INTRODUCTION

There is intrinsic value in generating an understand-ing of any ecological system and predation is an intuitively important process influencing the structureand function of populations and communities.However, most research funding is justified on themedium-term (3–10 years) benefits of developing ourunderstanding of ecological systems in order that various environmental issues can be resolved. Studyingpredation can be justified because it involves energytransfer between species, influences community struc-ture and dynamics, and can be affected by changes inhabitat. Furthermore, developing an understanding ofpredator/prey dynamics can help when interpreting theecological importance of temporal changes in moni-tored populations. Large predators, in particular, areoften the more visible components of soft-sedimentecosystems and are more readily valued by the public.

Studying predation can also include direct humanimpacts. Fishing is one of the largest threats to theintegrity of marine ecosystems and the viability of manyorganisms, particularly those with slow rates of growthor reproduction (Dayton et al. 1995).

Eating and avoiding being eaten are fundamentalprocesses that affect the success of individuals andpopulations and thus structure communities. Becauseof this intuitive importance, predation has been one ofthe best-studied and, consequently, well-reviewed biological processes. I will focus on studies involvingfield experiments, the main technique used to assessthe role of predators in influencing the structure of soft-sediment macrobenthic communities. Despite itsintuitive importance, a clear role for predators in influ-encing community structure is not always apparent inexperimental studies. However, we may be under-estimating the broad-scale importance of predation. Inthis paper, I illustrate some of the potential biases inthe information base, particularly with respect to howour perceptions of process are influenced by the scaleof observation/experimentation. This leads to questions

Australian Journal of Ecology (1999) 24, 344–354

Complex role of predators in structuring soft-sedimentmacrobenthic communities: Implications of changes inspatial scale for experimental studies

SIMON F. THRUSHNational Institute of Water and Atmospheric Research, PO Box 11–115, Hamilton, New Zealand(s.thrush@niwa.cri.nz)

Abstract In estuarine and coastal soft-sediment systems, the role that predators play in structuring communi-ties appears to be variable. Attributes of a particular predator that influence its role in structuring the communityinclude: the rate of prey consumption; the behaviour, morphology and mobility of the predator; and, in soft-sediment communities, sediment disturbances associated with feeding. Reviews of field experiments designed toassess the role of predators in influencing the structure and function of soft-sediment communities have concludedthat many of the predators are generalists and there is usually a lack of competitive exclusion. Thus predationstructures communities by many complex and indirect interactions that are often difficult to predict and general-ize. Variations in the apparent strength and role of predation in structuring benthic communities may depend ona variety of ecosystem characteristics and/or aspects of study design. In this paper, I consider whether we havebeen conducting our experiments at the appropriate scales. Five case studies from Manukau Harbour (New Zealand)illustrate how small changes in the spatial scale can affect results, due to predator perceptions and prey mobility.The results of these studies demonstrate the need to identify scales at which predator effects are likely to be important and to fit experiments within the dynamics and heterogeneity of the system being studied. To do this,we need basic information on the natural history, behaviour and spatial and temporal variability of both preda-tors and prey communities. We also need to be specific about scales of measurement when matching theoreticalpredictions to field observations/experiments. Finally, to enhance our ability to generalize from specific studies,we need to gather data that will enable us to both predict and test the importance of predation over a range of spatial and temporal scales.

Key words: direct effects, indirect effects, marine macrobenthic communities, New Zealand, predation, scale,soft-sediments, study design.

Accepted for publication February 1998.

we need to address and some conclusions concerningthe design of research programmes.

