Settlement rates of macroalgal propagules: Cross-species comparisons in a turbulent environment

Transcription

1 Limnol. Oceanogr., 55(1), 2010, E 2010, by the American Society of Limnology and Oceanography, Inc. Settlement rates of macroalgal propagules: Cross-species comparisons in a turbulent environment David Taylor, a,* Sebastien Delaux, a,b Craig Stevens, b Roger Nokes, c and David Schiel a a Marine Ecology Research Group, School of Biological Sciences, University of Canterbury, Christchurch, New Zealand b National Institute of Water and Atmospheric Research, Wellington, New Zealand c Department of Civil Engineering and Natural Resources, University of Canterbury, Christchurch, New Zealand Abstract The ability of propagules (fertilized eggs) of five species of fucoid algae (Hormosira banksii, Durvillaea antarctica, Cystophora torulosa from New Zealand, and Fucus gardneri and Pelvetiopsis limitata from Oregon, U.S.A.) to settle and attach was tested in a turbulent, stirred tank. The time taken to reach a steady state of settlement numbers varied between species and turbulence intensities. Normalized steady-state (NSS) settlement numbers showed differences among species. A settlement model, based on principles invoked in the analysis of motion of bed sediments in rivers, was developed. The model indicates that the NSS settlement number depends on two parameters, a propagule Reynolds number and an entrainment function that represents the relative importance of the shear stress experienced by settled propagules and their submerged weight. The inability of this model to collapse the data for all species suggests that the stickiness of the propagules, due to their mucus coatings, plays a significant role in the settlement process. P. limitata (largest propagules) exhibited the least effective attachment to the substratum, whereas F. gardneri (second largest) and D. antarctica (smallest propagules) were the most effective at withstanding hydrodynamic forces that detach propagules. We also model the boundary layer above a flat-bed, driven by linear water-waves, using a skin-friction drag coefficient and show that this study represents the lower end of the shear velocity u * range. However, these experiments capture the main region of variability in long-term propagule attachment, and indicate that most of these fucoid species will have successful settlement only during calm conditions. Successful settlement is the culmination of biological and physical processes and is fundamental to the establishment and replenishment of populations of algae on wave-driven shores (Gaylord et al. 2004, 2006). For many benthic marine species, the processes acting at or shortly after settlement can influence population structure more strongly than later postsettlement processes like competition among adults and predation (Gaines and Roughgarden 1985; Hunt and Scheibling 1997). However, the ability to determine the probability of larval stages successfully attaching to the substratum is often lacking in larval dispersal models (Eckman 1996), and especially so when varying turbulence is considered. Benthic marine species often release large numbers of microscopic propagules into the nearshore environment. Due to their small size, the transport of these often nonmotile propagules is largely a passive process determined by the movement of the water mass (Butman 1987; Mullineaux and Butman 1991; Crimaldi et al. 2002). However, as propagules approach the viscous sub-layer next to all settlement surfaces, the physical properties of the propagules themselves can affect settlement success (Stevens et al. 2008). Once entrained within this narrow, viscous region, motile stages of many benthic invertebrate species can select sites and move towards settlement cues (Abelson and Denny 1997). However, for the nonmotile propagules of many benthic algae, transport, settlement and early postsettlement attachment are mostly passive events driven by the size, mass density, and the stickiness of * Corresponding author: david.taylor@cawthron.org.nz 66 the propagules interacting with the water mass and substratum. Fucoid algae dominate intertidal and shallow subtidal rocky reef communities worldwide (Stephenson and Stephenson 1949) and are key foundation species, affecting diversity and function on temperate shores in both hemispheres (Chapman 1995; Schiel 2004; Schiel and Foster 2006). For these key species, successful settlement requires that the eggs (between 30 mm and 140 mm in diameter [Clayton 1992]) must not only be fertilized and arrive near a suitable settlement surface (Brawley 1992), but also penetrate the benthic boundary layer near the substratum (Hurd 2000; Stevens et al. 2008), adhere quickly and firmly (Charters et al. 1972), and withstand considerable hydrodynamic forces, often on shores ranging from moderate to high energy (Denny et al. 2003; Gaylord et al. 2003; Taylor and Schiel 2003). Predicting particle behavior in this complex environment, therefore, requires knowledge of the physical properties of the propagules and those of the turbulent environment near the substratum. The hydrodynamic regime at the substratum can be an important controlling element in the successful settlement of marine invertebrate larvae (see reviews by Butman 1987; Abelson and Denny 1997), but the effects of turbulent forces on the settlement of algal propagules has received less attention and is crucial to understanding replenishment and connectivity of populations (Schiel 2004). Poor initial attachment of newly settled fucoid propagules has been a feature of most of the studies that have been done to date. Taylor and Schiel (2003) found that,8% of newly settled propagules of Hormosira banksii and

