence of many lecitho-trophic larvae with larval durations of several days(e.g., Grantham et al. 2003). We address the origin oflarval behavior in the next section, and in doing so,explain the origin of the results presented in thissection. In the following section, we also address thelimits of the theory at long and short planktonicduration to clarify the origin of larvae of finite size and/or short planktonic duration.

The relative fitness of changes in TPLD, reproduction,and dispersal

To understand why a long TPLD is evolutionarilystable in some limits, and not others, we systematicallyaltered the model by changing one parameter indepen-dently of the trade-offs linking it to the otherparameters, and saw how this affected fitness. Thisserved a dual purpose: If, for example, we altered themean distance the larvae travel downstream Ladv byincreasing it several percent while leaving other param-eters unchanged, we can both judge if Ladv drives theresults given in the previous section, and we can judgethe evolutionary stability of behaviors that alter Ladv

alone.

TABLE 1. Summary table of the relationship between thefraction of marine invertebrate species with planktotrophiclarvae (from Marshall et al. 2012) and the log-transforma-tions of various physical variables that make up P2, alongwith log-transformed P2.

Temperature range (8C) U2 r2 sL P2 N

7.5–11 = (!) = (!) = (!) 3411–15 = (!) 3 = (!) 10715–20 = (!) 3 = (!) 6320–27 = (þ) 3 = (þ) 154

Notes: Temperature ranges are chosen so that the fractionalchange in growth rate expected from the relationship ofO’Connor et al. (2007) is the same over each temperaturerange. N is the number of data points in each analysis. Ticks(=) indicate a significant relationship (P , 0.05), and3’s showno significant relationship; negative (!) and plus (þ) symbolsindicate a negative or positive relationship, respectively,between the predictor variable and larval planktotrophy. U isthe mean currents experienced by the larvae in a Lagrangiansense, r is the standard deviation of those currents (both inunits of m/s), and sL is the Lagrangian decorrelation timescaleof the currents in seconds. Further details of data analysis aregiven in Appendix D.

JAMES M. PRINGLE ET AL.1026 Ecology, Vol. 95, No. 4

Increasing the mean distance the larvae travel Ladv fora given TPLD and leaving all other parameters as onewould expect from Eqs. 2–5 decreases fitness for allpossible parameters (Fig. 2C). This decrease in fitness isgreater as time in plankton increases (jP1j increases) andas the mean currents U increase or the variance incurrents r decreases (jP2j increases). Thus, an increasein mean downstream transport of larvae, within theassumptions of this model, always decreases fitness, andany larval behavior that decreases the mean transport is,all other things equal, favored.

Increasing the time in plankton without changingfecundity, but with changes to both mean and stochasticdispersal as specified in Eqs. 1 and 2, always decreasesfitness (Fig. 2B). The pattern of the decrease of fitness isstrikingly similar to that caused by an increase of Ladv

(compare Fig. 2B to C). This suggests that the maindeleterious effect of increasing TPLD with no fecunditytrade-off is the increase in downstream larval transport.Conversely, the main benefit of increasing TPLD with thefecundity trade-off is that, if (g ! m) . 0, it increasesfecundity (Fig. 2A). Thus, any behavior that decreases

FIG. 2. (A) The scaled fitness s0 caused by a change in the larval duration TPLD for allele B. Where s0 ¼ 1, an allele that causes10% increase in TPLD is selected for with s¼ 0.1. Where negative, an increase in TPLD decreases fitness. The solid line is the s0 ¼ 0contour. The arrows indicate the direction TPLD will evolve over time. (B) As in panel (A), but for a change in TPLD that altersdispersal, but not fecundity. (C) As in panel (A), but for a change in mean downstream distance the larvae disperse, Ladv. (D) As inpanel (A), but for a change in the standard deviation of the larval dispersal distance, Ldiff. The dashed line in panels (B) through (D)is the same as the solid line in (A), and indicates the boundary where a longer TPLD begins to confer increased fitness in a model thatincludes all trade-offs. The horizontal axis displays the magnitude of P2 because if P1 , 0, then P2 , 0. U is the mean currentsexperienced by the larvae in a Lagrangian sense, r is the standard deviation of those currents (both in units of length/time), and sLis the Lagrangian decorrelation timescale of the currents. The parameters g and m are the growth and mortality of larvaerespectively, both in units of time!1.

