species' traits and ecological functioning in marine conservation and management

Journal of Experimental Marine Biology and Ecology 366 (2008) 37–47

Contents lists available at ScienceDirect

Journal of Experimental Marine Biology and Ecology

j ourna l homepage: www.e lsev ie r.com/ locate / jembe

Species' traits and ecological functioning in marine conservation and management

J. Bremner ⁎Marine Biodiversity Research Programme, Institute of Biology, University of Oslo/Universitetet i Oslo, Postbox 1066 Blindern, 0316 Oslo, Norway

⁎ Tel.: +47 22854509; fax: +47 22854726.E-mail address: [email protected].

0022-0981/$ – see front matter © 2008 Elsevier B.V. Aldoi:10.1016/j.jembe.2008.07.007

a b s t r a c t
a r t i c l e i n f o
Keywords:
BenthosClimate changeEcosystemHuman impactsModelsPrediction
Marine conservation increasingly focuses on describing and maintaining ecosystem functioning. However, itis difficult to find suitable measures for whole-ecosystem functioning because the concept incorporatesmany different processes and includes physical, chemical and biological phenomena. An approach ispresented here for describing functioning based on traits exhibited by members of biological assemblages.Species' traits determine how they contribute to ecosystem processes, so the presence and distribution ofsuch traits can be utilised to indicate aspects of functioning. This multi-trait approach is relatively new tomarine ecology and the few studies to-date have mainly described patterns of functioning with respect toenvironmental variability and investigated the impacts of bottom trawling. Areas where the approach canmake a significant contribution to conservation and marine management are discussed, such as monitoringthe effects of human activities and success of subsequent management strategies, identifying species likely tobecome invasive or those particularly vulnerable to extinction and predicting the effects of futuredisturbance such as climate change.

© 2008 Elsevier B.V. All rights reserved.

1. Introduction

Marine ecosystems harbour large amounts of biodiversity but aresubject to a range of anthropogenic stressors. Conserving thesesystems requires knowledge, not only of which species are present,but of how the systems work and the effects of multiple andpotentially interacting threats. As such, increasing attention hasrecently been paid to investigating marine ecosystem functioning.Ecosystem functioning is a general concept that refers, in essence, tothe overall performance of ecosystems (see Jax, 2005). It has beenvariously defined as incorporating, individually or in combination,ecosystem processes (such as biogeochemical cycles), properties (e.g.pools of organic matter), goods (e.g. food and medicines) and services(e.g. regulating climate or cleansing air and water) as well as thetemporal resistance or resilience of these factors over time or inresponse to disturbance (Bengtsson, 1998; Biles et al., 2002; Diaz andCabido, 2001; Duffy, 2006; Duffy and Stachowicz, 2006; Giller et al.,2004; Hooper et al., 2005; Jax, 2005; Naeem andWright, 2003; Naeemet al., 2004; Virginia and Wall, 2001). In broad terms, it includes theprocesses (properties, goods or services) of ecosystems and theindividual ecosystem components involved in them.

Describing or measuring ecosystem functioning is difficult,particularly considering the differences of opinion among thescientific community on what the concept means; with a variety ofdefinitions quoted in the literature or, sometimes, no precise

l rights reserved.

definition given at all. As it encompasses a number of phenomena(Hooper et al., 2005), the overall functioning of an ecosystem iscomplex and involves many factors relating to the chemical, physicaland biological components of the system. No one individualparameter can be used to describe the functioning of entireecosystems (Giller et al., 2004), so consideration of multiple variablesmay be the most appropriate way to shed light on the concept (Duffyand Stachowicz, 2006).

Biological traits analysis is an analytical approach developed forthis purpose. The approach aims to provide a description of multipleaspects of functioning based on features of the biological ecosystemcomponent. It does this by utilising specific species traits as indicatorsof functioning (functional traits; see Diaz and Cabido, 2001) andexamining the occurrence of these traits over assemblages. Thepurpose of this paper is to present traits analysis as a means forinvestigating functioning inmarine ecosystems and discuss how it canbe used in conservation and management. The stages of traits analysiswill be explained, current and potential applications of the approachconsidered and some important issues relating to its use discussed.The approach is based on features of biological assemblages and doesnot explicitly measure physico-chemical variables, so it is an indicatorof ecosystem functioning, rather than a quantitative measure. To markthis distinction, it will be referred to hereafter as describing ecologicalfunctioning.

2. Biological traits analysis

The initial stages of traits analysis involve the identification of keyaspects of functioning in the ecosystem under consideration and the

mailto:[email protected]

http://dx.doi.org/10.1016/j.jembe.2008.07.007

http://www.sciencedirect.com/science/journal/00220981

Fig. 1. Simplified diagram of the marine carbon cycle, showing pathways facilitated by benthic macro-organisms. Numbered pathways are detailed in Table 1. Dotted lines representpathways where macro-organism have direct influence through resource capture, solid lines direct influence by other means and dashed lines indirect influence (modified fromBremner et al., 2006a).

38 J. Bremner / Journal of Experimental Marine Biology and Ecology 366 (2008) 37–47

selection of suitable indicator traits. An example is provided herebased on the marine carbon cycle and macrobenthos. A simplifieddiagram of the cycle, highlighting the pathways facilitated by benthicmacro-organisms, is shown in Fig. 1. The organisms fix carbon directlyfrom the overlying waters or remove it from the water column andtransfer it in various forms through the sediments and back into thepelagos (Table 1). Traits governing the involvement of benthic speciesin these processes can be utilised as indicators of their roles infunctioning (Table 1). Some of these traits can be quantified directly,while others may require the use of proxies (soft traits; see Hodgsonet al., 1999).

Once a list of functional indicator traits has been prepared,information on each is gathered for species present in the assemblagesstudied. The easiest way to organise this information, inmost cases, is tosplit the traits into categories (e.g. feeding method into the categoriesproducer, filter feeder, deposit feeder, predator) and give the species ascore for the extent to which they expresses each category. Codingsystems such as fuzzy coding (Chevenet et al.,1994) allow traits analysisthe flexibility to incorporate information on intraspecific variability intrait expression, which is advantageous with respect to traits that varyover species' life cycles or between populations.

This process provides a table of information on the functionalcharacteristics of species inhabiting the assemblages (a species-by-traits matrix). The resulting information can then be used on its own,or in combinationwith information on species' abundance or biomass,to form a picture of ecological functioning in assemblages that can beassessed over space or time. Depending on the requirements ofindividual studies, various multivariate ordination techniques can beutilised (Bremner et al., 2006b; Chevenet et al., 1994; Doledec andChessel, 1994; Doledec et al., 1996; Grime et al., 1997; Haybach et al.,

2004; Lindborg and Eriksson, 2005), the species combined intofunctional groups using cluster analysis (Ducrot et al., 2005; Grimeet al., 1997; Usseglio-Polatera et al., 2000; Wright et al., 2006) orindices of functional diversity (FD) computed (Botta-Dukat, 2005;Mason et al., 2005; Mouillot et al., 2007a, 2005; Petchey and Gaston,2002a; Walker et al., 1999; Weithoff, 2003).

3. Applications of traits analysis for marine conservationand management

Biological traits analysis in the marine environment is still in itsinfancy and research is severely lagging behind the freshwater andterrestrial realms. However, advances made in these areas can provideunderstanding about the general relationships between traits, speciesand their environment and generate ideas about how the approachcan be used to guide marine conservation and management. Thereappears to be particular potential in two main areas; assessing theeffects of human activities and subsequent management strategiesand making predictions about future change.

