the establishment of fucoid zonation on algal-dominated rocky shores: hypotheses derived from a...

Introduction

It has been argued that approaches which scale eco-logical performance using simple morphological vari-ables (e.g. Littler 1980; Poorter & Remkes 1990;Steneck & Dethier 1994; Nielsen et al. 1996) will pro-vide more useful generalizations than thoseapproaches which rely on defining numerous species-specific traits (Hay 1994). If this is the case, it shouldbe possible to construct models based on a limitednumber of assumptions that are capable of makinggeneral predictions about ecological phenomena.

Vertical zonation patterns formed by canopy-forming fucoid algae on rocky shores have a longhistory of investigation. On sheltered shores in thenorth-east Atlantic, Pelvetia canaliculata (L.) Dcneet Thur. is typically considered to be the specieswhich is distributed highest on the shore, followedby Fucus spiralis L., Ascophyllum nodosum (L.) leJol. and Fucus serratus L. as the mean level of lowwater at spring tides is approached (e.g. Schonbeck& Norton 1978). Several hypotheses have beenadvanced to explain algal zonation, based on desic-cation tolerance (e.g. Zaneveld 1937; Schonbeck &

Norton 1978; Dring & Brown 1982), competition(e.g. Lubchenco 1980; Hawkins & Hartnoll 1985;Chapman 1990) and interactions with grazers (e.g.Underwood 1980). None of the proposed mecha-nisms has been generally accepted (Chapman 1995).The search for generality is complicated by the factthat experimental approaches have often tested foreffects such as competition as a phenomenon with-out revealing anything of the underlying mecha-nisms (Tilman 1987). The demonstration ofcompetition as a phenomenon can say little aboutwhen a boundary between two species will form,where the boundary will lie or how dynamic theboundary might be.

This paper examines whether differences in themorphology of canopy-forming algae are sufficient tocause vertical zonation on rocky shores and considersgeneral predictions about the nature of zonationpatterns that arise from such an approach. The growthrates of different algal species were based on morpho-logical parameters derived from harvested individualsand desiccation tolerances taken from the literature.Algal photosynthesis was modelled in air and in atidal water column of variable depth.

FunctionalEcology 199812, 259–269

© 1998 BritishEcological Society

ORIGINAL ARTICLE OA 000 EN

The establishment of fucoid zonation on algal-dominated rocky shores: hypotheses derived from asimulation model

M. P. JOHNSON,* S. J. HAWKINS,* R. G. HARTNOLL† and T. A. NORTON†*School of Biological Sciences, University of Southampton, Biomedical Sciences Building, Bassett CrescentEast, Southampton SO16 7PX and †Port Erin Marine Laboratory, Port Erin, Isle of Man IM9 6JA, UK

Summary

1. A model was developed for the growth of intertidal algae with photosynthesissimulated both in air and in a tidal water column. Morphological data on dry massper unit area and length–area relationships were used to separate the growth ofdifferent fucoid species. The relative growth rate of fronds at any height on the shoredepended on a trade-off between net photosynthetic performance and tolerance todesiccation.2. The simulated zonation patterns and growth rates were consistent with thoseobserved previously for Fucus spp. and Pelvetia canaliculata.3. The simulated growth of Ascophyllum nodosum was always slower than for the otherspecies. This species did not form its characteristic distribution zones in simulationswithout including further processes in the model. However, Ascophyllum collectedfrom the field could be separated into upper and lower shore morphologies whichformed separate zones when they were simulated in competition with each other.4. Several hypotheses were proposed concerning the relative locations and sharpnessof interspecies boundaries on the shore. Zonation patterns were relatively insensitiveto changes in most model parameters except the desiccation rate.

Key-words: Canopy, desiccation, relative growth rates, thallus specific mass

Functional Ecology (1998) 12, 259–269

259

Materials and methods

DESCRIPTION OF THE MODEL

Photosynthesis has been frequently modelled in cropsusing an exponential attenuation of photosyntheticallyactive radiation (PAR, 400–700 nm) in the canopy andphotosynthesis-irradiance relationships (P vs I curves)for individual leaves (Johnson & Thornley 1984;Loomis & Connor 1992). Given information on respi-ration, the net carbon fixation of a plant in a canopycan be calculated. By altering the description of pho-tosynthesis to take account of tidal fluctuations inwater column depth, a similar approach can be appliedto algal canopies.