2 Settlement rates of propagules 67 Cystophora torulosa remained attached when exposed to 12 h of wave action after only 1 h of postsettlement time, but.75% of Durvillaea antarctica zygotes remained under the same field conditions. In another study, up to 99% of recently settled propagules of Ascophyllum nodosum were detached by low energy waves,10 cm in height (Vadas et al. 1990). However, in both cases the actual forces involved in dislodgment of propagules were not welldescribed. To understand the relevant processes at the culmination of transport, it is necessary to characterize both the forces acting near the substratum and the physical properties of the propagules. We use a turbulent stirred tank to standardize the physical environment and to test the hypothesis that the propagules of five species of fucoid algae from New Zealand and Oregon, U.S.A., have varying abilities to settle and remain attached under turbulent conditions, and that their differing behavior is due to different stickiness properties of the propagules. A nondimensional model was developed to encapsulate and further test this hypothesis. Methods Turbulence tank To create a turbulent environment with a Reynolds number (Re) approaching those found in intertidal environments we designed and built a propellerdriven stirred tank (Fig. 1). The tank was a 14-cm 3 14-cm 3 25-cm Perspex box containing seawater. A small volume was used to keep the numbers of propagules required manageable. Two opposing 30-mm-diameter thrust propellers were inserted 45 mm into the box at a 45u angle, 65 mm above the tank bottom. Propellers were driven by 7.2-volt electric motors powered by a 5-amp variable power supply. The speed of the propellers was measured using a digital tachometer (Checkline CDT-100HD) and could be varied from 250 revolutions per minute (rpm) to 2000 rpm, yielding shear stress values ranging up to,0.5 pascal (Pa). A fiber-cement settlement surface (Hardiflex TM, James Hardie), known to be very good for algal settlement and used in many field experiments with large brown algal propagules (Taylor and Schiel 2003), was placed on the bottom of the tank (Fig. 1A). Characterizing the flow Velocities in the tank were measured using Particle Tracking Velocimetry (PTV; O Brien et al. 2006), for motor speeds up to 750 rpm. PlioliteH particles (Eliokem), approximately the size of the algal propagules at mm diameter and specific gravity of 1.03, were added to the tank and illuminated using a 10-mm-wide light sheet that ran parallel to the propellers (Fig. 1B), but offset by 20 mm from the center of the tank. High-speed digital video footage of the particles motion at different propeller speeds was processed using Fluidstream 7.01 software (Nokes 2007) to produce timedependent velocity fields in the illuminated slice through the tank. It was expected that the ability of a propagule to settle and remain attached to the substratum would be largely controlled by the turbulent stress in the near-bed region. Fig. 1. (A) Schematic representation of the turbulent stirred tank with the location of the two propellers and the rigid borescope used in the settlement experiments; (B) picture of the stirred tank seeded with particles during the particle-tracking velocimetry measurement. Although the time-averaged mean flow within the tank was significant, near the settling surface itself the flow was dominated by turbulent eddies within the flow. We used an estimate for the magnitude of the fluctuating velocity, u9, in this near-bed region, obtained from the square root of the turbulent kinetic energy (TKE) TKE~ 1 ðu x Þ 2 2z z u y ð u z Þ 2 2 averaged over the bottom 20 mm of the tank, as an estimate of the shear velocity at the bed, u *. The bottom