PREVIOUS REVIEWS

In soft-sediment habitats, three general categories ofpredators are recognized: epibenthic predators, in-faunal predators and sub-lethal browsers. Each of thesecan have different effects on macrobenthic communitystructure and function. Epibenthic predators are oftenhighly mobile and include mammals, birds, fishes,starfishes and crustaceans. They can be highly selec-tive feeders, probing and extracting individual preyfrom the sediment. In this case, the behaviour and mor-phology of the predator will often determine the com-bination of prey density, size and burrowing depth thatcan be harvested. For example, feeding by shorebirdsis often constrained by their bill morphology whichaffects both the depth of sediment they can reach andthe size and type of prey they can handle (e.g. Reading& McGrorty 1978; Zwarts & Wanink 1989, 1993;Zwarts & Blomert 1992; Piersma et al. 1993). Otherepibenthic predators feed by taking bites out of the sedi-ment surface or by creating jets of water to separate preyfrom the sediment. The feeding of epibenthic preda-tors usually involves some disturbance to the sedimentsurface which can modify sediment topography andlocal hydrodynamics (Nowell & Jumars 1984). Whileindividual feeding disturbances may range from centi-metres to metres in scales, much larger areas can beaffected by aggregations of predators (see Hall et al.1994 for further discussion). Disturbance events associ-ated with predator feeding can, like other disturbanceevents, also expose other infauna to predation and fur-ther influence benthic community composition (Palmer1988; Kaiser & Spencer 1994; Bonsdorff et al. 1995;Norkko & Bonsdorff 1996). In contrast to epibenthicpredators that move over the sediment surface, infaunalpredators burrow through the sediments. Large preda-tory polychaete worms are the most commonly stud-ied, but Ambrose (1991) suggests that nemerteans arelikely to have a larger impact on infaunal abundancedue to their generally higher densities. Larger preda-tory infauna can be the preferred prey of shorebirds andthus have the potential to generate multiple trophic levels within soft-sediment systems (e.g. Commito1982; Ambrose 1984a,b; Commito & Ambrose 1985;Commito & Shrader 1985; Schubert & Reise 1986).Sub-lethal-browsers only ingest a portion of their preyand thus do not directly result in the death of prey.Epibenthic browsers often consume bivalve siphons orthe feeding appendages of polychaetes, while infaunalbrowsers often feed on the portions of animals burieddeeper in the sediment. Intense browsing can result inprey having a reduced growth and reproductive outputor being at greater risk from predation or disturbance

(e.g. De Vlas 1979; Peterson & Quammen 1982;Woodin 1984; Zwarts & Wanink 1989; Irlandi &Peterson 1991; Kamermans & Huitema 1994; Skilleter& Peterson 1994). Zajac (1995) demonstrated, viademographic models, that although the spionid poly-chaete Polydora cornuta showed restricted populationgrowth as a result of sub-lethal predation (by the phyl-lodocid polychaete Eteone heteropoda), this had less ofan effect on their demography than a similar intensityof ‘lethal’ predation. Removal of feeding appendagescan also influence a prey animal’s role in other eco-logical processes. Lindsay and Woodin (1996) showedthat the removal of feeding tentacles of the spionid poly-chaete Pseudopolydora kempi alter sediment-mediatedcompetitive and adult–juvenile interactions.

The main technique used to identify the role ofpredators in structuring soft-sediment communities hasbeen caging experiments that enclose or exclude pred-ators from feeding in small patches of sediment. Thisapproach has a long history (Blegvad 1928) but, likeany technique, it has its limitations. There can bemethodological problems associated with cage artefacts(Dayton & Oliver 1980; Hulberg & Oliver 1980; Nowell& Jumars 1984), replication (Hurlbert 1984; Eberhardt& Thomas 1991) and transient dynamics (Tilman1988; Brown 1995).

One factor that quickly emerged from the earliestreviews of caging experiments in soft-sediment com-munities was the apparent lack of competitive exclu-sion interactions amongst prey (Peterson 1979).Wilson’s (1991) review could find no study conductedin soft-sediments that has documented a dispropor-tionate rise in abundance in the absence of a competi-tive dominant—because competitive exclusion rarelyoccurs in soft-sediments. He argues that paradigms ofcommunity organization based on other habitats offerlittle insight into the structure of marine soft-sedimentcommunities.