A simplifying assumption of no underlying differ-ence between gross photosynthetic performance perquanta absorbed in different fucoids was adopted (seeMarkager 1993). Fucoids are thought to absorb closeto 90% of incoming light, regardless of species(Norton 1991). From similar gross photosyntheticyields per quanta absorbed, the parameters which canbe used to separate the net carbon fixation of differentspecies are thallus-specific carbon and carbon-specificrespiration rate (Markager & Sand-Jensen 1992). If itis assumed that different species of fucoids will havesimilar carbon specific respiration rates, the main dis-criminant of net photosynthesis in fronds becomes thethallus-specific carbon content (g C m–2). To facilitatethe use of field data a standard conversion betweencarbon and dry mass was used. Hence the net photo-synthesis in different fronds was solely dependent onthe thallus-specific mass (TSM, g m–2).

Profiles of light attenuation in submerged algalcanopies show exponential declines in irradiance withdepth (Gerard 1984; Cousens 1985; Holbrook, Denny& Koehl 1991). Strictly speaking this decline in irradi-ance with depth does not occur evenly across the PARband. However, changes in light quality with depth areprobably unimportant as it is likely that fucoids have aflat action spectra for photosynthesis, similar to thatreported for Laminaria saccharina by Dring (1982). Insubmerged plants the attenuation owing to the watercolumn must also be taken into account. Assumingminimal surface reflection of incident irradiance:

Iz = Ice(–λz – κT

AI), eqn 1

in which Iz is the irradiance at depth z (µmol photonm–2 s–1), Ic is the irradiance at the top of the canopy(either corrected for overlying water if the canopy isfully submerged or equal to the incident irradiancewhere the canopy reaches the water surface, µmolphoton m–2 s–1), z is depth below the water surface(m), λ is the attenuation coefficient of sea water (m–1),κ is the attenuation owing to algal canopy (TAI

–1,fronds assumed to be vertical while submerged) andTAI is the cumulative thallus area index from top of thecanopy to depth z (m2 thallus m–2 sea bed).

The rise and fall of the tide means that the atten-uation owing to water and the canopy are effectively

calculated with respect to different reference points.Attenuation in the water column is calculated withrespect to depth from the water surface, whereascanopy attenuation is calculated with respect to theinterval between the current position and the top of thecanopy when fully extended. The frond surface areaavailable for photosynthesis at any depth depends onthe species-specific growth form.

For a discrete approximation of the light availablefor photosynthesis at different depths, fronds weredivided into segments 0·01 m in length with areas persegment calculated using allometric relationships.This allowed a discrete irradiance profile to be con-structed with the light in 0·01 m steps becoming afunction of the depth of overlying water combinedwith the sum of areas in segments above and includingthe present one. The discrete version of eqn 1becomes:

d max

Iz(s) = Ice(–λ(s–0·5)/100 –κ ∑ Aseg(n)N – κ ∑ Aseg(n)N) ,

d + 1 – s d + 1 eqn 2

in which Iz (s) is the irradiance in segment s (µmol pho-ton m–2 s–1), s is segment number from the surface, dis the depth of water column rounded to the nearest0·01 m (if d > max then d = max), max is the totalnumber of segments in the canopy, Aseg (n) is the frondarea in segment n (1 ≤ n ≤ max) (m–2) and N is thefrond density (m–2). Equation 2 deals with situationswhen the height of the water column exceeds thecanopy height as well as when canopy height exceedswater depth.

With irradiance values calculated in 0·01 m incre-ments, Smith’s (1936) equation can be used to esti-mate the instantaneous gross photosynthesis for asingle frond in the canopy:

d PmaxαIz(n)Psng = ∑ ––––––––––––––– Aseg(d + 1 – n) +

1 √ Pmax2 + (αIz(n))

2

PmaxαIz(0) max

––––––––––––––– ∑ Aseg(n) , eqn 3√ Pmax

2 + (αIz(0))2

d + 1

in which Psng is the instantaneous gross photosynthe-sis of a single frond (µmol C s–1), Pmax is the maxi-mum gross photosynthetic rate (µmol C m–2 thalluss–1) and α is the initial slope of P vs I curve [µmol C(µmol photon)–1].

When plants are exposed to the air by a falling tidethere is some evidence that the photosynthetic rate canbe enhanced (e.g. Johnson et al. 1974; Johnston &Raven 1986; Madsen & Maberly 1990). Exposure inair, however, causes algae to desiccate and eventuallyphotosynthesis ceases as individuals dry out. Thewater content of exposed fronds was modelled as anexponential function of the time in air (Maberly &Madsen 1990):

W = 100e(–DE) eqn 4

260M. P. Johnsonet al.