3.1. Assessing impacts and management strategies

3.1.1. Reference conditionsUnderstanding the impacts of human activities allows the

identification of major threats to marine systems and provides asound basis on which to make decisions about their management. Tothis end, knowledge of reference (or baseline) conditions is extremelyuseful and, in some legislatory contexts, necessary. Strategies fordescribing these conditions are often based on species composition,but this approach provides limited information about ecological

Table 1Mechanisms by which macrobenthic species contribute to the marine carbon cycle andpossible functional indicator traits

Pathway Species facilitative actions Functional indicator traits

1 Direct fixation of carbon• Benthic algae fix carbon directly fromseawater

Resource capture method,body size, growth rate,longevity

2-5 Transport of carbon from pelagos to benthos• Filter feeders consume pelagic primaryproducers, consumers, POC and microbes

Resource capture method

6-14 Transport of carbon within benthos• Grazers and shredders consume benthicprimary producers (macro- and microalgae)

Resource capture method,palatability, body size,growth rate, longevity,movement method, livinglocation/environmentalposition, living habit

• Deposit feeders and scavengers consumePOC, detritus and microbes• Producers and consumers die andconsumers defecate• Microbes decompose organic carbon;facilitated by deposit feeding andmovement of fauna in top layers ofsediments and by presence of tubes andburrows in upper sediments (break-uplarger particles and transport oxygen)• Deep-dwelling fauna transport carbonforms between aerobic and anaerobic layers• Microbes anaerobically decompose organiccarbon; facilitated by deep-dwelling faunathat transport chemicals required

15-20 Transport of carbon from benthos to pelagos• Primary producers respire carbon into thewater column

Resource capture method,living location/environmentalposition, living habit,movement method,reproductive method,propagule dispersal,migratory activities,body design (morphology)

• Deep-dwelling fauna facilitate thetransport of carbon released by microbesduring anaerobic decomposition• Tubes and burrows facilitate themovement of decomposed carbonspecies from sediments to overlyingwaters, as do movements of fauna.• Production of planktonic propagules,vertical feeding migrations and passivetransport of individuals into the watercolumn move carbon to the pelagos, asdoes consumption of benthic organismsby pelagic fauna• Sediment re-working by fauna releasesPOC into overlying waters

Pathways are depicted in Fig. 1.

39J. Bremner / Journal of Experimental Marine Biology and Ecology 366 (2008) 37–47

functioning. Additionally, biogeographical variation in species' dis-tributions leads to regional variation in assemblages. This results indescriptions of reference conditions that are restricted to specificgeographical areas, providing little opportunity for generalisation.Traits analysis may provide an interesting alternative to conventionalapproaches. By definition, it provides more information on function-ing than species-based methods. Moreover, it is built on a theoreticalframework that allows the formulation of generalisations aboutcommunity assembly in different environments (McGill et al., 2006).It is centred on the habitat templet and environmental filteringconcepts (Keddy, 1992; Poff, 1997; Southwood, 1977; Townsend andHildrew, 1994; Zobel, 1997). These state that, in essence, theenvironment dictates community assembly through species traits,because only specific traits can persist under a given set of envi-ronmental conditions. The environment filters the regional speciespool to exclude traits not suited for particular conditions and com-munities are assembled from species possessing traits that passthrough the filter.

These concepts assert direct links between species' traits andenvironmental conditions that are independent of geographic scale.Empirical evidence from marine systems supports this assertion. For

example, epibenthic assemblages around southeastern England arestructured over local scales with regards to biological traits, whilespecies composition shows larger-scale geographic patterns (Fig. 2);an observation mirrored, to some extent, in meiofauna assemblageswithin the region (Schratzberger et al., 2007). Elsewhere, species struc-ture in Indonesian coral reef sponges is related to geographical anddepth effects, while trait patterns are related only to depth (Fig. 3)and differences in species structure between benthic macrofaunaassemblages in two geographically-distinct sites in New Zealand arenot reflected in traits; which are related, instead, to local variation inhabitat (Hewitt et al., 2008-this issue).

Under these circumstances, the traits approach provides a moregeneral picture than traditional species-based methods and, wheresufficient understanding of environment-trait patterns exists, it showspromise as an alternative for determining reference conditions. Usingobservations that trait patterns vary predictablywith respect to knownenvironmental conditions across European rivers, Statzner et al. (2005)havedefined and validated a trait-basedmodel of reference conditions.This model could be adapted for marine systems. Unfortunately,knowledge ofmarine environment-trait relationships is less advanced.Although other studies exist (e.g. (Bremner et al., 2006c; Cleary andRenema, 2007; Rachello-Dolmen and Cleary, 2007), work to-date hasbeen focussed at relatively small spatial scales and has been largelydescriptive. Examining the existence of similar patterns over largescales and in a number of marine environments will identify general-ities fromwhich models can be developed. These models should thenbe tested, in terms of both their assumptions and their predictivepower. Reference condition models provide a great deal of usefulmanagement information and the theory underlying these may helpprovide a fundamental explanation for patterns of biodiversity. It is anarea, therefore, that seems worthy of further attention.

3.1.2. Assessing human impactsTraits analysis can also make a useful contribution to identifying

changes in functioning in assemblages exposed to anthropogenicdisturbance. Marine applications have focussed mainly on the effectsof bottom-trawling. Studies published to-date have examined differ-ences in the occurrence of biological traits in benthic assemblagesacross a gradient of fishing intensity in the North Sea (Tillin et al.,2006), compared trait patterns between heavily fished and un-fishedareas of the northwest Mediterranean Sea (de Juan et al., 2007),studied temporal patterns in an area of the western North Sea subjectto varying levels of fishing pressure (Bremner et al., 2005) andsearched for evidence of change over a 30-year period in a fishingground in the Bay of Fundy, north-east Atlantic (Kenchington et al.,2007).

These studies generally confirm expectations about fishing effectsthat originate from conventional species composition studies.For example, Tillin et al. (2006) showed that higher incidences ofburrowers, infauna and scavengers were associated with sites subjectto higher levels of fishing, while less impacted sites contained morefilter feeders and attached fauna (Fig. 4). However, this is not alwaysthe case. For example, proportions of filter feeders and scavengersvaried little in the face of changes in fishing pressure in the westernNorth Sea study (Fig. 5) and, in the Mediterranean, changes weredocumented in assemblages dominated by organisms displaying traitsnot considered especially vulnerable to trawling (de Juan et al., 2007).The information gleaned from these studies is useful; while fishingcan undoubtedly lead to increases in certain scavenging species, itmay not lead to a consistent increase in scavenging expressed acrossan assemblage and, at the functional level, may not be as important asit might initially seem. It is clear that traits analysis can aid in therefinement of theory regarding the effects of anthropogenic activities.However, the variability in results obtained by the above studieshighlights a lack of clarity on the functional effects of fishing andfurther studies would be of benefit here.

Fig. 2. Spatial variability in (A) species and (B) trait composition in benthic invertebrate assemblages around the southern North Sea and eastern Channel. Symbols on the maps referto assemblage types determined from multivariate analyses. There are large-scale geographic patterns in species composition, with homogeneity along the northern Channel andsouthern North Sea and in the mid-Channel, but trait composition is locally heterogeneous (modified from Bremner et al., 2003).

Fig. 3. Species (A) and trait (B) composition of coral reef sponge assemblages. Plots arenon-metric multidimensional scaling (stress b0.09 for both) of assemblages fromdifferent positions (V=vertical, I= inclined, H=horizontal) and depths (15 m, 10 m, 5 mand reef crest (RC)) at two sites (S=Sampela, H=Hoga) in Indonesia. Dashed lineshighlight samples from the same depth strata. Species composition is affected by bothlocation and depth, while trait composition relates only to depth (from Bell, 2007).


With the exception of two papers considering links between traitsand heavy metals in Indonesian corals (Rachello-Dolmen and Cleary,2007) and effects of aggregate extraction on functional diversity inNorth Seamacrobenthos (Cooper et al., 2008-this issue), traits analysishas, to my knowledge, yet to utilised to assess the functional effects ofother human activities. Evidence from terrestrial and freshwatersystems suggests it may have wider applications in this respect,having been applied to a variety of stressors such as pollution, habitatengineering, land-use and other multi-source impacts in diversegroups of species ranging from anurans to ground beetles (Ernst et al.,2006; Gayraud et al., 2003; Hausner et al., 2003; Ribera et al., 2001;Schweiger et al., 2007; Statzner et al., 2001). Interestingly, in

Fig. 4. Trait composition of benthic invertebrate assemblages along a gradient of trawlingintensity in the Long Forties area of the northern North Sea (biplot of sites and traitsfrom fuzzy correspondence analysis). Trawling intensity (average area covered yr-1) issuperimposed over sites. Sites of high-intensity trawling are characterised by burrowers,infauna and scavengers; low-intensity sites are characterised by filter feeders and attachedfauna (Perm Att=permanently attached, Temp Att=temporarily attached) (from Tillinet al., 2006).