Olafsson et al. (1994) tabulated the results of 66inclusion or exclusion caging experiments publishedfrom 1928 to 1991 to update Peterson’s (1979) reviewof the role of epibenthic predators in soft-sedimenthabitats. They classified studies as conducted at < or> 2 m depth, ostensibly to indicate variations in hydro-dynamics and, thus, the potential for cage-associatedflow artefacts to influence results. They also categorizedpredator impacts as ‘strong’ when the contrast betweencontrol and predator inclusion or exclusion treatmentchanged infaunal density by 100%. In < 2 m deep un-vegetated habitats, which they considered most likelyto exhibit flow artefacts, strong effects either as a resultof the inclusion or exclusion of epibenthic predatorswere recorded in 44% of the contrasts (n = 55). Indeeper areas (> 2 m), strong effects were recorded in22% of the contrasts (n = 23). Strong effects of epi-benthic predators were rarest in vegetated sediments(15% of contrasts, n = 27). The authors recognized the

PREDATION IN SOFT-SEDIMENTS 345

limitations of ignoring the details of individual studydesign and location. Nevertheless, their findings sup-port the conclusion of Peterson (1979): epibenthicpredators can have strong effects in structuring soft-sediment communities in shallow unvegetated habitatsbut not in vegetated habitats.

However, the analysis by Olafsson et al. (1994) high-lights the number of studies demonstrating weak or noeffects. One of the striking features of soft-sedimentcaging studies is that frequently no direct negativeeffects of predators are identified (e.g. Reise 1977; Bell& Coull 1978; Virnstein 1979; Thrush 1986a; Raffaelliet al. 1989; Hall et al. 1990a,b). Features of soft-bottom communities used to explain the lack of directnegative effects by predators include: the absence ofdramatic resource monopolization and the generalistnature of many predators and prey (Peterson 1979;Whitlatch 1980), the presence of multiple trophic levels (Commito & Ambrose 1985), and the mobilityof both predators and prey (Thrush 1986a; Frid 1989;Hall et al. 1990b). Predator–prey interactions can alsobe complex because many predators are capable ofswitching among a suite of prey species (e.g. Livingston1984; Mattila & Bonsdorff 1988). Predation is also nota constant; prey availability and mortality can vary sub-stantially on seasonal and larger temporal scales.

The lack of simple negative effects and absence ofmajor changes in community structure apparent inmany studies implies one or more of the following ishappening: (i) predation is not generally an importantprocess directly structuring soft-sediment communities;(ii) complex interactions are common in these systems;and/or (iii) we are using inappropriate or incompletestudy techniques.

Reviewing the ecological literature on predator den-sity manipulations, Sih et al. (1985) concluded thatunexpected, indirect predator-mediated effects arecommon, particularly when: predators prefer competi-tively dominant species; predation intensity is low; orthe prey species is a mid-level predator or habitat dis-rupter. In unvegetated soft-bottom habitats, inter-actions between different size-classes of the dominantprey can also complicate the results of exclusion experi-ments. A number of studies demonstrate that exclusionof large predators increases the size and biomass ofdominant prey with a concomitant reduction in thedensity of conspecific juveniles (e.g. Reise 1978;Raffaelli & Milne 1987; Wilson 1989; Thrush et al.1994). Multiple trophic levels in some soft-bottomcommunities can further complicate effects, withinfaunal predators released from epibenthic predationpressure excessively cropping other infauna (e.g.Ambrose 1984a,b; Commito & Shrader 1985; Kneib1988). Kent & Day (1983) demonstrated that increaseddensity of adult nereid polychaetes in predator exclu-sion cages suppressed the abundance of juvenile con-specifics, counter-balancing the effect of bird and fish

exclusion. However, despite a general recognition thatcomplex interactions are likely to be important in struc-turing soft-bottom communities (Kneib 1991; Posey& Hines 1991), forecasting outcomes of indirect effectsis difficult without a thorough (and usually unavailable)understanding of how a given system functions.