© 1998 BritishEcological Society,Functional Ecology,12, 259–269

in which W is the remaining water content of the frond(%), D is the desiccation rate (s–1) and E is the timethat the frond has been exposed in air (s).

The initial enhancement of photosynthesis causedby exposure in air followed by the decline owing toexcessive desiccation was modelled for all speciesusing the empirical equation presented for F. spiralisby Madsen & Maberly (1990). Net photosynthesiswas altered by a fraction dependent on the water con-tent of exposed fronds. This produced a multiplier forPmax in eqn 6 which varied from 1·26 in hydratedfronds newly exposed in air to 0 in tissue with watercontents below 16%.

According to Dring & Brown (1982), intertidalalgae can be distinguished by the extent to which dif-ferent species recover to full photosynthesis after des-iccation. Therefore, Pmax during any period ofimmersion following exposure to air was multipliedby a modifying factor. The value of this factor wasdependent on the species being simulated and thewater content of thalli at the end of a period of expo-sure. For example, P. canaliculata was parameterizedto make a full recovery from desiccation down to awater content of 4% (Dring & Brown 1982). Below4% water content the extent of recovery was interpo-lated linearly between no recovery from 0% watercontent to a full recovery from 4%.

A further complication is that a well-developedcanopy may protect fronds from the effects of desicca-tion (Schonbeck & Norton 1979a). Therefore themodifiers to photosynthetic rate and the affects of des-iccation were not applied in cases where the thallusarea index exceeded 2.

The physical environment of the model wasdescribed using sine wave functions for irradiance andtidal height, following the approach of Maberly &Madsen (1990). Day length was fixed at 12 h and thetidal cycle ran independently with a period of 12·43 h.The combination of these two functions defined theincident light and exposure regime experienced byfronds at any defined height relative to low water.

Simulations were run with 15 min time steps. Theinstantaneous photosynthesis was calculated at eachtime step using eqn 3 and using modifying factors forPmax if appropriate. The total photosynthesis in each15 min interval was estimated by trapezoidal integra-tion of adjacent instantaneous rates. Gross photosyn-thesis was converted into net carbon fixation bysubtracting a time invariant respiration rate. This respi-ratory loss was dependent on the dry mass of the frond,calculated using the TSM to convert from frond area:

t+1 t+1

Psn_net = ∫ Psng– ∫ RTSMA, eqn 5t t

in which Psn_net is the net carbon fixation per time step(µmol C), R is the biomass specific respiration rate[µmol C g (dry mass)–1 s–1], TSM is the thallus specificmass (g m–2) and A is the frond area (m2).

Net photosynthesis was summed for all time stepsin a day to give a daily net carbon fixation. This wasconverted into new frond area using a moles carbon tograms dry mass conversion and the TSM:

∑ Psn_netAnew = –––––––– , eqn 6

CTSM

in which Anew is the new area grown in a day and C isthe carbon fraction of frond dry mass [µmol C g (drymass)–1]. Daily changes in frond height were calcu-lated from the new frond area using allometric rela-tionships.

Once the growth of one species at different heightson the shore could be simulated, it was relativelystraightforward to duplicate code and have two sepa-rate species growing together. To calculate the lightclimate at any particular depth the thallus area indexof both species was combined. Hence a tall speciescould reduce the growth rate of shorter species byshading. This allowed an investigation into the effectsof growth rate and morphology on the competitionbetween species. Simulations were run as pairwisecompetitive trials as including all the species wouldhave added computational complexity without materi-ally affecting the results.

DEFAULT MODEL PARAMETERS

The model was set up with parameters based on val-ues in the literature considered typical for a temperaterocky shore (Table 1).

Photosynthetic parameters were chosen to be con-sistent with the range of values in King & Schramm(1976), Chock & Mathieson (1979), Johnston &Raven (1986), Peckol, Harlin & Krumscheid (1988),Hsiao (1990), Madsen & Maberly (1990) andMarkager & Sand-Jensen (1992) and (1996). The car-bon to dry mass conversion assumes a 27% carboncontent in fucoids. This value was used by Atkinson &Smith (1983) in cases where they lacked direct mea-surements and is close to the value of 26·4% C g (drymass)–1 measured for F. spiralis by Maberly &Madsen (1990). Slightly higher values of 38% and35% C g (dry mass)–1 are given for A. nodosum and F.vesiculosus by Vinogradov (1953). These carboncontents are relatively low compared with terrestrialplants, which may reflect an additional mass of salt inmarine species following drying. A canopy attenua-tion coefficient of 0·31 has been estimated for a standof Postelsia palmaeformis by Holbrook et al. (1991).An upright canopy such as grass may have a κ valueof about 0·5 (Loomis & Connor 1992). Maximumpossible attenuation would occur where thallus layerswere in horizontal sheets perpendicular to the incidentirradiance. In such a case the attenuation would be setby the light transmission properties of individual thal-lus layers. Taking a 10% transmittance of incidentlight for fucoids (Norton 1991) the corresponding