Fig. 5. The relative proportions of different feeding mechanisms exhibited in a benthicinfauna assemblage from a western North Sea trawling ground over periods of varyingfishing activity. Phases 1 and 2 are initial years of low (1972-1981) andmoderate (1982-1986) effort, Phase 3 is a period of high effort from 1981-1989 and Phases 4 and 5 aresubsequent years of moderate (1990-1994) and low (1995-2001) effort (from Bremneret al., 2005). There was little variability over the period.


freshwater systems, it has the power to differentiate between theeffects of different types of anthropogenic activity (Doledec et al.,1999; Statzner et al., 2001). Thus, it may be particularly useful inmarine systems, which are often subject to multiple and potentiallyinteracting impacts such as bottom trawling, substrate extraction,physical engineering and pollution. This, aspect however, has yet to beinvestigated. Additional questions remain, such as how humanactivities will interact with local environmental conditions. Bottomfishing, for instance, has different species-level effects in differenthabitats (Kaiser et al., 2006). Will it also have differing effects ontraits? Will this pattern be evident for other impact types? If traitresponse to environment is scale-independent (see above), will thisalso be the case for response to human activities? These are importantissues. Descriptive studies of environment-trait links, coupled withexperimental approaches aimed at separating the effects of humanstressors from natural environmental variability, should providevaluable information allowing a clearer picture to emerge.

3.1.3. Assessing management strategiesIdentifying and assessing the effects of human activities is only one

element of marine management. The information resulting from suchassessments is used to develop response strategies for mitigating theimpacts of different activities. Traits analysis will be useful inevaluating the success of such management strategies. Two examplesfrom the literature serve to illustrate how it can contribute in this area:

1. Evaluating the effects of a management strategy. van Kleef et al.(2006) studied the effects of restoration measures on aquatic in-vertebrate traits in Dutch softwater lakes. They found that restorationhad variable effects, with some traits enhanced and others negativelyaffected (e.g. species utilising detritus and algae responded positively,while sexually-reproducing organisms were impacted). Effectsdiffered depending on the management phase, with execution ofthe restoration having differing effects to those seen during therecoveryphase. This informationwasused tomake recommendationsfor improving the management strategy, such as phasing restorationmeasures to maintain habitat required for particular traits.

2. Comparing different management options. Kahmen et al. (2002)compared four grassland management options as alternatives tothe traditional practice of sheep grazing in southwest Germany. Thevarious options had differing effects, with two leading to alteredtrait composition (one immediately and one several years later)and two preserving the initial composition. Interestingly, the sheepgrazing option conducted for at least 19 years prior to inception ofthe study continued to affect trait composition for the next 25years.From these findings, the authors made recommendations aboutwhich of the available management options would be mostappropriate in the circumstances.

There has been very little work in this area, in marine ecology orother disciplines. That management strategies may have long-termeffects on trait composition (Kahmen et al. (2002) saw effects at least40 years after management began), suggests they should be carefullyconsidered and properly evaluated for their effects on functioning.Moreover, as stressors do not exist in isolation in marine ecosystems,management strategies designed to mitigate the impacts of particularactivities may fail when multiple stressors are present because we donot have full understanding of how they interact or their cumulativeeffects on the system. A functional approach using species traits willbe particularly useful in this respect, as maintaining functionaldiversity can provide a buffer against potential management failure(Elmqvist et al., 2003). There is a lack of even basic knowledge aboutfunctional diversity in many marine habitats and this type ofinformation is crucial for all stages of the management process,from defining reference conditions through to assessing effects andevaluating responses.

3.2. Predicting future change

Future changes in marine systems are likely to feature anthro-pogenically-driven species extinctions or invasions. Global climatechange threatens marine assemblages through temperature- oracidification-induced species loss, while increased temperatures andother human-mediated pathways can allow invasion of non-nativespecies (Berezina, 2007; Hiddink and Ter Hofstede, 2008; Hiscocket al., 2004; Minchin, 2007). These extinctions and invasions are likelyto have implications for system functioning. The ability to makepredictions about which species may invade or become extinct andwhat the effects of such changes may be will help to prioritiseconservation efforts and guide management strategies.

3.2.1. Identifying likely invaders and vulnerable speciesMany species are introduced to new areas, but not all of these

become successful invaders (Boudouresque and Verlaque, 2002). It ispossible that success (or lack of) is due to the particular characteristicsexhibited by species and a set of traits may exist that can becollectively associated with invasive species. Considering the range ofpathways available for human introduction of non-native species(Minchin, 2007) and that all species with southern distributions could,theoretically, become invasive if temperature increases sufficiently toallow northern range-expansion, a large pool of potential marineinvaders exists and there is a lot to be gained from attempting topredict which will succeed (but see Reise et al., 2006 for an alternativeviewpoint).

While approximately 450-600 species are known to have invadedEuropean coasts alone (Reise et al., 2006), there has been little workon multi-species, multi-trait comparisons of marine invaders. Most ofthe information available on traits of invading species comes fromother disciplines and the vast majority of this from plant ecology. Anumber of reproductive and morphological traits have been linked toinvasive plants, including monoecious breeding systems, long flower-ing periods, high fecundity and vegetative reproduction, small seeds,large leaves, wind- and vertebrate-driven dispersal, high relativegrowth rate and high shoot-to-root ratio (Burns, 2006; Lloret et al.,2005; Sutherland, 2004; Thuiller et al., 2006b). Elsewhere, in aquaticanimals, traits such as high fecundity and fast growth have beenrelated to invasive species, as well as early maturity, wide foodspectrum and high genetic variability (Berezina, 2007; Grabowskiet al., 2007). Similarities between the systems, such as high growthrates and fecundity, hint at the existence of universal patterns ininvasive species traits. If this is true, insights gained elsewhere mayhave direct applicability to marine systems. However, invaders do notnecessarily exhibit traits predicted to enhance invasion success(Sutherland, 2004) and non-natives do not always display a uniqueset of traits but may, in fact, share characteristics with natives (Acosta


et al., 2006). Perhaps certain traits are associated with invasionsuccess, but the universal pattern does not exist (Lloret et al., 2005).Invasion traits may vary depending on the specifics of each case - suchas environmental conditions, introduction histories or stage of inva-sion (Acosta et al., 2006; Burns, 2006; Lloret et al., 2005; Muthand Pigliucci, 2006; Thuiller et al., 2006b). With such little infor-mation available for marine invaders, this is an area ripe for furtherinvestigation.

Traits of taxa declining in abundance have also received attention,in an effort to identify species particularly vulnerable to extinction.Research over approximately the last decade has shown that largebody size, slow growth, late maturity and high trophic level areassociated with increased vulnerability to extinction in a range ofmarine fishes around the globe (see review by Reynolds et al., 2005).Body size has also been implicated in population declines and rangecontractions in birds; as has breeding system, reproductive output,habitat requirements and dispersal (Amano and Yamaura, 2007; Jiguetet al., 2007). Other studies have examined traits correlated withspecies' rarity, as traits associated with extinction may also be linkedto rarity (Harcourt, 2006). For example, several trait categories couldbe related to rarity in stream macrofauna (16 in total, equalling 17% ofthose examined; Resh et al., 2005), while an inverse relationshipbetween range size and body size has been documented in marinemacrobenthos (Ellingsen et al., 2007).

Many traits have been examined with regard to species' vulner-ability, but demonstrating general patterns remains somewhatproblematical (see Murray et al., 2002). For instance, in ColoradoRiver Basin fishes, specific traits were related to distribution declinesbut the declining species shared other traits with invasive (i.e.expanding distribution) species (Olden et al., 2006). Similar findingselsewhere (Amano and Yamaura, 2007) suggest a complex relation-ship between species' traits and vulnerability. Many studies examineonly a small number of traits and this may restrict their ability tocharacterise relationships. Others focus on life history traits, but thesemay not be the only types of trait important for determining rarity orextinction risk (see, for example, Harcourt, 2006). Moreover, sometraits apparently important for vulnerability may actually be corre-lates for other (unidentified) traits influencing population variability(Amano and Yamaura, 2007).