3 68 Taylor et al. Fucoid egg properties Reproductive portions of adult plants of Hormosira banksii, Cystophora torulosa, and Durvillaea antarctica in New Zealand, and Fucus gardneri and Pelvetiopsis limitata in Oregon, were collected from field sites and refrigerated for 24 h at 4uC. Eggs were liberated from adult plants by exposing them to room temperature and were rinsed from adult plants using 1-mm filtered seawater. The diameters of 100 newly liberated eggs of each species were measured in a Petri dish using a 1-mm micrometer beneath a 1003 binocular light microscope (60.1-mm accuracy). Fig. 2. Linear regression of maximum shear stress measured above the 4-mm 2 settlement areas vs. propeller speed in the tank. shear stress, t, is related to u * by t~ru 2 ð1þ Shear stress estimates were plotted against motor speed, and a linear regression of the data provided shear stress values at propeller speeds.750 rpm to be calculated by extrapolation, due to limitations of PTV analysis beyond these speeds (Fig. 2). This regression had an r 2 of It should be noted that the estimates of u * obtained using this method encapsulate a large amount of uncertainty and, because of this, are used as a broad method of ordering rather than as an explicit measure. Exact values should, therefore, be viewed with some caution. At larger scales (such as that of a natural wave), the rocky substratum environment that we are attempting to simulate should involve significant horizontal flow, which clearly is not represented in the experimental tank. However, when viewed at the scale of a propagule, the environment in which it finds itself can still be viewed as a viscous sub-layer, adjacent to the substratum and embedded within a turbulent flow, which has an intensity that can be characterized by a shear velocity based on the shear stress at the substratum. The interaction of the particle scale, turbulence, and fluid viscosity is encapsulated in the turbulent particle Reynolds number Re p* 5 u * d p /n, where d is the particle diameter and n is the kinematic viscosity (Stevens et al. 2008). The present experimental configuration can generate a range of Re p* from 0 to Therefore, we expect that the experimental tank includes all of the important characteristics necessary to simulate the mechanics of propagules crossing the viscous sub-layer in a naturally occurring flow (Stevens et al. 2008). Sinking rates Sinking rates (U s ) of freshly released unfertilized eggs were measured in a 15-cm 3 15-cm cm Perspex column filled with 1-mm filtered seawater at 18uC using PTV. The density of the seawater, r kg m 23, was measured using an Anton PAAR density meter. Eggs of each species were added to the column by surface injection within 15 min of release from adult plants, and their paths through the column were illuminated using a 10-mm-wide light sheet. Sinking rates were calculated from the time-averaged vertical velocities of an ensemble of eggs identified by the PTV analysis. The sinking of propagules should be Stokesian because a variant of Re p*, which replaces the friction velocity scale with a sinking speed, results in the buoyancy particle Reynolds number (Re p 5 U s d/v, 1); these are very small and so viscosity controls the flow (Crimaldi et al. 2002; Stevens et al. 2008). Under these conditions, assuming the particles are spherical in nature, the sinking velocity of the propagules, U s, is determined by a balance of buoyancy and viscosity and is given by U s ~ 2 ðd=2þ 2 g r p{r 0 ð2þ 9 n r 0 where d is the diameter of the propagule, n is the kinematic viscosity of the fluid (seawater), r p is the density of the propagule, r 0 is the density of the surrounding fluid (seawater), and g is the acceleration due to gravity. Using the measured sinking rates and particle diameters, the density of the propagules could be calculated. Settlement experiments Settlement rates for each species were measured in separate experiments. For each experiment, 3 liters of 1-mm filtered seawater was added to the turbulence tank. Male and female gametes of each species were liberated and washed from plant material, as above, and left to fertilize for 15 min. Eggs were washed through 120-mm plankton mesh and then were counted in five replicate 0.1-mL aliquots under a 1003 binocular light microscope to estimate egg numbers per milliliter. Depending on the density of eggs released from each species, experimental replicates were standardized to use either 50,000 or 100,000 fertilized propagules per experiment in the tank. The propagules were too small to discern with the naked eye, especially as they encountered the settlement surface on the bottom of the tank. To measure the number of them reaching the settlement surface and those remaining

4 Settlement rates of propagules 69 Table 1. Unfertilized egg properties (propagules, n5150) of five species of fucoid algae (sinking rate measured in 18uC seawater using Particle Tracking Velocimetry, 15 min postfertilization). Species Diameter mm (6SE) Sinking rate cm s 21 (6SE) Density (kg m 23 6SE) from Stoke s equation Durvillaea antarctica 29.3(0.4) 0.029(0.0028) (250) Hormosira banksii 60.8(0.6) 0.044(0.0075) (150) Cystophora torulosa 101.0(1.2) 0.062(0.0078) (60) Fucus gardneri 74.0(1.9) 0.037(0.0012) (20) Pelvetiopsis limitata 103.0(1.6) 0.063(0.0032) (20) attached, five replicate 4-mm 2 areas of the substratum were chosen for observation during each experiment. These areas were 20 mm from the center of the tank and were observed using a rigid borescope (Hawkeye Brand) mounted 10 mm above the settlement substratum (Fig. 1A). Counts of settled propagules were done at 60, 120, 360, 540, 720, 900, 1200, and 1500 s