261Vertical zonationand algal growthon rocky shores


canopy attenuation coefficient would be 2·3. Given thisupper limit for κ, an initial value of 0·7 was used in sim-ulations. The sea-water light attenuation coefficientwas chosen as representative of moderately turbidcoastal waters, equivalent to a Secchi disk visibility ofabout 3 m. Desiccation rate was chosen from the mid-dle of the range measured by Maberly & Madsen(1990) using F. spiralis apices exposed in the field (D-values from 5 × 10–4 to 18 × 10–4 s–1). The mean PARirradiance in a day is similar to the value quoted byMaberly & Madsen (1990) for April and is also con-sistent with records for mean daily irradiance at acoastal station in Ireland over a period of 30 years(Rohan 1986).

Desiccation tolerances were approximated from thedata in Dring & Brown (1982). Pelvetia canaliculatahad a full recovery from desiccation to 4% water con-tent (using an extreme case). Fucus spiralis and F. ser-ratus recovered from water losses of 85 and 60%,respectively. In the absence of information on A.nodosum, recovery was assumed from desiccation to30% water content. This is the value that Dring &Brown (1982) gave for F. vesiculosus, a species whichoccurs adjacent to A. nodosum on the shore.

The dynamics of fronds recruiting to the shore werenot explicitly tackled as algae were simulated to growfrom germlings 0·01 m long. Growth at a range of fronddensities was simulated with 2000 fronds m–2 used as adefault. The default tidal range was 6 m. In reality thetidal range of a shore will vary as a result of factors suchas the ‘spring-neap’ tidal cycle. These variations werenot included in the model, so the practical terminologyfor tidal heights (lowest astronomical tide, mean low-water springs, etc.) did not apply to simulations and allheights on the shore could be referenced in terms ofvertical distance from the low-water point.

Data on algal morphology were based on samplestaken from a sheltered gully between Langness andFort Island in the Isle of Man (OS grid ref.: SC294 673). A point along the shore was selected at ran-dom as the basis for a vertical transect. Fucoids at thissite can be visually distinguished into distinct verticalbands. Pelvetia canaliculata was uppermost on theshore, followed by F. spiralis, A. nodosum and F. ser-ratus as the mean low-tide mark is approached.

Samples were taken in six locations down the line ofthe transect, representing zones with the followingspecies: P. canaliculata, F. spiralis, F. spiralis–A.nodosum transition zone, high A. nodosum zone, lowA. nodosum zone, A. nodosum–F. serratus transitionzone. At each location all the plants in 0·25 m × 0·25 mquadrats were removed.

After rehydration in sea water for at least an hour,individual fronds were separated and blotted dry formeasurements of length and fresh mass. Fronds weredefined as: ‘any system of shoots and reproductivestructure ultimately derived from a single meristem-atic protrusion of the holdfast’ (Cousens 1984).Photographs of fronds alongside a scale bar were usedfor the estimation of (one-sided) surface area using animage analyser. Dry mass measurements wereobtained after leaving fronds overnight in an oven at105 °C. The length of every individual frond wasmeasured; however, only a representative selectionfrom each quadrat was used for mass and area deter-minations.

Various relationships were derived from the charac-ters measured on individual fronds. The allometricrelationship between length and frond area wasexpressed in the form: ln(area) = a + b ln(length). Theother important morphological relationship used inthe model was the relationship between thallus areaand dry mass (TSM, g m–2).

Results

Allometric relationships were calculated for the dif-ferent species in each quadrat. With F. serratus and P.canaliculata there were too few individuals measuredto plot quadrat-specific relationships so data werepooled from all the locations. Tukey tests (Zar 1984)between pairs of length–area slopes suggested thatdata on F. spiralis from different quadrats could bepooled into a single relationship. Ascophyllumnodosum fronds from 2·5 to 4·3 m above lowest astro-nomical tide (LAT) had similar slopes so a pooledregression was derived. However, A. nodosum frondsin the uppermost location (4·8 m above LAT) weresignificantly different from one of the lower shoresites (P < 0·05), so this quadrat was not pooled with