The complexity of the relationship may also be a function of threattype (Amano and Yamaura, 2007). For example, large body size isoften associated with increased vulnerability but both large and smallfreshwater fishes aremore likely to be at risk, as big fish are vulnerableto fishing while small fish are vulnerable to pollution (Olden et al.,2007). Environmental variability can add further complexity (Murrayet al., 2002; Resh et al., 2005) and it is possible that the mechanismsand, thus, traits associated with the stages of decline and extinctionmay differ (Jiguet et al., 2007). With the exception of some fish species(Reynolds et al., 2005), there has been little comparative study ofrelative vulnerabilities in marine organisms. Traits analysis provides atool with which to identify the aspects of their ecology that makesome species more vulnerable to extinction than others. In light of theissues identified in studies from other systems, avenues for furthermarine research should incorporate formal comparisons of vulnerableand robust species, do this in the context of environment- and threat-type and consider the different stages of extinction.

In the context of identifying characteristics associated withinvasive or vulnerable species, traits analysis is not limited specificallyto functional traits. It will, however, provide particularly enlighteninginformation if the traits that make species successful invaders or athigh risk of extinction are also functionally important. A pertinentexample is given by the case of invasive ecosystem engineers. In amodelling approach based on the invasive cordgrass Spartina alterni-flora, Cuddington and Hastings (2004) showed that engineeringspecies may be more successful at inhabiting certain habitats thannon-engineers. Ecosystem engineers (sensu Jones et al., 1994) modify

habitats and resource availability for other species in the assemblage,so species exhibiting engineering traits are important for systemfunctioning (see, for example, Wallentinus and Nybert, 2007).Examination of the species' traits allows predictions, in cases suchas this, of which species will invade and of their likely effects onfunctioning.

3.2.2. Functional effects of future changeIn a changing world, conservation management must be proactive

as well as reactive. Predicting the nature and consequences of changein marine systems allows managers to prepare response strategies forsituations that may occur in the future. The ability to make predictionsis particularly important with regards to climate change as, althoughthere is mounting evidence that some marine species' distributionshave already been affected (Harley et al., 2006; Hawkins et al., 2003;Nehls et al., 2006), we currently have little real idea of the implicationsof such changes for system functioning. Given the links betweenspecies traits and invasion/extinction and that resistance of marineassemblages to events such as invasion may be linked to thecharacteristics of member species (Arenas et al., 2006; Stachowiczand Byrnes, 2006), it seems reasonable to assert a traits-basedapproach may also play a part in predicting the effects of futurechange.

Oneway traits analysis can contribute to our understanding of howfunctioning may change in future is through modelling approachesthat seek to link species, traits and environmental conditions and usethese links to predict assemblage trait composition under scenarios ofenvironmental change (Hausner et al., 2003). These models link traitsto environmental conditions either directly or indirectly. The indirectapproach links species' distributions to environmental variables andmodels their occurrence under varying conditions. Predictions aremade aboutwhich species will be found at a particular site under futureconditions and traits of these species examined to indicate how theassemblage will function. This environment-species-trait approachhas been used to link plant traits to current climate gradients, predictfuture species distributions under climate change scenarios andexamine how species' predicted range-shifts will affect functionaldiversity (Thuiller et al., 2006a, 2004, 2005). Interestingly, predictedspecies richness and functional diversity are not always correlated,suggesting scenarios must consider range-shifts and functional traitsseparately to gain fuller understanding of potential impacts (Thuilleret al., 2006a).

Initial investigations show this type of predictive analysis could beuseful in a management context, with a recent study illustrating howit can be used to investigate the functional effects of future change inmarine protected areas (Bremner et al., 2006a). Information ontemperatures encountered at species' southern range limits wasused to generate predictions about the likelihood of the speciesinhabiting a candidate conservation area being excluded, in future,under projected temperature increases. Despite predicted exclusion ofnearly 15% of the species examined, no loss of functional traits wasforecast. The scope of this particular study was limited, in that itconsidered only future species loss at the site in question, not speciesgain. Species' exclusion from a site under conditions outwith theirupper thermal tolerance can be predicted with more confidence thannorthwards expansion of southern species, because predicting whichspecies from the large pool of possible invaders (i.e. any species with ahigher temperature tolerance) are likely to arrive and integrate withexisting species is complicated by factors such as the existence ofdispersal barriers and competition or predation effects. In contrast,exclusion from a site is (theoretically) driven by species' physiologicallimits. Northwards range-expansions do occur and may be evenmore common than southern range-contraction in some marinespecies (Hiddink and Ter Hofstede, 2008), so predictions based only onexclusion will ignore important potential effects of climate warming.Nevertheless, the point of the exercise was to examine whether it


was possible to apply the approach and it certainly seems to havepotential.

Alternative models link traits with environmental conditions andpredict future trait distributions directly from projected changesin environmental variables. This approach is based on the assertionsof the environmental filtering/habitat templet concepts discussedearlier; some traits are better suited to particular environmentalconditions, so only species carrying the traits are likely to succeedunder those conditions. Convincing evidence to support this assertioncomes from French vineyards, where a model of plant communityassembly, determined by environmental filters acting on species'traits, predicted 94% of variance over a 42-year period (Shipley et al.,2006). Coastal lagoon fish assemblages also support the assertion(Mouillot et al., 2007a) but, in other cases, trait composition does notdeviate from null-model expectations (Mouillot et al., 2007b),suggesting environment-led trait filtration is not the only factoracting on species assembly.

In contrast to the environment-species-traits methods, thesemodels predict future species composition from trait composition,rather than traits from the species. Like much of the work discussed inthis paper, methods development currently comes mainly fromterrestrial ecology. For example, Barboni et al. (2004) have modelledchanges in plant traits along climate gradients in the Mediterranean,Devineau and Fournier (2005) made general predictions aboutvegetation responses to human impacts in west Africa and Diaz andCabido (1997) related South American plant traits to a steep climategradient to predict changes in functioning under hypothetical futuretemperatures. Development of the approach in marine systems couldprovide a sound theoretical framework for predicting functionaleffects of future change. Some marine systems are particularlyspecies-rich (Gray, 2002) and modelling environment-trait relation-ships in these systems will be complex and time-consuming, but suchendeavours are worthwhile. Studies focussed on less species-richsystems, such as intertidal sands and rocky shores, make a usefulstarting point. Areas combining relatively species-poor assemblageswith well-recognised environmental gradients, such as estuaries orthe Baltic Sea, for example, provide good opportunities for modeldevelopment.

Another means by which traits analysis can contribute to under-standing of future change is through a comparative approach. This isbased on the idea that certain places may currently be exposed toconditions expected elsewhere in the future (spatial analogues, see IPCC,2007, Chapter 2). Comparing trait composition between study sites andtheir spatial analogues provides an indication of how functioning maychange. An excellent example of this is found in a recent study of streammacrofauna by Bonada et al. (2007). Postulating that Mediterraneanstreams exhibit similar environmental conditions to those expected tooccur in future temperate streams, they compare assemblage traitcomposition between the two to illustrate how functioningmay alter inthe temperate streams. The approach required no prior knowledge ofenvironment-trait links, using only information on the species and theirtraits. This makes it a useful tool to provide, at least, a basic level ofunderstanding about the implications of climate change while morerobust models are developed.

One of the interesting outcomes of Bonada and colleagues'study was their prediction of changes in species composition butfewer effects on trait composition. The mechanism they proposedfor this was that species loss due to local extinction would becompensated for, at the functional level, by immigration ofsouthern species. The concept of species compensation is funda-mentally important for understanding human-derived impacts onecosystem functioning. In theory, functioning may remain stable inthe face of changes such as local extinction, because some speciesplay equivalent roles in the ecosystem and reductions or removalsof one species can be compensated for by increases in another(Frost et al., 1995; Walker et al., 1999). Compensation occurs

because these functionally-equivalent (also termed redundant, seeWalker, 1992) species differ in their response to environmentalconditions and the changing conditions that lead to loss of onespecies may be more conducive to another (Walker et al., 1999).Compensation can occur through two mechanisms; (i) a species islost and its function is replaced by an existing member of theassemblage or (ii) a species is lost and its function is replaced by aspecies new to the assemblage. The nature of the secondmechanism is irrelevant, in theory; the invader may displace thenative species or its arrival may be co-incidental, the result wouldbe maintenance of functioning in either case.