after each experiment began. Numbers of settled propagules were measured in the turbulent conditions created by propeller speeds of 0, 300, 400, 500, 600, 750, 800, 900, and 1000 rpm. These correspond to shear stress in the bottom 20 mm of the tank ranging from,0 Pa to 0.42 Pa. To normalize the measured settling numbers, a control experiment was done for each species in which the tank was stirred at 1000 rpm for 5 s after which the propellers were stopped and the eggs were allowed to settle over time, eventually reaching a plateau, or steady state. At this steady state, the number of propagules settled on the settlement substratum was measured and designated as N 0. In later analysis this number was used to normalize the number of settled propagules in the experiments. Results Propagule properties Egg diameters varied from mm [mean 6 SE] (Durvillaea antarctica) to mm (Pelvetiopsis limitata; Table 1), with corresponding sinking rates of cm s 21 to cm s 21 respectively. However, the mass densities deduced from Eq. 2 showed significant variation, with the smallest eggs, those of Durvillaea, having by far the greatest density of 1660 kg m 23. The three species with the largest eggs, Cystophora, Fucus, and Pelvetiopsis, were all found to have about the same density of 1140 kg m 23. Flow characterization The time-averaged velocity fields (vectors) and turbulent kinetic energy (TKE) fields (color) for three propeller speeds (400, 500, and 750 rpm) were calculated from the PTV data (Fig. 3). These data were collected within the bottom 50 mm of the tank. The timeaveraged flow structure shows the presence of mean circulation cells on either side of the tank, the cell on the left possessing a clockwise rotation, and that on the right an anti-clockwise rotation. These cells are clearly driven by the mean flow generated by the propellers. However, it was noticeable that the mean flow was considerably reduced in the center of the tank where the settlement surfaces were located. We have assumed that in the bottom 20 mm of the tank the average turbulent kinetic energy can be used to provide a broad estimate of the shear velocity experienced by the propagules on the settling surface (Table 2). Settlement experiments The shapes of the settlement curves were similar for all species, with the number of settled propagules (averaged across the five 4-mm 2 settlement areas), N(t), rising as a function of time for all five species (Fig. 4). Initially, the number of propagules settling on the substratum increased with time. After a period that depended on species and propeller speed, the number of propagules attached to the settlement surface reached an approximate steady state, indicating a balance between settlement-inducing factors such as particle weight, stickiness of the propagules, and re-entrainment by the hydrodynamic forces acting on the propagules. This number was designated as N ss. During this steady state, propagules were seen touching down and rolling along or near the substratum, but were then re-suspended. All species except Fucus gardneri showed a clear separation of curves over the various stirring rates. Durvillaea antarctica was the only species that had any settlement at 0.42 Pa. Maximum settlement was reached after 500 s for most species except Durvillaea, where it occurred at around 750 s. Cystophora torulosa had the poorest settlement overall, with controls reaching only 7 per 4 mm 2, while Hormosira and Durvillaea had the greatest settlement of around 25 per 4 mm 2. The steady-state normalized settlement number, N* 5 N ss /N 0, for each species is presented as a function of the shear stress (Fig. 5). Except for Fucus gardneri, all species showed a decrease in normalized settlement number with increasing hydrodynamic forcing. In the case of Fucus, clumpingofthe propagules in the low turbulence experiments caused greater numbers of propagules to settle on the substratum than were measured when there was no stirring at all. Settlement model We now develop a framework within which the settlement data can be interpreted. The proportion of propagules that ultimately settle within a turbulent environment, given by the normalized steadystate settlement number, is expected to depend on several physical parameters. We believe that the list below captures all of the important physics of the problem and includes a parameter representing the stickiness of the mucus surrounding the propagules. The proposed key physical parameters are: (1) u * the shear velocity, representative of the shear stress at the