Table 1. Default parameters used in the model. For parameter origins see text. TAI is the cumulative thallus area index fromtop of the canopy to depth z (m2 thallus m–2 sea bed)

Parameter Description Default value Units

Pmax maximum gross photosynthetic rate 7 µmol C m–2 s–1

α initial slope of P vs I curve 0·05 µmol C (µmol photon)–1

R biomass-specific respiration rate 0·002 µmol C g (dry mass)–1 s–1

C carbon fraction of frond dry mass 2·25 × 104 µmol C g (dry mass)–1

κ canopy attenuation coefficient 0·7 (TAI)–1

λ seawater attenuation coefficient 0·5 m–1

D desiccation rate 1·17 × 10–4 s–1

I∑ daily irradiance 24 × 106 µmol m–2 day–1

words a steeper allometric slope indicates that aspecies had a relatively more ‘bushy’ frond. On thiscomparison Fucus spp. and P. canaliculata were gen-erally more bushy than the low shore samples of A.nodosum (Table 2).

Thallus dry mass and area were plotted on log–loggraphs to check for variations in the TSM with overallfrond size. The relationships clustered around a slopeof one. Therefore a general case of no size dependentdifference in TSM was adopted. All subsequent estima-tions of TSM used means (Table 2).

The simulated growth curves of different specieswere all sigmoid. Examples for F. spiralis are given inFig. 1. The plateau of such growth curves was reachedwhen the respiratory load of shaded tissue equalledthe gross photosynthesis in each frond. Maximumcanopy heights and growth rates varied with height onthe shore. Fronds grown lower on the shore had fastergrowth rates and taller final canopies when comparedwith fronds grown further up on the shore. Densityalso affected the growth curves as fronds seeded atlow densities attained higher final canopies than moredensely packed fronds. The split in slope betweengrowth curves from different densities occurred at thepoint where protection from desiccation was reached(TAI > 2). This point was obviously reached at a lowerfrond height when individuals were more denselypacked.

Before using the morphological relationships givenin Table 2 as a basis for comparing species, the effectsof independently varying allometric slope and TSM

were assessed. In cases where TSM was fixed, thegrowth of a pair of frond types together led to heightdominance by the species with the lowest allometricslope (i.e. the more elongate species). When theallometry of a pair of frond types was fixed, the frondswith the lower TSM grew tallest. Once a species estab-lished height dominance over another it eventuallycaused the shaded species to lose height as the respira-tion cost of shaded tissues exceeded gross photosyn-thesis. When such a height loss was simulated theaffected fronds were assumed to die. The most suc-cessful frond type in pairwise competition wouldtherefore be a species with a low TSM and a relativelyelongate (as opposed to bushy) growth form.

Competition between the fucoids was simulated at60 heights on the shore. With the default parametersgiven in Table 1 and morphological data from Table 2,zones were simulated where one of P. canaliculata, F.spiralis or F. serratus formed the canopy (Fig. 2). Thispattern is the same as observed at Langness except thatA. nodosum forms a canopy between F. serratus and F.spiralis in the field. An understorey of each speciesformed during the first year of simulations. If themodel was left to run for 3 years, competitive domi-nance by canopy plants led to the death of understoreyplants as a result of shading. This process sharpenedthe boundaries between species. Within A. nodosum,the two morphologies grew with different degrees of

Table 2. Morphological relationships for species from different quadrats. Units are mfor frond length and m2 for frond area. TSM is thallus mass divided by thallus area(g m–2). Ascophyllum nodosum quadrat positions are given relative to the height ofthe lowest astronomical tide (LAT)

ln(area) = a + b ln(length)

intercept slope TSM (g m–2)Species group (± SE) (± SE) r2-adj. (%) (± SE)

P. canaliculata (– 0·78 (± 2·24 74 295(all quadrats) (± 1·03) (± 0·43) (± 12)

F. spiralis (– 0·10 (± 2·66 89 239(all quadrats) (± 0·30) (± 0·14) (± 5)

F. serratus (± 0·21 (± 2·85 97 168(all quadrats) (± 0·38) (± 0·24) (± 13)

A. nodosum (– 1·16 (± 3·01 74 461(4·8 m above LAT) (± 0·85) (± 0·40) (± 17)

A. nodosum (– 4·25 (± 1·82 90 572(2·5–4·3 m above LAT) (± 0·06) (± 0·04) (± 12)

Fig. 1. Simulated growth in height of Fucus spiralis at (a) three separate heights onthe shore (1, 2 and 3 m above low water) and (b) three separate densities at a height of2 m above low water (500, 2000 and 8000 fronds m–2).

the others. The coefficient in the allometric equationgives an estimate of how quickly frond area changeswith increasing length. Fronds with a high coefficientcan be considered to have more frond area for a givenlength than fronds with a low coefficient. In other


success on the shore (Fig. 3). The simulated pattern ofzonation reflected the distribution of A. nodosum mor-phologies observed in the field, with the upper zonemorphology forming a fringe at the top of the zoneoccupied by the 2·4–4·3 m above LAT morphology.