Trait-based approaches have been used to examine functional-equivalence in bird and coral reef sponge assemblages (Bell, 2007;Petchey et al., 2007) and to test a model for comparing levels ofequivalence across assemblages (Fonseca and Ganade, 2001). Studiessuch as these make significant contributions to knowledge offunctional compensation. However, if biogeochemical processes areconsidered the main aspects of ecosystem functioning, traits analysiscan not prove functional-equivalence or -compensation. The identi-fication of sets of species with similar traits is not, in itself, evidencethey actually have equal effects on ecosystem processes and thecontinuing presence of specific traits in an assemblage only indicatesthe species present are maintaining functioning. Direct evidence canbe obtained only through experimental approaches that quantify andcompare the effects of different species on rates of processes (e.g.Boyer and Fong, 2005; Resetarits and Chalcraft, 2007; Wohl et al.,2004) or remove species from an assemblage and measure resultingeffects on system processes (O'Connor and Crowe, 2005; Schiel, 2006;Suding et al., 2006). Detecting functional-equivalence by this means isa daunting task, considering the large number of species present insomemarine systems (Gray, 2002). The benefit of traits analysis to thestudy of functional compensation is, like several of the issuesdiscussed here, in providing a theoretical framework on which tobase experimental studies.

4. Issues to consider

In 1997, Chapin et al. (1997) wrote that traits with powerful effectson ecosystem processes are those that “(i) modify the availability,capture, and use of soil resources such as water and nutrients,(ii) affect the feeding relationships (trophic structure) within acommunity, and (iii) influence the frequency, severity, and extent ofdisturbances such as fire”. Ten years later the same basic premiseremains. Traits that affect resource use (including energy andnutrients) and feeding interactions are still regarded as fundamentallyimportant for ecosystem functioning, while traits related to habitatmodification (bioturbators and habitat providers; akin to both the firstand third of Chapin's categories) are recognised for their functionalimportance (Graf and Rosenberg, 1997; Hastings et al., 2007; Meys-man et al., 2006; Pearson, 2001). These three categories are wide-ranging and this makes a large number of traits potentially importantfor functioning. For example, an expert group focussing on only twomarine habitat types (rocky reefs and subtidal sandbanks, seeBremner et al., 2006a) identified some twenty-eight functionally-important macrobenthic species' traits (Table 2). Expanding thisrationale to all benthic habitats, all marine habitats or all speciesgroups could result in a prohibitively large number of traits. Moreover,in addition to those currently recognised, there is always thepossibility of further functionally-important traits yet to be identified.How do we choose which, or how many, traits to consider?

Multivariate ordination techniques and univariate functionaldiversity indices appear somewhat sensitive to trait number (Bremneret al., 2006b; Petchey, 2004), with analyses based on a single traitleading to particularly variable results (Fig. 6). While these differencesmay be subtle in a statistical context, the effects on our perceptions ofassemblage functioning and the consequences for conservation are

Fig. 6. How the number and type of traits analysed can affect ordination outcomes intraits analysis. The ordination plot shows second-stage multidimensional scaling ofspecies composition (Species, Genus), single-trait (Tail shape, Buccal morphology, Adultlength, Adult shape, Life history) and multi-trait (Biological traits matrix) datasets, withSpearman rank correlations (rs) between them highlighted in solid (rs=0.5) or dotted(rs=0.25) lines. Data are from nematode assemblages in the southwestern North Sea.Ordinations based on single traits produce different results than those using multi-traitdata (from Schratzberger et al., 2007).

Table 2Functionally-important species traits of rocky reef and subtidal sandbank assemblages(from Bremner et al., 2006a)

1. Maximum size2. Maximum growth rate3. Longevity4. Time to maturity5. Reproductive method6. Fecundity7. Propagule dispersal8. Body design9. Living habit10. Living location/environmental position11. Exposure potential12. Degree of flexibility13. Degree of attachment to substrate14. Strength of attachment to substrate15. Resource capture method16. Food type17. Energy transfer efficiency18. Tissue components19. Defence strategy20. Movement method21. Mobility22. Water column migration23. Horizontal migration24. Intra-specific sociability25. Predictability of dynamics26. Recruitment variability/success27. Biogenic habitat provision28. Scale of habitat provision


unclear. For example, variation in the number of traits included inanalyses can alter the degree of ‘redundancy’ seen in assemblages(Micheli and Halpern, 2005; Petchey and Gaston, 2002b).While this is,theoretically, intuitive (increasing the number of variables used todescribe entities will automatically increase the opportunity fordifferences between them), it is not a trivial issue because thevariables represent distinct aspects of ecosystem functioning. If ourability to say how similar species are in their effects on functioning isconstrained by how many traits we examine, there is a danger ofproviding erroneous information on the degree of species loss forwhich assemblages have the potential to compensate. Petchey andGaston (2006) suggest “the correct number of traits is the number thatare functionally important”. This is wise advice, but it raises furtherquestions about our certainty of which traits are functionallyimportant and whether some are more important than others.

Perhaps, then, more relevant than the number of traits selected foranalysis is the identity of the traits themselves. Different types of traitmay produce different pictures of functioning in marine assemblages(Bremner et al., 2006b) and the performance of environment-traitmodels depends on the traits analysed, because some can be moreaccurately modelled than others (Pöyry et al., 2008). Certain types oftrait may be more pertinent in some circumstances than others. Forexample, functional traits are often divided into two main groups;functional-effect and functional-response (Lavorel and Garnier, 2002).Effect traits describe how species affect ecosystem functioning, whileresponse traits describe how they respond to changes in environ-mental conditions. Both types of trait will be useful for monitoringpurposes and examining response traits can be especially helpful forindicating the presence of particular human activities, because thespecies' responses can be directly tied to anthropogenic drivers (seeSection 3.2.1). Including response traits in investigations of functionalcompensation is, in contrast, much more complicated. The concept offunctional compensation is based on functionally-equivalent specieshaving different responses to environmental conditions and it is thisdiffering response that allows compensation to take place (Walkeret al., 1999). What is required here is ‘redundancy’ in effect traits anddiversity in response traits (Hooper et al., 2005). If functional-equivalence is defined as species sharing both response and effect

traits, there is no logical basis for suggesting the loss of such speciescan be compensated for by another, because each of the functionally-equivalent species responds to environmental change in the sameway(i.e. they will all be impacted). The resulting species categorisationswill be of limited use for investigating compensation. It is clear thattrait inclusion, both in terms of type and number, must be consideredin the context of the questions being asked to make best use of theapproach.

The success of traits analysis, like any other analytical method, isdependent on the reliability of the underlying data. Its use in apredictive capacity may be hindered by uncertainty about thebehaviour of species' traits over time. Exploitation-linked evolutionof life history traits has been documented in commercial fish species(Law, 2000, 2007), increasing temperatures have been linked tochanges in dispersal and phenological traits in animal and plantspecies (Massot et al., 2008; Root et al., 2003) and intraspecific dif-ferences in a number of plant traits have been related to environ-mental changes brought on by introduction to new habitats (Zou et al.,2007). Predictions about future change are based on the traits thatspecies currently exhibit. If these traits evolve in response toenvironmental change, the link between species, traits and environ-mental drivers is broken. Prediction of future effects becomesextremely complex and confidence in the outcomes of models maybe impaired. It is not currently clear how extensive this problemmightbe or how it can be resolved. Fuzzy coding (Chevenet et al., 1994)provides a means to account for intraspecific variability in traitexpression, but this variability must be identified in advance. Thereare large gaps in our knowledge of natural history for many marinetaxa as it is; uncovering human-induced change in these traits isunlikely for all but the best-studied species or those of commercialimportance.