April 2014 1027CIRCULATION CONSTRAINTS ON LARVAL MODE

time in plankton, but leaves fecundity unchanged, willincrease fitness.Increasing the stochastic component of larval trans-

port Ldiff, but leaving all other parameters as one wouldexpect from Eqs. 1–5 leads to a more complex pattern offitness (Fig. 2D). Increasing Ldiff increases the spread oflarvae released from a single point, and so increases bothdownstream and upstream transport equally. IncreasingLdiff increases fitness when time in plankton is larger(jP1j) and where the mean current U is large or thecurrent variability r is small (P2). These are parameterranges where the downstream transport of larvae by themean currents is important, suggesting that the mainimportance of Ldiff is to counteract the mean down-stream transport of larvae Ladv. Where an increased Ldiff

is favored, it would tend to push a species towardoverlapping generations and iteroparity, for, as dis-cussed in Byers and Pringle (2006), these will interactwith interannual variability in the currents to increaseLdiff.

These results strongly suggest that long planktonicdurations do not persist for the great downstreamdispersal they allow; instead, this downstream dispersalis largely disadvantageous and will be selected against.This evolutionary pressure to reduce mean dispersaland, for some parameter ranges, increase the variabilityof dispersal, suggests selection for a rich set of dispersalbehaviors that should be observable in many marineorganisms, largely in the form of behaviors that reducethe alongshore transport of larvae and traits such asbrooding structures, egg capsules, and gels that increaseretention and reduce dispersal.

Impacts of neglected larval dynamics

In common with Vance (1973a, b), the theorydeveloped in the prior two sections suggests that theevolutionary stable states are either an infinite numberof infinitely small offspring or offspring that spend notime in the plankton. Neither result entirely matchesobserved life histories. Even for planktotrophic larvaewith long TPLD, most larvae are much larger than thesmallest possible size for a multi-cellular organism (Belland Mooers 1997). And many non-feeding larvae havesome planktonic duration, albeit for a time shorter thanplanktotrophic larvae. For example, in Grantham etal.’s (2003) compilation of species along the California,Oregon, and Washington coasts in the United States, themedian time in plankton of planktotrophes was 35 days,and the median for lecithotrophes was 5 days (cf.Mortensen 1921, Todd and Doyle 1981, Emlet et al.1987, Hoegh-Guldberg and Pearse 1995).These deviations from our predictions result from

biological dynamics we neglected. We had neglected thechanges in growth, g, and mortality, m, as larval sizechanges. While this is appropriate to understanding howcirculation alters the fitness of planktonic dispersalstages, it discards a mechanism that limits the minimumsize of larvae. As discussed in Peterson and Wroblewski

(1984), mortality of marine larvae increases as sizedecreases. Kiflawi (2006) and Taylor and Williams(1984) convincingly argue that that the optimal initialsize of larvae Slarv will occur where g¼m (see their Fig.1). When in our simulations we included the power-lawgrowth and mortality curves chosen so that there is anoptimal larval size in the absence of a mean current (U¼0; e.g., see Taylor and Williams 1984, Kiflawi 2006), theresults shown in Fig. 2 are qualitatively unchangedexcept for the presence of an evolutionary stable larvalsize with finite planktonic duration in the parameterspace where we had predicted an evolutionary pressurecausing a runaway to ever smaller larvae. Where there isa mean current, this optimal initial larval size Slarv

occurs where g . m, i.e., at a larger larval size thanwould be expected without currents. Essentially, thedownstream advection acts analogously to increasedmortality. As P2 increases, the evolutionarily stablelarval size increases, and the stable larval durationdecreases, until the optimum crosses the threshold whereshorter larval durations are favored. At that point, noplanktonic larvae are favored, only direct development.We also did not include in the model described in the