Attributes of a particular predator that influence itsrole in structuring the community include: the rate ofprey consumption; the behaviour, morphology andmobility of the predator; and, in soft-sediment com-munities, sediment disturbances associated with feed-ing. Issues of study design and variations in effects with habitat changes encompassed by these general categories are important, but it is also important to con-sider whether we have been conducting our experi-ments at the appropriate scales.

Functional responses may shape predator–preydynamics (e.g. Murdoch & Oaten 1975), and linkingthe spatial scales of predators and prey is important ifwe are to identify the scales at which predator effectsare likely to be important. Several studies have shownthat predators aggregate in relation to prey, and thatmobile predators respond weakly or not at all at smallscales. Aggregative responses of predatory birds and fishto their prey are stronger at some spatial scales thanothers (Schneider & Piatt 1986; Wilson 1990; Colwell& Landrum 1993; Horne & Schneider 1994). The spatial scales over which predator or prey densities aremanipulated in experiments are usually determined bypracticalities, rather than knowledge of how predatorsrespond to variations in prey distributions over a variety of spatial scales. A decoupling of predator den-sity or attack rate from prey density, particularly at thesmall spatial scales used in experiments, needs to becarefully considered in the spatial and temporal designof experiments.

Linking predator behaviour to prey density highlightsthe spatial heterogeneity of prey abundance. Theo-retical studies have illustrated the potential importanceof heterogeneity in the growth and stability of popula-tions and the diversity of communities over a varietyof scales (e.g. De Angelis & Waterhouse 1987; Kolasa& Pickett 1991; Loehle 1991; Pimm 1991; Legendre1993). Few field studies have explicitly assessed the rolethat predators may play in affecting spatial variance insoft-sediment communities (but see Schneider 1978;Botton 1984). However, Schneider (1992) developedmathematical relationships between predator feedingbehaviour and spatial distributions of prey. Predatorbehaviour dictated by prey density (i.e. prey removalcorrelated with initial prey density) was predicted toincrease spatial variance of prey. Conversely, predatorbehaviour dictated by predator density (i.e. aggregativeresponses where prey removal is correlated with itself)was predicted to decrease spatial variance. These pre-dictions were tested with field data on changes in spatial variance of a maldanid polychaete preyed upon

346 S. F. THRUSH

by shorebirds. Observed changes in spatial variancematched predictions at the scale of individual sandflats(0.2–3 km2) but not at the scale of study plots (1 ha)within sandflats. The scale-dependent nature of suc-cess in matching theoretical predictions to observationshighlights the need to be specific about scales of mea-surement.

IMPLICATIONS OF CHANGES IN SPATIALSCALE FOR EXPERIMENTAL RESULTS:SOME EXAMPLES FROM MANUKAU HARBOUR

Changes in spatial scale can influence the results of anytype of study. Given the small scale over which fieldexperiments are usually conducted, this is an impor-tant issue (e.g. Kareiva & Andersen 1988; Levin 1988;Thrush et al. 1997b). Differences in spatial scale maylimit the generality of conclusions as well as explain theapparent inconsistencies in the results of experimentsand surveys. This is illustrated by studies of the eco-logical role of benthic suspension-feeding bivalves (e.g.Black & Peterson 1988; Andre & Rosenberg 1991;Andre et al. 1993; Hewitt et al. 1997a) or macrofaunalrecolonization (Smith & Brumsickle 1989; Gunther1992; Thrush et al. 1996a). In field studies it is usefulto consider three separate components of spatial scale:‘grain’, the area of an individual sample; ‘lag’, the inter-sample distance; and ‘extent’, the total area over which samples were collected. While these descriptionsoriginate from the geostatistical literature (see Isaaks& Srivastava 1989), they have also been applied to eco-logical studies (Wiens 1989; Kotliar & Wiens 1990; Heet al. 1995).