The positions of interspecies boundaries on theshore were estimated using linear interpolation. Aboundary between two species was defined by thepoint where canopy heights were equal. The simulatedzone boundaries were relatively insensitive to varia-tion in κ, λ, daily irradiance (I∑) or total frond density(Table 3). The maximum deviation was an increase of0·16 m in the height of the P. canaliculata/F. spiralisboundary associated with high water turbidity. At suchhigh water turbidities (a Secchi disk visibility of≈ 0·5 m) the lower limit of positive frond growth wasdrastically raised from 13·6 m below the low-tidepoint to 1·3 m below low water. Desiccation rates hadthe largest impact on simulated zonation patterns.Removing desiccation from the model preventedzonation patterns forming as the shore was dominatedby F. serratus (Fig. 4). With increasing rates of desic-cation the F. serratus, F. spiralis, P. canaliculata zona-tion pattern was established, as well as an upper limitfor fucoid growth.

Success in competition was determined when onespecies grew taller than another. The degree of com-petitive asymmetry was assessed using the height ratioof a species pair. Changes in frond density affected thetime of onset of competition for light and the time thatdesiccation stress applied. At high density the faster-growing but less desiccation-tolerant plants succeededin competition at slightly greater heights on the shoreas the high densities protected individuals from desic-cation. Conversely, at low densities desiccationbecame relatively more important and upper shoreplants could slightly extend their lower boundaries.These effects of variation in total density are shown fortwo heights on the shore in Fig. 5. At 2·2 m P. canalic-ulata grew taller than F. spiralis until the highest densi-ties were simulated. At low densities, dominance by P.canaliculata was reduced because there was lessopportunity for F. spiralis to be shaded by its competi-tor. By comparison in the default model F. spiralis out-competed P. canaliculata at 2·1 m on the shore. Thiscompetitive effect was enhanced at high densities.Meanwhile at the lowest densities desiccation toler-ance allowed P. canaliculata to form a canopy in azone normally dominated by F. spiralis. Interspeciesboundaries were not affected when the total frond den-sity was held constant while the relative proportions ofdifferent species were adjusted.

Height differentials between species at the start ofsimulations could have profound impacts on the out-come of competition (Fig. 6). For example, P. canalic-ulata was overtopped by F. spiralis at a shore heightof 1·5 m in the default model. However, if the Pelvetiagermlings started simulations 0·004 m taller than F.spiralis, they escaped dominance by fronds of Fucuseven though this species was normally competitivelysuperior at a shore height of 1·5 m. Close to an inter-species boundary the outcome of competition becamevery sensitive to small differences in height betweenspecies (see the lines for 2·1 and 2·2 m in Fig. 6). With


Fig. 2. Zonation patterns established by competitive interactions between species:(a) after simulation of 1 year; (b) after simulation of 3 years. Heights of understoreyspecies represent growth under the canopy dominant at that height on the shore.

Fig. 3. Competitive outcomes between separate Ascophyllum nodosum morpholo-gies after simulation of 1 year. The dotted line represents heights of the lower-shoremorphology (2·5–4·3 m above LAT). The solid line depicts the heights of the upper-shore morphology (4·8 m above LAT).

tence. Even in cases where variation in parameterscaused little change in the position of a zone bound-ary, there were still effects on the rate at which onespecies was eliminated by another (Table 4). Increasesin κ intensified the effect of being shaded, leading togreater competitive dominance. Growth rates wereenhanced by raising the photosynthetic energy input(I∑), which resulted in a more rapid onset of competi-tion. Conversely, increased λ values led to slowergrowth rates and longer periods of coexistence.

Discussion

The model demonstrated how zonation can arisethrough competition for light when cohorts of differ-ent species are separated by their TSM and their toler-ance to desiccation. This implies a trade-off between alow TSM (which aids carbon fixation) and increasedmaterial in the fronds (which appears to aid desicca-tion tolerance; Schonbeck & Norton 1979b). A simplemorphological approach was sufficient to provide amechanism by which faster growing fucoids canshade and eventually exclude slower growing plants(e.g. Hawkins & Hartnoll 1985; Chapman 1990).Zonation occurs because the comparative growth ratesof different species change with position on the shore(e.g. Schonbeck & Norton 1980; F. A. Brown, unpub-lished data, cited in Dring 1982).