5 70 Taylor et al. Fig. 3. Turbulent kinetic energy (TKE) field (color) and velocity field (vectors) averaged between t 5 0 s and 33 s in the bottom 50 mm of a slice parallel to the plane of the propellers and 20 mm distant from the center of the tank for different propeller speeds: (A) 400 rpm (maximum mean velocity cm s21), (B) 500 rpm (4.11 cm s21), and (C) 750 rpm (6.58 cm s21). substratum; (2) Us /ut a ratio of the settling velocity of the propagules to a turbulent velocity scale representative of the turbulence in the bulk of the tank; (3) d the propagule diameter; (4) n fluid kinematic viscosity; (5) r fluid Table 2. Turbulent kinetic energy (TKE) averaged over the bottom 20 mm of the tank for four different propeller speeds. The shear velocity, u*, is estimated as the square root of the TKE. Propeller speed (rpm) Average of TKE over the bottom slice (cm2 s22) u* (cm s21) Bottom shear stress (Pa) density; (6) er(sg 2 1)gd3 the frictional resistance force of the propagules in contact with the substratum. Here sg is the specific gravity (rp /rf) of the propagules, and e is their coefficient of friction; (7) S a stickiness parameter measuring the force of attraction, per unit area of contact, between a propagule and the substratum. A simple dimensional analysis leads to the following functional dependence Nss u d u2 ru2 Us,,, ~f N ~ ð3þ n e(sg {1)gd S ut N0 The last of these parameters is a measure of how effectively the turbulence in the bulk of the tank, or environment, can mix the propagules throughout the water column, and is well-known from studies of suspended

6 Settlement rates of propagules 71 Fig. 4. The number of settled zygotes (61 SE) vs. time for several propeller speeds (shown as average shear stress, Pa), for DA) Durvillaea antarctica, CT) Cystophora torulosa, HB) Hormosira banksii, PL) Pelvetiopsis limitata, and FG) Fucus gardneri. Note difference in y-axis scale across graphs. sediment loads in rivers (Henderson 1966; Nokes and Wood 1987). If this parameter is very much less than unity, then the propagules can be expected to be uniformly mixed throughout the water column and this parameter will have no effect on the number of particles encountering the bottom viscous sub-layer. The turbulence in the water column is likely to exceed the shear velocity scale near the boundary. For our data, using the shear velocity as a lower bound estimate for u t leads to an estimate of U s /u t which is one to two orders of magnitude less than unity. Thus, the propagules will always be well-mixed through the water column and we can neglect the effect of this parameter on the settling process. Therefore, Eq. 3 reduces to N ~f Re p, E f, E s ð4þ where Re p is a particle Reynolds number, E f 5 u 2 /[e(s g 2 1)gd] is an entrainment function that represents the ratio of the shear stress attempting to detach propagules from the substratum and the frictional resistance that acts to withstand this entrainment, and E s 5 ru 2 /S is an entrainment function that represents the ratio of the shear

7 72 Taylor et al. Fig. 5. Number of settled zygotes (normalized by the maximum number of settled propagules over time at 0 rpm) vs. shear stress in the bottom 20 mm of the tank. stress and stickiness force per unit area. The first two of these variables are essentially the same as those that appear in the well-known Shields diagram (Henderson 1966) that arises in the analysis of noncohesive sediment motion on the bed of a river. The Shields diagram predicts the threshold of sediment motion, the form of bed development such as ripples or dunes, and the ultimate suspension of bed sediments. However, the analysis of settlement of propagules on a solid substratum is somewhat different to the sediment problem. In the sediment problem, the bed is comprised of a densely packed layer of sediment grains that interact and can aid one another to prevent motion. In the case of propagule settlement, the propagules are essentially independent and isolated on the settlement substratum. The problems also differ due to the choice of shear velocity. In the parameters in the Shields diagram, the shear velocity is formally defined by Eq. 1, whereas here we are unable to measure this parameter and, hence, must use a representative turbulent velocity scale near the settlement surface. The fundamental difference between the two problems is the additional parameter in the propagule problem that represents the importance of the stickiness of the mucus. In an attempt to quantify the effect of the stickiness parameter we now develop a simplistic mechanistic model of the detachment process that will allow us to reduce the number of parameters in the problem. Consider a single propagule of roughly spherical shape in contact with a smooth, horizontal settlement surface. The boundary layer adjacent to such a surface is comprised of two regions. Away from the boundary the flow is turbulent and the velocity has a logarithmic profile given by u~ u k ln z z 0 for 5n u vzvd ð5þ Here k is von Karman s constant, z is the coordinate perpendicular to the boundary, z 0 is the distance from the boundary at which the idealized velocity given by the law of the wall goes to zero (Schlichting and Gersten 2000), and d is the thickness of the boundary layer. Embedded within the turbulent boundary layer, and adjacent to the boundary, is a laminar, or viscous, sub-layer. This layer extends a distance of,5 n/u * from the surface (Tritton 1988). Its mean-velocity profile varies approximately linearly with z (Landau and Lifchitz 1959). Thus