Methods some dynamics that tend to promote moderatelarval dispersal. A temporally uniform environment wasassumed, with no stochastic disturbances to habitat, andwe assumed that there is no penalty in settling nearparents beyond that of the density dependence in themodel. The environment is also assumed to be spatiallyuniform, with no small-scale patchiness in habitatquality. These neglected phenomena can provide somefitness advantage to moderate planktonic dispersal (e.g.,Pechenik 1999, Burgess et al. 2013): But, as forcefullyargued by Strathmann et al. (2002), observed planktonicdurations in species with long planktonic durations arefar in excess of those needed to provide the advantage(cf. Strathmann 1980, 1985). However, as they dis-cussed, these phenomena may explain why some specieswith short (less than several days) planktonic durationshave not always evolved toward having no planktonicduration.Lecithotrophic larvae with long planktonic durations

and without facultative feeding are never evolutionarilystable in our theory, because such larvae must be fullyprovisioned to reach critical settlement size at birth, andincreasing their TPLD does not cause an increase infecundity (Marshall and Bolton 2007; Levitan 2000discusses facultative feeding, cf. McEdward 1997). Thisis the case discussed in the last section and shown in Fig.2C, where Ladv is increased without a fecundity trade-off. Their presence suggests either evolutionary con-straints preventing the loss of a planktonic stage anddevelopment of direct development (Jablonski and Lutz1983, Pechenik 1999), or phenomena which favor verylong dispersal distances that we have not identified. Wesuspect that selection for increased offspring sizes post-metamorphosis drives the evolution of lecithotrophy inmany species (Marshall and Morgan 2011). Because our

JAMES M. PRINGLE ET AL.1028 Ecology, Vol. 95, No. 4

model focuses on pre-metamorphic events alone, it isperhaps unsurprising that our model does not predictthe evolutionary stability of lecithotrophy in these cases.

Model predictions and life-history patterns

The frequency of planktotrophic larvae shows asignificant and expected decrease with increasing meancurrents and P2 for all but the warmest temperature bin(Table 1 and Fig. 3, which shows the frequency ofplanktotrophy for the three cooler temperature rangesfrom the logistic regression; further details, includingdata distribution and goodness of fit, in Appendix D).The variation in frequency is large over oceanograph-ically plausible current ranges. As might be expected, theregression suggests that, for a given ocean current thereis more planktotrophy at warmer temperatures (thevertical differences between lines in Fig. 3); however, thisinteraction between temperature and the relationship ofcurrents to planktotrophy is not statistically significantfor the temperature ranges shown in Fig. 3, and itsconfirmation must await more data. As shown in DM,there is an increase in the frequency of planktotrophiclarvae with temperature (their Table 1), suggesting theexpected increase in planktotrophy with increasing (g!m). The relationship between the strength of the variablecurrents r2s and the frequency of planktotrophy is notsignificant in three of the temperature ranges, and runscounter to the theory in the coldest temperature range.

DISCUSSION

The predictions of our model matched the spatialdistributions of life history in the global coastal ocean.As predicted, the frequency of benthic species withplanktotrophic larvae, relative to other life histories,decreased as the scaled advection P2 increased. We alsodetected relationships with the components of P2:increasing frequency of species with planktotrophiclarvae associated with decreasing mean currents U andincreasing growth less mortality (g ! m), to the extentthe latter can be assumed to be controlled by temper-ature.That the effects of mean currents on the incidence of

planktotrophy are less strong in warmer waters isperhaps unsurprising. Species with planktonic develop-ment are most prevalent in warmer waters (DM: Figs. 2and 3), suggesting that these conditions favor thisdevelopmental mode. Warmer temperatures allow morerapid development, and so the negative effects of meancurrents on dispersal and persistence are likely to beminimized under these circumstances. To illustrate,consider that in cooler climes, planktotrophic larvaemust spend much longer in the plankton because of thestrong temperature dependent development rates thatlarvae show. As such, even slight increases in meancurrents will result in large decreases in persistence. Incontrast, planktrophic larvae in warmer waters spend solittle time in the plankton (relatively speaking) that evenlarge increases in mean currents are unlikely to affect

persistence strongly, reducing the importance of dis-persal as a mechanism linking TPLD to fitness (O’Connoret al. 2007).