This leads me to discuss aspects of some predationexperiments that emphasize how changes in spatialgrain influence results. These studies were all con-ducted in Manukau Harbour (37°01.39S, 174°49.29E),New Zealand, mainly on the sandflats off WiroaIsland. As the results of many experiments appear tobe contingent on location, a description of this habitatis important. Physical and biological descriptions of theintertidal sandflats that occupy about 40% of the areaof the harbour can be found in Pridmore et al. (1990),Dolphin et al. (1995), Turner et al. (1995) and Bell etal. (1997).

Case study A

During summer, some of the sandflats in ManukauHarbour take on a cratered-like landscape due to thefeeding pits created by eagle rays (Myliobatis tenuicau-datus). To assess the influence of ray disturbance onspatial heterogeneity in macrobenthic communities, weconducted an experiment to assess the recolonization

of feeding pits on two Manukau sandflats: the WiroaIsland sandflat, dominated by bivalves (Macomona liliana and Austrovenus stutchburyi) and Te Tau Bank,a polychaete (Boccardia syrtis) dominated sandflat(Thrush et al. 1991). We found infilling and recolon-ization of these feeding pits occurred rapidly, and didnot result in the spatial heterogeneity generated by feed-ing pits in subtidal habitats (e.g. Van Blaricom 1982;Oliver & Slattery 1985; Thrush 1986b). This studyhighlighted the importance of bedload sediment move-ment on the sandflats and its subsequent influence onpostlarval dispersal (Commito et al. 1995b; Cummingset al. 1995; Hewitt et al. 1996, 1997b; Turner et al.1997).

Case study B

A predator exclusion experiment was carried out that excluded: shorebirds; and rays and shorebirds(Thrush et al. 1994). An important feature of thisexperiment was that we were able to fit our samplingtimes into periods relevant not only to the density ofthe two types of predator, but also to seasonal changesin prey density associated with recruitment. Eagle raysare only present on the sandflat during the summer anddisturb large volumes of sediment when extracting prey,whereas shorebirds are found on the sandflats through-out the year and feed by removing individual preyitems.

The experiment was initially sampled six monthsafter its initiation when rays had been absent from thesite for several months and Macomona liliana (the domi-nant macrofauna) had recently recruited. Nine com-mon taxa, including the three most abundant, showedsignificant treatment effects. However, these weremainly decreases in density in the predator exclusionplots, indicating possible indirect effects. Shorebirdswere the major predator on the sandflat prior to thissampling and they are very size-selective feeders.Significant negative effects were apparent on Macomonaliliana (> 8 mm shell length) and the increasing densi-ties of smaller individuals and species in the exclusionplots were attributed to negative interactions with largeMacomona. Negative effects of large Macomona onsmall conspecifics and other species in the Wiroa sand-flat were confirmed in subsequent experiments (Thrushet al. 1996b; 1997a).

We expected our bird, and ray plus bird treatmentsto produce similar results because the rays had beenabsent from the site and both treatments effectivelyexcluded shorebirds. However, of the nine commontaxa that showed significant treatment effects on thissampling occasion, five taxa showed significant treat-ment effects in the bird exclusion treatment only and all showed edge effects around the bird exclusionplots. The edge effect around the bird exclusion plots

PREDATION IN SOFT-SEDIMENTS 347

effectively increased the area of this exclusion treat-ment, thereby reducing the probability of individualsmoving out of the plot. This emphasizes the importanceof infaunal mobility and its potential to swamp preda-tor effects and that differences in the area occupied byexclusion plots can influence results.

Further sampling was carried out eight months laterwhen ray predation was at its peak and the density ofjuvenile Macomona was low. On this occasion, few indirect effects were found. Thus this study revealedindirect effects of predators that were seasonally depen-dent.