Multi-trait analyses of marine assemblages are data- and time-hungry processes. Large numbers of species must be identified andtrait information collated for each. Reducing the workload associatedwith such analyses is beneficial from a conservation and managementperspective, because it can reduce costs as well as the time-lagbetween data collection and translation of findings into managementaction. From a purely ecological viewpoint, quicker analyses allow thefield of research to develop at a faster rate, leading to a deeperunderstanding of ecological functioning. Time and effort can be savedby focussing analyses on a subset of the available data, such as themost abundant or widespread species. Data reductions appear to have


little effect on descriptions of assemblage structure, whether usingunivariate or multivariate measures (Bates et al., 2007; Clarke andWarwick, 1998; Gray et al., 1988; Magierowski and Johnson, 2006;Somerfield and Clarke, 1995; Vellend et al., 2008). Focussing traitsanalysis on a reduced species-set could result in significant timesavings. However, this assumes trait composition behaves in the sameway as species structure. Ellingsen et al. (2007) indicated this may notbe the case; a subset of the most widespread species in New Zealandsoft sediment assemblages failed to mirror the full species comple-ment because the subset did not include all traits found in thecomplete dataset. Three particular traits were missing from thesubset; grazing, high bioturbation potential and large body size. Eachof these can be considered functionally important, inferring that traitsanalysis based on only a subset of species may not provide anappropriate picture of ecological functioning. This is an importantissue and if the approach is to be utilised for developing ecologicaltheory and delivering information about system functioning, it is onethat should be formally analysed.

Biological traits analysis is not a panacea. The approach, in the formpresented here, does not measure marine ecosystem functioning. Itdoes not even measure elements such as benthic ecosystemfunctioning, which are determined by the combination of physical,chemical and biological components. Ideal measures of whole-ecosystem functioning would have two main attributes. First, theywould incorporate information on each of the three system compo-nents. Second, in terms of the biological component, they wouldinclude information on each of the organism groups (micro-, meio-,macro- and mega-organisms). Clearly this is a tall order and oneunlikely to be filled by any single variable or index. Traits analysis is,however, a step in the right direction. It provides a means toincorporate a degree of information on the three ecosystemcomponents and, to an extent, interactions between the differentorganism groups. In this respect, it can be a useful tool for indicatingfunctioning within marine systems and has many potential applica-tions. As marine and terrestrial systems share structural attributes(Gray et al., 2005, 2006), the developments in multi-trait analysisalready achieved in the terrestrial and, indeed, freshwater disciplinescan be used to shape the approach as a tool for addressing ecologicaltheories about how marine systems are assembled and how theyfunction. This, in turn, can help identify conservation concerns and aidin the development of appropriate management strategies.

Acknowledgements

This paper is dedicated to thememory of Professor John S. Gray, whogave the encouragement and academic freedom that allowed me todevelop the ideas presented herein, but died before his thoughts couldbe included. It was an honour to work with him and he will be greatlymissed. Thanks go to Silvana Birchenough, Simon Brockington, ErikBonsdorff, Tasman Crowe, Chris Frid, Jan Hiddink, Keith Hiscock, KerryHowell, Stuart Jenkins, Leigh Jones, Charlie Marshall, Odette Paramor,Paul Somerfield, Harvey Tyler-Walters and Jack Sewell for theircontributions to the development of the functional trait list presentedin Table 2. I would also like to thank Richard Warwick for the invitationto contribute to this special issue and an anonymous reviewer, whosecomments allowed the manuscript to be significantly improved. [SS]

References

Acosta, A., Izzi, C.F., Stanisci, A., 2006. Comparison of native and alien plant traits inMediterranean coastal dunes. Commun. Ecol. 7, 35–41.

Amano, T., Yamaura, Y., 2007. Ecological and life-history traits related to rangecontractions among breeding birds in Japan. Biol. Conserv. 137, 271.

Arenas, F., Sanchez, I., Hawkins, S.J., Jenkins, S.R., 2006. The invasibility of marine algalassemblages: Role of functional diversity and identity. Ecology 87, 2851–2861.

Barboni, D., Harrison, S.P., Bartlein, P.J., Jalut, G., New, M., Prentice, I.C., Sanchez-Goni, M.F., Spessa, A., Davis, B., Stevenson, A.C., 2004. Relationships between plant traits andclimate in the Mediterranean region: A pollen data analysis. J. Veg. Sci. 15, 635–646.

Bates, C.R., Scott, G., Tobin, M., Thompson, R., 2007. Weighing the costs and benefits ofreduced sampling resolution in biomonitoring studies: Perspectives from the temperaterocky intertidal. Biol. Conserv. 137, 617–625.

Bell, J., 2007. Contrasting patterns of species and functional composition of coral reefsponge assemblages. Mar. Ecol. Prog. Ser. 339, 73–81.

Bengtsson, J., 1998. Which species? What kind of diversity?Which ecosystem function?Some problems in studies of relations between biodiversity and ecosystem function.Appl. Soil. Ecol. 10, 191–199.

Berezina, N.A., 2007. Invasions of alien amphipods (Amphipoda: Gammaridea) in aquaticecosystems of North-Western Russia: pathways and consequences. Hydrobiologia590, 15–29.

Biles, C.L., Paterson, D.M., Ford, R.B., Solan,M., Raffaelli, D.G., 2002. Bioturbation, ecosystemfunctioning and community structure. Hydrol. Earth Syst. Sci. 6, 999–1005.

Bonada, N., Doledec, S., Statzner, B., 2007. Taxonomic and biological trait differences ofstream macroinvertebrate communities between mediterranean and temperateregions: implications for future climatic scenarios. Global Chang. Biol.13,1658–1671.

Botta-Dukat, Z., 2005. Rao's quadratic entropy as ameasure of functional diversity basedon multiple traits. J. Veg. Sci. 16, 533–540.

Boudouresque, C.F., Verlaque, M., 2002. iological pollution in the Mediterranean Sea:invasive versus introduced macrophytes. Mar. Pollut. Bull. 44, 32–38.

Boyer, K.E., Fong, P., 2005. Co-occurrence of habitat-modifying invertebrates: effects onstructural and functional properties of a created saltmarsh. Oecologia 143, 619–628.

Bremner, J., Rogers, S.I., Frid, C.L.J., 2003. Assessing functional diversity in marinebenthic systems: a comparison of approaches. Mar. Ecol. Prog. Ser. 254, 11–25.

Bremner, J., Frid, C.L.J., Rogers, S.I., 2005. Biological traits of the North Sea benthos - doesfishing affect benthic ecosystem function? In: Barnes, P., Thomas, J. (Eds.), Benthichabitats and the effects of fishing. American Fisheries Society Symposium.Bethesda, Maryland, pp. 477–489.

Bremner, J., Paramor, O.A.L., Frid, C.L.J., 2006a. Developing a methodology forincorporating ecological structure and functioning into designation of SpecialAreas of Conservation (SAC) in the 0-12 nautical mile zone, Report to EnglishNature. Inductively Coupled Plasmas in Analytical Atomic Spectrometry. Universityof Liverpool, Liverpool. 153pp.

Bremner, J., Rogers, S.I., Frid, C.L.J., 2006b. Methods for describing ecological functioningof marine benthic assemblages using biological traits analysis (BTA). Ecol. Ind. 6,609–622.

Bremner, J., Rogers, S.I., Frid, C.L.J., 2006c. Matching biological traits to environmentalconditions in marine benthic ecosystems. J. Mar. Syst. 60, 302–316.

Burns, J.H., 2006. Relatedness and environment affect traits associated with invasiveand noninvasive introduced Commelinaceae. Ecol. Appl. 16, 1367–1376.

Chapin, F.S., Walker, B.H., Hobbs, R.J., Hooper, D.U., Lawton, J.H., Sala, O.E., Tilman, D.,1997. Biotic control over the functioning of ecosystems. Science 277, 500–504.

Chevenet, F., Doledec, S., Chessel, D., 1994. A fuzzy coding approach for the analysis oflong-term ecological data. Freshw. Biol. 31, 295–309.

Clarke, K.R., Warwick, R.M., 1998. Quantifying structural redundancy in ecologicalcommunities. Oecologia 113, 278–289.

Cleary, D.F.R., Renema,W., 2007. Relating species traits of foraminifera to environmentalvariables in the Spermonde Archipelago, Indonesia. Mar. Ecol. Prog. Ser. 334, 73–82.