More speculatively, one might expect that larvalbehavior can more effectively decouple dispersal fromthe strength of mean circulation in warmer waters.Within developmental modes, egg sizes are smallest athigh temperatures and largest at cool temperatures(DM). As such, the pre-feeding, non-swimming phaselasts much longer in cooler climes (larger eggs takelonger to develop in their non-feeding stage, cooler eggstake longer to develop [Marshall and Bolton 2007,Marshall and Keough 2007]). Consequently, the poten-tial for swimming behaviors to mitigate the effects ofcurrents is greater in warmer climes than cooler.Validating this speculation will require quantitativeobservations of the relative effectiveness of behavior atreducing dispersal under different conditions.

The lack of the expected correlation between thevariability of currents (r2s) and the frequency ofplanktotrophic larvae may be driven by the collinearityof the mean and variable currents. The log-transformedvariability in the currents is strongly correlated with themean current (R¼ 0.88 over all temperatures) and is lessimportant to the scaled advection P2 than the meancurrents (as can be seen by the similarity of therelationship to larval planktotrophy of both U2 andP2). This suggests that any relationship between currentvariability and larval planktotrophy is masked by thestronger effect of the mean currents on P2.

In summary, we found that the observed distributionof the frequency of larval planktotrophy is broadly

FIG. 3. The proportion of larval planktotrophy as afunction of the mean ocean currents for the three temperatureranges showing a significant negative relationship betweenmean currents and life history, using percent planktotrophyfrom Marshall et al. (2012). The dotted lines are the 6 standarderror limits for the central temperature range; the other errorlines are omitted for clarity, but are similar in magnitude. Thedifferences between the three lines are not significant to P ,0.05. Further details of analysis are given in the Methods andAppendix D.

April 2014 1029CIRCULATION CONSTRAINTS ON LARVAL MODE

consistent with our theory, documenting a link betweentemperature, ocean circulation, and life history forbenthic species in the coastal ocean. Further examina-tion of these relations must progress on two fronts: first,the inclusion of more species from more coastlines witha broader range of environmental conditions thanMarshall et al. (2012), and secondly, the more detailedexamination of larval behaviors in order to determinethe true mean and variable currents experienced bylarvae, instead of merely assuming the surface current isthe relevant dispersal mechanism (cf. Byers and Pringle2006).

CONCLUSIONS

Extending the work of Vance (1973a, b) and Levitan(2000) to include the effects of ocean circulation, wefound that mean alongshore currents diminish thefitness of planktotrophic larvae. For benthic species onan open coast with limited spatiotemporal variation,direct development is always an evolutionarily stablestrategy. Planktotrophy and long TPLD is evolutionarilystable only when the larval growth rate is larger thanlarval mortality (g ! m) . 0, and that the scaledadvection experienced by the larvae (P2) is small.Marine organisms with planktonic larvae, due to the

long time they drift with the ocean currents, have thepotential for much greater dispersal than similarterrestrial species with passive dispersal of propagules(Kinlan and Gaines 2003, Kinlan et al. 2005). We arguethat great dispersal potential is favored in marine speciesnot for dispersal per se, but for the larval feeding andadditional fecundity allowed by long planktonic dura-tions. When (g! m) . 0, larval feeding in the planktoncan increase the effective fecundity of the adults withouta corresponding increase in maternal investment (cf.Vance 1973a, Taylor and Williams 1984, Kiflawi 2006).