u~ u2 n z 5n for 0ƒzƒ u We will consider only the drag force acting on the propagule that attempts to cause the propagule to move from the settlement surface. This drag force is primarily viscous in nature for the particle Reynolds number likely to be encountered in the field. For a particle far from a boundary in a uniform flow this force can be derived theoretically and shown to be equal to 3pmdU. Assuming that this drag force has a similar dependence on viscosity, particle diameter, and velocity for a particle in a velocity gradient adjacent to a solid boundary, and taking the velocity at the center of the particle as an appropriate velocity scale, according to Eq. 6 this force is proportional to rd 2 u 2. Two forces are present that resist these destabilizing forces the frictional force proportional to the weight of the particle, and the force due to the particle stickiness. Thus, the total resisting force is given by er(s g {1)gd 3 zsd 2 We propose that the relative importance of the destabilizing forces to the resisting forces can be represented by a single dimensionless parameter defined by ð6þ ð7þ

8 Settlement rates of propagules 73 Fig. 6. Normalized steady-state settlement number, N*, plotted against E T for the five species. The stickiness parameter is assumed to be zero for all species. Fig. 7. Normalized steady-state settlement number, N*, plotted against E T where the stickiness parameter, S *, has been chosen to ensure that all data points collapse onto a single curve defined by the species Pelvetiopsis limitata, which is assumed to have no stickiness. ET ~ ð8þ e(s g {1)gdzS=r and that E T replaces E s and E f in Eq. 4. In addition, despite the fact that the propagule is located within a laminar sub-layer where viscous effects are important, the scaling of the velocity within the viscous sub-layer, specified by the influence of the external turbulent boundary layer and given in Eq. 6, ensures that the fluid viscosity does not appear in either the destabilizing or stabilizing forces. The implication is that the particle Reynolds number should not play an important role in the physics. Certainly, the dependence on the particle Reynolds number in the Shields diagram is relatively weak when compared with the dependence on the entrainment function (Henderson 1966). Therefore we propose a simplified version of Eq. 4 given by N ~f ET ð9þ Finally, we assume that the friction coefficient is the same for all species of propagule. Without this final assumption it is not possible to quantify the relative importance of stickiness for each of the species. Under this assumption Eq. 9 becomes where u 2 N ~fðe T Þ ð10þ u 2 E T ~ (s g {1)gdzS and S ~ S ð11þ er Because r and e are assumed constant across all species, S * is proportional to S. If Eq. 11 is a valid parameterization of the propagule settlement problem, the experimental data will lie on a single curve in the E T -N * plane, independent of species. Figure 6 shows the experimentally determined normalized steady-state settlement number plotted against the total entrainment function, assuming that the stickiness parameter is zero for all species. Clearly the data do not lie on a single curve. For each data point in Fig. 6 a value for S * was deduced that caused all of the data to collapse onto a single curve (see Fig. 7). In this process the least sticky species, Pelvetiopsis limitata, was assumed to have an S * value of 0. Table 3 presents the average stickiness parameter required to collapse the data for each species. Also listed is the standard deviation deduced from the range of S * values computed; assuming that E 5 1, we show the ratio of propagule weight to stickiness. The results show a significant spread for most of the species. This is partly due to the small number of data points and the fact that N * is similar for all species at low shear velocities, whereas their behavior diverges at higher shear velocities. Although this analysis is rather coarse by its nature, it at least provides an ordering of species stickiness that is consistent with field observations. Durvillaea and Fucus are the most tenacious and, hence, have the stickiest propagules, while Pelvetiopsis, the species with the largest propagules, is most easily removed from the substratum due to low levels of stickiness. The ratio of stickiness to weight also provides a similar result, in that Hormosira, Cystophora, and Pelvetiopsis are more reliant on propagule weight to remain on the substratum, whereas stickiness is most important for Fucus and Durvillaea propagules. Application to field conditions The physical environment in a wave-driven coastal region is somewhat different to the idealized tank flow in the laboratory. In the intertidal zone, wave motion will cause horizontal motion of significantly longer horizontal length-scale than the tank near the substratum onto which propagules must settle. The flow near the substratum will be unsteady by nature due to the intrinsic oscillatory flow beneath the waves. However, it is expected that a quasi-steady turbulent boundary layer will exist, driven by the horizontal motion near the bottom