Case study C

Experiments designed to assess the responses of ben-thic macrofauna and epibenthic predators/sedimentdisturbers to variations in the patch size and density ofadults of the venerid bivalve Austrovenus stutchburyirevealed some unexpected effects (Whitlatch et al.1997). While the experiment revealed low mortality, theproportion of nipped Austrovenus siphons observed wasrelatively high (11–37%). Although the percentage ofsub-lethal browsing was unrelated to manipulatedAustrovenus densities, it was related to patch size; 9.0 m2 plots had more than twice the proportion ofnipped siphons as 0.25 m2 plots. A number of studieshave documented the prevalence of siphon-nipping in soft-sediment habitats by conducting small-scale(1–2 m2) field experiments (e.g. Peterson & Quammen1982; Coen & Heck 1991; Skilleter & Peterson 1994).However, these may have underestimated the intensityof siphon-cropping if the sub-lethal predators displaylarge-scale aggregative foraging responses similar tothose found in this study.

Case study D

Intensively mapping the distribution of adult Macomonawithin 12.5 ha of sandflat (Legendre et al. 1997) en-abled an assessment of eagle ray feeding relative to thespatial arrangement of infaunal bivalves (Hines et al.1997). Eagle rays exhibited a non-linear segmentedresponse to prey density, in which ray foragingincreased sharply above a threshold density [about 176Macomona (> 15 mm shell length) m–2], but did notreach satiation. Comparisons of three estimators of preydensity used to map prey distribution indicated thatrays were responding to prey patches on a 75–100 mscale.

Case study E

Cummings et al. (1997) assessed the aggregativeresponses in shorebirds feeding on benthic inverte-

brates, over two spatial scales (experimental 0.25 m2

plots, and a 12.5 ha study site). Densities of Macomona(> 15 mm shell length) were manipulated in 0.25 m2

plots throughout this 12.5 ha study site. Based onknowledge of the foraging behaviour of these shore-birds, the following responses to the experimentallyinduced increases in bivalve density were predicted: (i)shorebirds would discover and then focus their forag-ing on plots with experimentally elevated densities ofMacomona liliana; and (ii) shorebird density within thestudy site would increase during the course of theexperiment. To test these predictions, the density andrate of prey attack by shorebirds were measuredbefore, during, and after the density-manipulationexperiment. Although the shorebirds discovered theexperimental aggregations of prey, there was noresponse at the scale of the plot, or at the larger-scaleof the study site. These results imply that shorebirdsare foraging in Manukau over large scales and not dis-criminating at the smaller scales used in this study. Thehypothesis of a lower limit on the spatial scale ofaggregative response set by the mobility of prey rela-tive to the predator is consistent with available evidence.

LESSONS OF THE PAST FOR FUTURESTUDY DESIGNS AND QUESTIONS

These case studies illustrate how results may varydepending on spatial aspects of experimental design—particularly changes in grain (i.e. plot size). The stud-ies emphasize the need for caution in assuming that theresults from experimental plots are representative ofwhat is happening at different scales. Scaling-up fromm2 cages to hectares of sandflat is unlikely to be a matter of simple multiplication. Changes in the spatialgrain of experiments reveal variation in the strength ofpredator effects related to predator behaviour and themobility and spatial patterns of prey. The spatial lagand extent over which processes are manipulated is alsoimportant. Increasing the distance between plots andthe extent of a study is likely to increase the physicaland biological heterogeneity encompassed. As rates ofpredation and consequent effects on benthic communi-ties can interact with habitat heterogeneity theseincreases can influence study results.