While there are other explanations for planktonicdispersal that either invoke temporal and/or spatialstochasticity in habitat or the need to escape negativeeffects of settling too near parents, they do not seem toexplain the very large dispersal potential of organismswith typical planktonic durations of tens of days ormore (Strathmann et al. 2002; as discussed when weconsidered neglected larval dynamics, these otherexplanations for larval dispersal may explain thepersistence of short larval durations within species withlecithotrophic larvae).However, the observed dispersal of larvae is most

often less than would be expected for particles driftingpassively with the currents (Levin 2006, Cowen andSponaugle 2009, Shanks 2009). Many larval strategieshave been found that decrease the mean distance larvaeare dispersed, either by decreasing exposure of larvae toadvective currents, decreasing the time larvae spend inthe plankton, and/or increasing the stochastic spread oflarvae. Byers and Pringle (2006) found that a dispro-portionate fraction of the species in coastal Oregonrelease larvae in months where the mean currents are aminimum or across months where the mean currentsreverse, serving to both decrease mean larval transportand increase the variability of this transport. Alsostriking are observations of nearshore crustacean larvaealong the West Coast of North America: Many arefound to use vertical positioning behavior to stay withinthe nearshore region with its much slower alongshorecurrents despite strong offshore transport near thesurface (Morgan et al. 2009, Miller and Morgan 2013).This reduction in alongshore dispersal is consistent

with the predictions of our model, where increaseddownstream transport of larvae by mean currentsreduces fitness and any strategies that tends to reduce

PLATE 1. (Left) Tadpole larvae of Ciona intestinalis, which has a typical dispersal time in the plankton of hours to minutes(Svane and Havenhand 1993). (Right) Late-stage larvae of Concholepas concholepas, with a planktonic stage of 3–12 months thatcan enable long distance larval dispersal. However, C. concholepas also exhibits diel migration and other vertical positioningbehavior that will tend both to reduce dispersal, to enhance its ability to find prey to feed on, and to retain it in nearshoreenvironments (Manrıquez and Castilla 2011). Both larvae are about 1 mm in size. Photo credits: left, Amy Hooper; right, PatricioManrıquez.

JAMES M. PRINGLE ET AL.1030 Ecology, Vol. 95, No. 4

the mean transport of larvae while leaving mortality andtime in plankton unchanged will be favored.Observed patterns of life-history distribution in the

global coastal ocean are found to be broadly consistentwith our prediction, with increased temperature anddecreased mean alongshore currents associated with anincrease in the fraction of species with planktotrophiclarvae.As with most simplified theories of complex systems,

much of what can be learned from this theory comesfrom observations that appear to be inconsistent with itspredictions; this disagreement identifies situationswhere, in often interesting ways, our assumptions arenot valid. A theory is a mechanism to test assumptions.When a species with a long larval dispersal stage isidentified where the scaled advection P2 is large, severalquestions are foremost: Does the larva have behaviorthat can minimize its exposure to the strong currents (orincrease exposure to variable currents) sufficiently toreduce the P2 it experiences? Is the species present atthat location because it is maintained by larval inputfrom a more congenial upstream location? Or can itpersist because of some inter-species competition effectnot included in this model of intra-species competition(e.g., is it a ‘‘weedy’’ species that can only survive whereother species have been eliminated by spatially andtemporally ephemeral disturbances)? Even where thescaled advection is small, it is illuminating to considerthe persistence of larval dispersal stages that do notobviously increase fecundity, as in the case ofmany lecithotrophes.

ACKNOWLEDGMENTS

We thank Rick Lumpkin of NOAA’s Atlantic Oceanograph-ic and Meteorological Laboratory for kindly sharing with usdata from the Global Drifter Project. Funding for J. Pringlecame from NSF awards OCE 0961344 and OCE 1029602; andfor J. Wares and J. Byers from NSF award OCE 0961830. D.Marshall was supported by grants from the AustralianResearch Council. P. Pappalardo thanks CONICYT for itssupport of her doctoral fellowship.

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SUPPLEMENTAL MATERIAL

Appendix A

Sensitivity to dispersal kernel shape (Ecological Archives E095-086-A1).

Appendix B

Numerical solution method (Ecological Archives E095-086-A2).

Appendix C

Reconciling Vance (1973a, b) and Levitan (2000) (Ecological Archives E095-086-A3).

Appendix D

Details of comparison of theory to observed life-history distribution (Ecological Archives E095-086-A4).

Appendix E

Variation of larval growth g with temperature (Ecological Archives E095-086-A5).

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