9 74 Taylor et al. Table 3. Modeled stickiness parameter, S*, and the ratio of stickiness to weight for each species, based on the assumption that the mucus of Pelvetiopsis limitata is not sticky. Species Mean value S * (cm 2 s 22 ) SD S* (cm 2 s 22 ) S* : weight Durvillaea antarctica Hormosira banksii Cystophora torulosa Fucus gardneri Pelvetiopsis limitata caused by passing waves, and an idealized flow model will persist (Landau and Lifchitz 1959). The friction velocity, u *, is of particular importance in boundary-layer turbulence by providing a velocity scale that characterizes the near-boundary turbulence, but in a wave field it is more straightforward to predict the outer flow velocity. If the topographic complexity of the substratum is ignored and the assumption is made that the motion beneath the waves can be modeled using linear inviscid theory, the slowly varying horizontal flow generated by the wave motion will exert a shear stress on the seabed that can be empirically deduced from a skin-friction drag coefficient C f. This coefficient relates the surface shear stress t to the free stream velocity, U, on the outer edge of the boundary layer by t~ru 2 ~rc f U? 2 ð12þ or p u ~ ffiffiffiffiffiffi C f U? ð13þ where the local outer flow speed U is deduced from inviscid, irrotational wave theory. Estimates of C f are of the order of 0.01 depending on roughness of the substratum (Reidenbach et al. 2006b). Hence, an outer flow velocity of 1ms 21 implies a friction velocity of 0.1 m s 21. The shear velocities calculated for various wave amplitudes and water depths are based on a friction coefficient of 0.01 and a typical wavelength of 20 m (Fig. 8). It can be seen that the shear velocities in the field strongly depend on both wave height and water depth. However, based on the range of laboratory shear velocities over which significant changes in settlement success occurred, it is logical to conclude that successful propagule settling of the species considered here is unlikely to occur in the field except in relatively calm conditions. Discussion Models of fucoid algal dispersal generally show shortrange dispersal over ecological time, and yet the known dispersal extremes are often larger than predicted (Gaylord et al. 2002; Kinlan et al. 2005). The biological basis for categorizing fucoid algae as short-range dispersers is related to their large propagule size (relative to kelps, for example), lack of mobility, and not having an obligate planktonic development. At the same time, it is recognized that basic knowledge of propagule properties and their Fig. 8. Friction velocity u * (cm s 21 ) as a function of water depth (m) computed from inviscid, irrotational wave theory. The curves correspond to different wave heights 0.2, 0.5, 1.0, 2.0 (m). The friction coefficient is 0.01 and the wavelength is 20 m. effect on successful settlement are fundamental for reliable models of dispersal and population connectivity (Reed et al. 2000; Gaylord et al. 2002; Kinlan and Gaines 2003). Our initial approach to this problem was to test the properties of propagules within a controlled laboratory experiment without the added complexities of the natural environment. Through direct observation of settlement on a planar surface, clear differences were seen in the settlement rates of five fucoid species. These differences were attributable to the propagule characteristics of the different species. One point of interest is that there was no overall correlation between propagule size and settlement success. The largest eggs (Pelvetiopsis limitata) were least resistant to detachment by hydrodynamic forces, whereas the smallest (Durvillaea antarctica) and second largest (Fucus gardneri) were most resistant. We surmise that the stickiness and, therefore, the mucus characteristics of the eggs, is the key factor in explaining differences among species. Settlement and attachment Propagules of all fucoid algae produce an extra-cellular mucus soon after fertilization, the amount and hardening time of which can have significant consequences on subsequent postsettlement attachment (Vreeland et al. 1993). Whereas the extreme wave forces of the intertidal environment are known to influence the distribution and abundance of adult stages of intertidal biota (Denny et al. 1989; Gaylord et al. 1994; Blanchette 1997), less is known about the direct effects of wave forces on the settlement of microscopic algal propagules. Settlement of propagules on planar surfaces can be broken into two phases (Abelson et al. 1994), encounter or deposition, and attachment. The former is influenced by the frequency of sweeps and eddies that bring propagules to the benthic boundary layer and the viscous sub-layer within