Predator effects are often location dependent. Pred-ation rates and functional responses can differ signifi-cantly between sediment types (Lipcius & Hines 1986;Eggleston et al. 1992). Predators may switch their atten-tion to other prey, or their efficiency in extracting andhandling prey may be influenced by differences in sed-iment characteristics (Quammen 1980; Sponaugle &Lawton 1990). Prey survivorship may vary with refugiaprovided by habitat complexity or co-occurring species(Woodin 1978; Martin et al. 1989; Everett & Ruiz1993; Ruiz et al. 1993; Skilleter 1994). Habitats with

348 S. F. THRUSH

complex three-dimensional structures can also containhigher predator densities and provide refuges for agreater suite of predators (e.g. Davis & Van Blaricom1978, 1982). Nevertheless, a variety of studies demon-strate lower mortality of tethered prey in complex habi-tats in comparison with simple habitats (e.g. Heck &Thoman 1981; Heck & Wilson 1987; Wilson et al.1990). Similar to other types of predators, the effectsof sub-lethal-browsers may interact with habitat fea-tures (Coen & Heck 1991; Peterson & Skilleter 1994)and result in complex interactions (Skilleter & Peterson1994). Micheli (1997) demonstrated that, even in a onepredator – one prey system (the blue crab Callinectessapidus and the hard clam Mercenaria mercenaria), todevelop a mechanistic understanding of predator–preydynamics, an understanding of the interactions betweenhard clam distribution, habitat structural complexity,blue crab density and blue crab predators was neces-sary. Variations in the susceptibility of prey to preda-tors in relation to changes in the spatial dimensions ofhabitat characteristics emphasize further complicationsin the potential for scale-dependent interactionsbetween habitat features and predators and prey(Irlandi 1994; Irlandi et al. 1995).

Manipulative field experiments enable us to observethe response of dynamic systems to small-scale con-trolled perturbations and they have proved invaluablein extending our understanding of the complexity oflocal biological interactions in marine soft-sediments.However, it is important to design experiments that fitwith the temporal dynamics and spatial heterogeneitiesof the system being studied. This will require a furtherfocus on the behaviour of predators and prey, and thespatial and temporal variations in the diet and ener-getics of predators. One of the problems in unravellingthe complex role of predators in structuring soft-sediment populations and communities is that usuallythere is a lack of basic information on the natural history. Yet this information is essential to designingstudies sensitive both to issues of scale (Hewitt et al.1996) and the different effects that can arise from vary-ing biological attributes of predators and prey.

Linking natural history characteristics of predatorsis best developed in the shorebird literature (e.g.Piersma et al. 1993; Zwarts & Wanink 1993; Goss-Custard 1996). An important aspect of the behaviourof prey is mobility; this can influence both preyresponses and our ability to study them. Frid (1989)and Hall et al. (1990b) provide simple models of howanimal movement can swamp predator effects in smallcage experiments. These models assume animals movesmall distances (e.g. mm h–1) by crawling over orthrough the sediment. But, especially in exposed sand-flats, rates of movement are likely to be much higherthan this (Hewitt et al. 1996; 1997b). Movement overlarge distances is possible with animals actively enter-ing the water column (e.g. Dean 1978; Armonies &

Hellwig-Armonies 1992; Armonies 1992; Cummingset al. 1993) or by passive movement with sediment bed-load (e.g. Emerson & Grant 1992; Commito et al.1995a,b; Cummings et al. 1995). The results of cageexperiments in soft sediments are likely to be highly sus-ceptible to the size of the exclusion area when residentsare highly mobile. Post-larval dispersal is very impor-tant in soft-sediments, patterns of larval settlement areunlikely to persist and dictate population and com-munity structure over small to meso spatial scales (< km) in dynamic habitats.

The problem with a purely reductionist approach tostudying ecological systems is that the individual com-ponents are not just bricks in a wall. Indirect effectsplay an important part in structuring many communi-ties, but the mechanisms that operate in a particularsituation are only usually identifiable by a series ofintensive experiments rather than tests of theoreticalpredictions (Fairweather 1990). Reise (1987) consideredthat assemblages organized by weak interactions arelikely to be beyond the scale of resolution of field experiments. Hall et al. (1990b) have suggested thatchanges in infaunal densities of 5% or less are indica-tive of a weak interaction between species. It is unlikelythat weak interactions could be identified without a verynarrowly focused experiment and very intensive sam-pling. Skilleter & Peterson (1994) concluded that theinfluence of indirect interactions on predation rate innatural ecosystems may be more the rule rather thanthe exception. This implies that developing an under-standing of the role of predators within ecosystems willinvolve a broader perspective than the mechanisticreductionist approach. We need experiments to iden-tify relevant mechanisms, but potential scale depen-dence of the results needs to be acknowledged.