Cooper, K.M., Barrio Froján, C.R.S., Defew, E., Curtis, M., Fleddum, A., Brooks, L., Paterson,D.M., 2008. Assessment of ecosystem function following marine aggregate dredging.J. Exp. Mar. Biol. Ecol. 366, 82–91 (this issue). doi:10.1016/j.jembe.2008.07.011.

Cuddington, K., Hastings, A., 2004. Invasive engineers. Ecol. Model. 178, 335–347.de Juan, S., Thrush, S.F., Demestre, M., 2007. Functional changes as indicators of trawling

disturbance on a benthic community located in a fishing ground (NW Mediterra-nean Sea). Mar. Ecol. Prog. Ser. 334, 117–129.

Devineau, J., Fournier, A., 2005. Towhat extent can simple plant biological traits accountfor the response of the herbaceous layer to environmental changes in fallow-savanna vegetation (West Burkina Faso, West Africa)? Flora 200, 361–375.

Diaz, S., Cabido, M., 1997. Plant functional types and ecosystem function in relation toglobal change. J. Veg. Sci. 8, 463–474.

Diaz, S., Cabido, M., 2001. Vive la difference: plant functional diversity matters toecosystem processes. Trends Ecol. Evol. 16, 646–655.

Doledec, S., Chessel, D., 1994. Co-inertia analysis - an alternative method for studyingspecies environment relationships. Freshw. Biol. 31, 277–294.

Doledec, S., Chessel, D., terBraak, C.J.F., Champely, S., 1996. Matching species traits toenvironmental variables: A new three-table ordination method. Environ. Ecol. Stat. 3,143–166.

Doledec, S., Statzner, B., Bournard,M.,1999. Species traits for future biomonitoring acrossecoregions: patterns along a human-impacted river. Freshw. Biol. 42, 737–758.

Ducrot, V., Usseglio-Polatera, P., Pery, A.R.R., Mouthon, J., Lafont, M., Roger, M.C., Garric,J., Ferard, J.F., 2005. Using aquatic macroinverteb rate species traits to build testbatteries for sediment toxicity assessment: Accounting for the diversity of potentialbiological responses to toxicants. Environ. Toxicol. Chem. 24, 2306–2315.

Duffy, J.E., 2006. Biodiversity and the functioning of seagrass ecosystems. Mar. Ecol.Prog. Ser. 311, 233–250.

Duffy, J.E., Stachowicz, J.J., 2006. Why biodiversity is important to oceanography:potential roles of genetic, species, and trophic diversity in pelagic ecosystemprocesses. Mar. Ecol. Prog. Ser. 311, 179–189.

Ellingsen, K.E., Hewitt, J.E., Thrush, S.F., 2007. Rare species, habitat diversity andfunctional redundancy in marine benthos. J. Sea Res. 58, 291–301.

Elmqvist, T., Folke, C., Nystrom, M., Peterson, G., Bengtsson, J., Walker, B., Norberg, J.,2003. Response diversity, ecosystem change, and resilience. Front. Ecol. Environ. 1,488–494.

Ernst, R., Linsenmair, K.E., Rodel, M.O., 2006. Diversity erosion beyond the species level:Dramatic loss of functional diversity after selective logging in two tropicalamphibian communities. Biol. Conserv. 133, 143–155.



Fonseca, C.R., Ganade, G., 2001. Species functional redundancy, random extinctions andthe stability of ecosystems. J. Ecol. 89, 118–125.

Frost, T.M., Carpenter, S.R., Ives, A.R., Kratz, T.K., 1995. Species compensation andcomplementarity in ecosystem function. In: Jones, C., Lawton, J. (Eds.), LinkingSpecies and Ecosystems. Chapman and Hall, New York, pp. 224–239.

Gayraud, S., Statzner, B., Bady, P., Haybachp, A., Scholl, F., Usseglio-Polatera, P., Bacchi,M., 2003. Invertebrate traits for the biomonitoring of large European rivers: aninitial assessment of alternative metrics. Freshw. Biol. 48, 2045–2064.

Giller, P.S., Hillebrand, H., Berninger, U.G., Gessner, M.O., Hawkins, S., Inchausti, P., Inglis, C.,Leslie, H., Malmqvist, B., Monaghan, M.T., Morin, P.J., O'Mullan, G., 2004. Biodiversityeffects on ecosystem functioning: emerging issues and their experimental test inaquatic environments. Oikos 104, 423–436.

Grabowski,M., Bacela, K., Konopacka,A., 2007.Howtobean invasive gammarid (Amphipoda:Gammaroidea)-comparison of life history traits. Hydrobiologia 590, 75–84.

Graf, G., Rosenberg, R.,1997. Bioresuspension and biodeposition: a review. J. Mar. Syst.11,269–278.

Gray, J.S., 2002. Species richness ofmarine soft sediments.Mar. Ecol. Prog. Ser. 244, 285–297.Gray, J.S., Bjorgesaeter, A., Ugland, K.I., 2005. The impact of rare species on natural

assemblages. J. Anim. Ecol. 74, 1131–1139.Gray, J.S., Bjorgesaeter, A., Ugland, K.I., Frank, K., 2006. Are there differences in structure

between marine and terrestrial assemblages? J. Exp. Mar. Biol. Ecol. 330, 19–26.Gray, J.S., Aschan, M., Carr, M.R., Clarke, K.R., Green, R.H., Pearson, T., Rosenberg, R.,

Warwick, R.M.,1988. Analysis of community attributes of the benthic macrofauna ofFrierfjord/Langesundfjord and in a mesocosm experiment. Mar. Ecol. Prog. Ser. 46,151–165.

Grime, J.P., Thompson, K., Hunt, R., Hodgson, J.G., Cornelissen, J.H.C., Rorison, I.H.,Hendry, G.A.F., Ashenden, T.W., Askew, A.P., Band, S.R., Booth, R.E., Bossard, C.C.,Campbell, B.D., Cooper, J.E.L., Davison, A.W., Gupta, P.L., Hall, W., Hand, D.W.,Hannah, M.A., Hillier, S.H., Hodkinson, D.J., Jalili, A., Liu, Z., Mackey, J.M.L., Matthews,N., Mowforth, M.A., Neal, A.M., Reader, R.J., Reiling, K., RossFraser, W., Spencer, R.E.,Sutton, F., Tasker, D.E., Thorpe, P.C., Whitehouse, J., 1997. Integrated screeningvalidates primary axes of specialisation in plants. Oikos 79, 259–281.

Harcourt, A.H., 2006. Rarity in the tropics: biogeography and macroecology of theprimates. J. Biogeogr. 33, 2077–2087.

Harley, C.D.G., Hughes, A.R., Hultgren, K.M., Miner, B.G., Sorte, C.J.B., Thornber, C.S.,Rodriguez, L.F., Tomanek, L., Williams, S.L., 2006. The impacts of climate change incoastal marine systems. Ecol. Lett. 9, 228–241.

Hastings, A., Byers, J.E., Crooks, J.A., Cuddington, K., Jones, C.G., Lambrinos, J.G., Talley, T.S.,Wilson,W.G., 2007. Ecosystem engineering in space and time. Ecol. Lett.10,153–164.

Hausner, V.H., Yoccoz, N.G., Ims, R.A., 2003. Selecting indicator traits for monitoring landuse impacts: Birds in northern coastal birch forests. Ecol. Appl. 13, 999–1012.

Hawkins, S.J., Southward, A.J., Genner, M.J., 2003. Detection of environmental change ina marine ecosystem - evidence from the western English Channel. Sci. TotalEnviron. 310, 245–256.

Haybach, A., Scholl, F., Konig, B., Kohmann, F., 2004. Use of biological traits forinterpreting functional relationships in large rivers. Limnologica 34, 451–459.

Hewitt, J.E., Thrush, S.F., Dayton, P.K., 2008. Habitat variation, species diversity andecological functioning in a marine system. J. Exp. Mar. Biol. Ecol. 366, 116–122(this issue). doi:10.1016/j.jembe.2008.07.016.

Hiddink, J.G., Ter Hofstede, R., 2008. Climate induced increases in species richness ofmarine fishes. Global Chang. Biol. 14.