10 Settlement rates of propagules 75 it. Once entrained within the viscous sub-layer, gravitational forces associated with propagule size and density may become important (Eckman 1990) and the stickiness of the propagules themselves can influence their ability to remain attached (Taylor and Schiel 2003). To enhance successful settlement, some fucoid algae preferentially release propagules during periods of low water motion (Gordon and Brawley 2004). Our study supports the conclusion that this leads to greater settlement and attachment. We have developed a scaling framework in which the particle Reynolds number and the entrainment function are the parameters governing the settlement numbers of nonsticky propagules. Our data indicate that this framework is inadequate in describing the settling characteristics of the various species. We suggest that differences in the abilities of propagules of these species to attach under similar removal forces could be explained by variations in the properties of the egg mucus that forms after fertilization, with some eggs being stickier than others. Laboratory vs. field conditions In a natural intertidal setting, fine-scale turbulence is likely to be affected by substratum topography and roughness elements produced by reef biota, but at larger scales the shape of the nearshore environment is likely to be more important (Crimaldi et al. 2006; Monismith et al. 2006; Reidenbach et al. 2006a). However, at close proximity to the substratum, the shape of surrounding organisms is also likely to influence small-scale turbulence and diffusive processes that can affect the path of propagules through the viscous sub-layer (Crimaldi et al. 2002; Reidenbach et al. 2006b; Stevens et al. 2008). Consequently, over intertidal reefs of high structural complexity shear-layer vortices may dominate, as has been shown for wave-dominated flat reefs (Falter et al. 2004), seagrass beds (Cornelisen and Thomas 2004), and coral reefs (Reidenbach et al. 2006a). Flows in the rocky intertidal region are typically very complex and, near the substratum itself, they are dominated by variability in boundary-layer shape and interactions with wave forcing (Denny et al. 2003). The relationship between wave-climate and the characteristic velocity scale u * can be examined by modeling the boundary layer above a flat bed driven by a linear water wave using a skin-friction drag coefficient (Figs. 7, 8). The model indicates that the friction velocities measured in these laboratory experiments correspond to wave-heights of less than half a meter in the intertidal zone. This is without considering the effects of topographically amplified flows (Denny et al. 2003). However, the experiments appear to capture the main region of variability in long-term attachment, at least as formulated here, so this points to most species favoring calmer periods for propagule release and settlement. Although it is important to recognize the role of topography in amplifying flow speeds and accelerations, the work here and in Stevens et al. (2008) suggests that its role in providing small zones of slower flow, or enhanced flow variability, is just as important. A natural extension of the experiments here is to consider the role of variable outer flow. This can be simply achieved by varying the propeller speeds and, with slight modifications to the present set-up, quite complex but repeatable flow time-series can be created. This would enable exploration of the present settlement curves in the context of variable background flow. Stevens et al. (2008) compared how buoyancy, scale, and temporal variability combine to generate conditions favorable for initial settlement. The combination of these two studies would enable stronger quantitative consideration of the biogenic transformation that occurs after settlement, but is challenging due to the fine temporal and spatial scales under these transformations that occur in the field. For passive propagules of fucoid algae released into a turbulent environment, successful contact with the benthos is only the first stage of establishment. Subsequent attachment due to propagule stickiness plays a key role in retaining propagules on the substratum through to the stages where rhizoids develop and form a more permanent attachment. We have found that differences in attachment strength between species can be attributed to differences in egg stickiness and that this characteristic will be critical in the successful establishment of these key, habitat-dominating species along intertidal shores. The tendencies of eggs of some species to clump together, and their relative abilities to secrete mucus for attachment soon after fertilization, are areas highlighted for further fine-scale study. Acknowledgments We thank the technicians in the Fluid Dynamics laboratory of Civil Engineering and in the School of Biological Sciences at the University of Canterbury. We are also grateful to S. Popinet for help with data analyses and invaluable input, J. Ackerman and two anonymous reviewers for providing helpful comments, and B. Menge and J. Lubchenco for support while in Oregon through the use of laboratory space at the Hatfield Marine Science Centre, Oregon State University. 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