Interactions between predation and other biologicalor physical processes are likely to increase in prevalencewith increasing extent, reducing the likelihood that con-sistent responses will be apparent in experiments ofbroad regional or geographical extent. Given the rangeand complexity of responses over a variety of scales thatare apparent in soft-sediment habitats, we need a variety of tools to study predation. We must be veryaware of how experimental results may change withscale, and anticipate indirect effects and weak interactions. The best analysis of predator effects on soft-sediment communities comes when a variety of differ-ent methods are combined (e.g. measures of long-termvariation in guild structure, patterns of prey utilization,and predator exclusion experiments: Hines et al.1990).

Ecological models with appropriate spatial structurebecome especially useful in developing specific andtestable predictions and assessing the importance oflocal biological processes over different scales (e.g.McArdle et al. 1997). To generate information relevantto environmental management issues we must collect

PREDATION IN SOFT-SEDIMENTS 349

data over the appropriate large scales. We need to be able to link large-scale information to small-scalestudies that identify mechanisms, e.g. nesting experi-ments within larger scale patterns (Schneider 1978;Wiens 1989; Thrush et al. 1997a,b). We also need todevelop a much more interactive approach that iteratesbetween prediction and testing in order to identifyeffects over different scales (Horne & Schneider 1994;Schneider 1994; Schneider et al. 1997).

CONCLUSIONS

All of the potential problems and complexities raisedby the previous studies of predation emphasize that we still have a lot to learn, and that it is still a chal-lenging and exciting topic for research. Many interest-ing and fundamental questions need to be addressed,including: predator effects on sediment stability; rela-tionships between predation, spatial heterogeneity andother ecological/environmental processes; interactions between top-down and bottom-up controls of com-munities. Important applied questions include theeffects of changes in estuarine and coastal habitats, inparticular, the loss of heterogeneity (especially threedimensional complexity) and biodiversity and theirimplications for predators and prey. Particularly impor-tant are the largely unknown ecological effects ofhumans as predators in marine ecosystems.

I have emphasized a number of important factors thatcan modify the way predation influences macrobenthiccommunity structure. The factors that emerge fromthis are that soft-sediment systems do not mimic othermarine systems. It is not clear what drives these cross-system differences. I suspect it involves the plasticityof feeding behaviour of soft-sediment organisms andthe scales of movement of predators and prey, togetherwith the important effects of habitat variation and scalesover which we have conducted our studies. In otherwords, to predict the effects of predation or changes inrates of predation in soft-sediment communities, weneed to know more about the natural history of preda-tors and prey, particularly in relation to different scalesof heterogeneity within the sediment. This informationis crucial in determining ecologically relevant scales ofstudy. To understand the role of predators in the struc-ture and function of soft-sediment communities overdifferent scales, we need to develop more integrativeresearch techniques. This is especially true whenassessing the broad-scale biological interactions that aredirectly relevant to environmental management andconservation.

ACKNOWLEDGEMENTS

I thank Andrew Constable for the invitation to presentthis paper at the conference in Warnambool. The ideasdeveloped in this paper have evolved through working

with my colleagues Judi Hewitt, Vonda Cummings andRick Pridmore (National Institute of Water andAtmospheric Research, Hamilton, New Zealand),Dave Schneider (Memorial University, Newfoundland,USA), Tuck Hines (Smithsonian EnvironmentalResearch Center, Maryland, USA) and Bob Whitlatch(University of Connecticut, Connecticut, USA).Comments by Dave Raffaelli, Alf Norkko and twoanonymous reviewers improved an earlier version ofthis manuscript.

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