Although the model takes a highly simplistic andtemperature-independent view of whole organismphysiology, the calculated daily growth rates weresimilar to values reported in the literature. The initialsimulated dry matter production rate for F. spiralis inthe default model was 4·2% day–1 at the low-tidelevel, falling to 3·4% day–1 at a shore height of 1 m,


Table 3. Species boundaries simulated using hypothetical maximum and minimum values for model parameters. Symbols andunits are given in Table 1; NB signifies that no boundary was formed on the shore. In such cases the entire shore was coveredwith a canopy of Fucus serratus

Height on shore ofParameter range F. spiralis/F. serratus boundary

Parameter Maximum Default Minimum At maximum At default At minimum

κ 2·3 0·7 0·3 1·04 1·05 1·05λ 3·0 0·5 0·1 1·12 1·05 1·05I∑ 24 ×107 24 ×106 24 ×105 1·05 1·05 1·06D 2 ×10–4 1·16 ×10–4 0·0 0·36 1·05 nbTotal frond density (m–2) 40 000 2000 100 1·15 1·05 1·03

Height on shore ofParameter range P. canaliculata/F. spiralis boundary


κ 2·3 0·7 0·3 2·13 2·13 2·14λ 3·0 0·5 0·1 2·29 2·13 2·13I∑ 24 ×107 24 ×106 24 ×105 2·13 2·13 2·14D 2 ×10–4 1·16 ×10–4 0·0 0·85 2·13 nbTotal frond density (m–2) 40 000 2000 100 2·25 2·13 2·05

Fig. 4. Simulated shore occupancy by different species of fucoids as desiccationrate is altered.

increasing distance from a boundary the height differ-entials had to be larger to have an effect. At 2·5 m upon the shore, F. spiralis could not overtop P. canalicu-lata even when Fucus fronds were 10 times taller thanPelvetia fronds at the start of simulations.

Simulations were run using a variety of tidal ranges.This did not have any impact on the proportion ofshore occupied by any particular species. For exam-ple, if a zone boundary occurred at 1·5 m above lowwater when the tidal range was 6 m, the same bound-ary was simulated at 0·25 m when the tidal range wasreduced to 1 m.

The rates at which competitive exclusion of onespecies by another occurred were compared using therelative-height ratios of fronds at the end of a simula-tion period (usually a year). When height ratios wereclose to unity, pairs of species were close to coexis-

2·3% day–1 at a height of 2 m and 0·7% day–1 at 3 mabove low water. In comparison, Fortes & Lüning(1980) measured a growth rate of ≈ 2% day–1 for F.spiralis cultivated at 10 °C. The growth rates of F. spi-ralis plants transplanted to different shore heightsduring September ranged from 1·9% day–1 at the baseof the eulittoral to 1·5% day–1 at the top of the eulit-

toral zone (F. A. Brown, unpublished data, cited inDring 1982). There is a greater variety of measure-ments for linear growth rates of algae in the field.Unfortunately, the fact that simulated growth curvesfor fucoids were sigmoid prevents any valid compar-isons with linear growth rates. An example of a sig-moid-type growth curve for a stand of algae is givenby Baardseth (1955) for A. nodosum.

The morphological relationships measured atLangness generally agree with the limited amount ofdata available from other locations. Jones & Norton(1979) gave TSM values of 167 g m–2 and 169 g m–2 forF. serratus and F. spiralis, respectively. However, aTSM of 400 g m–2 can be derived for F. spiralis fromRobertson (1987). Clearly there is a need for morefield data to characterize the scales of variation in TSM

and length–area relationships. Other areas where moredetail would be desirable include the role of sunflecks(e.g. Wing & Patterson 1993) and the description ofspecies response to variable desiccation rates. In themodel, all species had the same desiccation rate eventhough desiccation rate is correlated with the surfacearea to volume ratio of fronds (Dromgoole 1980).Assuming that TSM and the surface area to volumeratio of fronds are negatively correlated, this impliesthat low-shore species will dry out faster than uppershore species. This process can be expected to rein-force the zonation hierarchy produced in simulations.

The use of a simulation model means that assump-tions have been quantitatively formalized and are moreamenable to falsification. At the same time the use ofmathematics ensures that the assumptions are inter-nally consistent and that zonation can be shown toarise under a variety of circumstances. The generalityof the model can be extended by examining hypothe-ses derived from simulations run with different param-eter values (Table 5). Although these additionalhypotheses remain to be formally tested, some of themare supported by earlier work. For example, Knight &Parke (1950) remarked on the stunted appearance ofFucus at the top of a zone (hypothesis a1). Lewis(1964) mentions the greater area of shore occupied byF. serratus at a north-facing site shaded by high cliffs,while Burrows et al. (1954) considered that algal zoneswere raised at a site with continuous rough water andmoist air (hypothesis b6). The zone boundaries wereobserved to sharpen on a newly built jetty over aperiod of years (Clokie & Boney 1980; hypothesis c1).


Fig. 5. Effect of total frond density on the outcome of competition between Pelvetiacanaliculata and Fucus spiralis after 1 year of simulation. A height ratio greater thanone implies that P. canaliculata will eventually exclude F. spiralis at that position onthe shore. In the default model P. canaliculata excluded F. spiralis at 2·2 m above lowwater, whereas F. spiralis eventually dominated at 2·1 m above low water.

Fig. 6. Changes in the competitive outcome between Pelvetia canaliculata andFucus spiralis associated with height differences at the start of simulations at variouslevels above low water. Points below the dotted line imply eventual competitiveexclusion of P. canaliculata by F. spiralis and vice versa.

Table 4. Height ratios of P. canaliculata to F. spiralis at 2·3 m on the shore after 1 year of simulation under various parametervalues. Symbols and units are given in Table 1

Parameter range P. canaliculata/F. spiralis height ratio


κ 2·3 0·7 0·1 2·33 2·04 1·76λ 3 0·5 0·1 1·00 2·04 2·16I∑ 24 ×107 24 ×106 24 ×105 2·14 2·04 1·55


In terms of growth rates A. nodosum is an enigma:how does such an apparently slow growing plantcome to dominate over Fucus in the intertidal?Consideration of this leads to factors which the modelhas so far left out. For example, Ascophyllum may beless palatable to grazers than Fucus (Watson & Norton1987). Simulations essentially described the establish-ment of zonation amongst a cohort of algae recruitedto a bare shore. Demographic factors are likely to playa role in allowing A. nodosum to colonize through acanopy of Fucus (e.g. Keser & Larson 1984). Forexample, given life spans of 3–4 years for F. serratusplants (Knight & Parke 1950), longer life spans for A.nodosum (Åberg 1992) and a limit to the height ofmature Fucus (set by mechanical stress from waves orallocating resources to reproduction), simulationscould ‘grow’ an Ascophyllum canopy through theremnants of a Fucus cohort. Under appropriate condi-tions the Ascophyllum canopy would be tall enoughnot to be outgrown by a cohort of Fucus recruited inthe following year.

Although the model was derived for patterns onshores in the north-east Atlantic, simulations implythat vertical zonation will occur whenever the follow-ing conditions are met: species are morphologicallydifferent, a desiccation gradient exists which is nottoo severe to prevent the growth of algal fronds, rela-tive growth rate is negatively correlated with TSM,desiccation tolerance is correlated with TSM andfronds recruit to a shore in sufficient densities tocompete for light.

The model presented in this paper should not beconstrued as evidence that the trade-off between des-iccation tolerance and net photosynthesis per unit areais the most important factor in determining patterns of

zonation on the shore. Alternative hypotheses, such asgrazing, have not been properly considered. Well-designed field experiments remain the key to discrim-inating between hypotheses (Underwood 1991). Themorphological approach represents a method of deriv-ing a coherent general model, consistent with fieldobservations, which leads to hypotheses amenable toexperimental testing. There are gaps in the processeswhich any model includes. The purpose of the simula-tions was to investigate the implications of speciestraits in an ecological context rather than to discrimi-nate between hypotheses. As such the option toinclude and assess additional processes, such as graz-ing, nutrient interactions, more complex physiologicalrepresentations, environmental tolerances or demog-raphy, remains open should appropriate data becomeavailable.

Acknowledgements

This research was funded by a grant in the NERC spe-cial topic: ‘Testable models of aquatic ecosystems’.We thank S. C. Maberly for critical comments on anearlier version of the manuscript. S.J.H. and R.G.H.received additional support from the EU under MASTprogramme contract MAS3-CT95–0012 (EURO-ROCK).

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Table 5. Additional hypotheses suggested by the fucoid growth model

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Received 26 April 1996; revised 8 April 1997; accepted 29April 1997



the establishment of fucoid zonation on algal-dominated rocky shores: hypotheses derived from a...

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