Hiscock, K., Southward, A., Tittley, I., Hawkins, S., 2004. Effects of changing temperatureon benthic marine life in Britain and Ireland. Aquat. Conserv.: Mar. Freshw. Ecosyst.14, 333–362.

Hodgson, J.G., Wilson, P.J., Hunt, R., Grime, J.P., Thompson, K., 1999. Allocating C-S-Rplant functional types: a soft approach to a hard problem. Oikos 85, 282–294.

Hooper, D.U., Chapin, F.S., Ewel, J.J., Hector, A., Inchausti, P., Lavorel, S., Lawton, J.H.,Lodge, D.M., Loreau, M., Naeem, S., Schmid, B., Setala, H., Symstad, A.J., Vandermeer,J., Wardle, D.A., 2005. Effects of biodiversity on ecosystem functioning: A consensusof current knowledge. Ecol. Monogr. 75, 3–35.

IPCC, 2007. Climate Change 2007: Impacts, Adaptation and Vulnerability. In: Parry, M.L.,Canziani, O.F., Palutikof, J.P., van der Linden, P.J., Hanson, C.E. (Eds.), Contribution ofWorking Group II to the Fourth Assessment Report of the Intergovernmental Panelon Climate Change. Cambridge. 976pp.

Jax, K., 2005. Functionand qfunctioningq inecology:what does itmean?Oikos 111, 641–648.Jiguet, F., Gadot, A.-S., Julliard, R., Newson, S.E., Couvet, D., 2007. Climate envelope, life

history traits and the resilience of birds facing global change. Global Chang. Biol. 13,1672–1684.

Jones, C.G., Lawton, J.H., Shachak, M.,1994. Organisms as ecosystem engineers. Oikos 69,373–386.

Kahmen, S., Poschlod, P., Schreiber, K.F., 2002. Conservation management of calcareousgrasslands. Changes in plant species composition and response of functional traitsduring 25years. Biol. Conserv. 104, 319–328.

Kaiser, M.J., Clarke, K.R., Hinz, H., Austen, M.C.V., Somerfield, P.J., Karakassis, I., 2006.Global analysis of response and recovery of benthic biota to fishing. Mar. Ecol. Prog.Ser. 311, 1–14.

Keddy, P.A., 1992. Assembly and response rules: two goals for predictive communityecology. J. Veg. Sci. 3, 157–164.

Kenchington, E.L.R., Kenchington, T.J., Henry, L., Fuller, S., Gonzalez, P., 2007. Multi-decadal changes in the megabenthos of the Bay of Fundy: The effects of fishing.J. Sea Res. 58, 220–240.

Lavorel, S., Garnier, E., 2002. Predicting changes in community composition and ecosystemfunctioning from plant traits: revisiting the Holy Grail. Funct. Ecol. 16, 545–556.

Law, R., 2000. Fishing, selection and phenotypic evolution. ICES J. Mar. Sci. 57, 659–668.Law, R., 2007. Fisheries-induced evolution: present status and future directions. Mar.

Ecol. Prog. Ser. 335, 271–277.

Lindborg, R., Eriksson, O., 2005. Functional response to land use change in grasslands:Comparing species and trait data. Ecoscience 12, 183–191.

Lloret, F., Medail, F., Brundu, G., Camarda, I., Moragues, E., Rita, J., Lambdon, P., Hulme, P.E.,2005. Species attributes and invasion success byalienplants onMediterranean islands.J. Ecol. 93, 512–520.

Magierowski, R.H., Johnson, C.R., 2006. Robustness of surrogates of biodiversity inmarine benthic communities. Ecol. Appl. 16, 2264–2275.

Mason, N.W.H., Mouillot, D., Lee, W.G., Wilson, J.B., 2005. Functional richness, functionalevenness and functional divergence: the primary components of functionaldiversity. Oikos 111, 112–118.

Massot, M., Clobert, J., Ferriere, R., 2008. Climate warming, dispersal inhibition andextinction risk. Global Chang. Biol. 14, 461–469.

McGill, B.J., Enquist, B.J., Weiher, E., Westoby, M., 2006. Rebuilding community ecologyfrom functional traits. Trends Ecol. Evol. 21, 178–185.

Meysman, F.J.R., Middelburg, J.J., Heip, C.H.R., 2006. Bioturbation: a fresh look atDarwin's last idea. Trends Ecol. Evol. 21, 688–695.

Micheli, F., Halpern, B.S., 2005. Low functional redundancy in coastal marineassemblages. Ecol. Lett. 8, 391–400.

Minchin, D., 2007. Aquaculture and transport in a changing environment: Overlap andlinks in the spread of alien biota. Mar. Pollut. Bull. 55, 302–313.

Mouillot, D., Dumay, O., Tomasini, J.A., 2007a. Limiting similarity, niche filtering andfunctional diversity in coastal lagoon fish communities. Estuar. Coast. Shelf Sci. 71,443–456.

Mouillot, D., Mason, N.W.H., Wilson, J.B., 2007b. Is the abundance of species determinedby their functional traits? A new method with a test using plant communities.Oecologia 152, 729–737.

Mouillot, D., Mason, W.H.N., Dumay, O., Wilson, J.B., 2005. Functional regularity: aneglected aspect of functional diversity. Oecologia 142, 353–359.

Murray, B.R., Thrall, P.H., Gill, A.M., Nicotra, A.B., 2002. How plant life-history andecological traits relate to species rarity and commonness at varying spatial scales.Austral. Ecol. 27, 291–310.

Muth, N.Z., Pigliucci, M., 2006. Traits of invasives reconsidered: Phenotypic compar-isons of introduced invasive and introduced noninvasive plant species within twoclosely related clades. Am. J. Bot. 93, 188–196.

Naeem, S., Wright, J.P., 2003. Disentangling biodiversity effects on ecosystem functioning:deriving solutions to a seemingly insurmountable problem. Ecol. Lett. 6, 567–579.

Naeem, S., Loreau, M., Inchausti, P., 2004. Biodiversity and ecosystem functioning: theemergence of a synthetic ecological framework. In: Loreau, M., Naeem, S., Inchausti,P. (Eds.), Biodiversity and Ecosystem Functioning. Oxford University Press, Oxford,pp. 3–11.

Nehls, G., Diederich, S., Thieltges, D.W., Strasser, M., 2006. Wadden Sea mussel bedsinvaded by oysters and slipper limpets: competition or climate control? Helgol.Mar. Res. 60, 135–143.

O'Connor, N.E., Crowe, T.P., 2005. Biodiversity loss and ecosystem functioning:distinguishing between number and identity of species. Ecology 86, 1783–1796.

Olden, J.D., Poff, N.L., Bestgen, K.R., 2006. Life history strategies predict fish invasionsand extirpations in the Colorado River Basin. Ecol. Monogr. 76, 25–40.

Olden, J.D., Hogan, Z.S., Vander Zanden, M.J., 2007. Small fish, big fish, red fish, blue fish:size-biased extinction risk of the world's freshwater and marine fishes. Global Ecol.Biogeogr. 16, 694–701.

Pearson, T.H., 2001. Functional group ecology in soft-sediment marine benthos: the roleof bioturbation. Oceanogr. Mar. Biol. Annu. Rev. 39, 233–267.

Petchey, O.L., 2004. On the statistical significance of functional diversity effects. Funct.Ecol. 18, 297–303.

Petchey, O.L., Gaston, K.J., 2002a. Functional diversity (FD), species richness andcommunity composition. Ecol. Lett. 5, 402–411.

Petchey, O.L., Gaston, K.J., 2002b. Extinction and the loss of functional diversity. Proc. R.Soc. Lond., Ser. B: Biol. Sci. 269, 1721–1727.

Petchey, O.L., Gaston, K.J., 2006. Functional diversity: back to basics and lookingforward. Ecol. Lett. 9, 741–758.

Petchey, O.L., Evans, K.L., Fishburn, I.S., Gaston, K.J., 2007. Low functional diversity andno redundancy in British avian assemblages. J. Anim. Ecol. 76, 977–985.

Poff, N.L., 1997. Landscape filters and species traits: Towardsmechanistic understandingand prediction in stream ecology. J. North Am. Benthol. Soc. 16, 391–409.

Pöyry, J., Luoto, M., Heikkinen, R.K., Saarinen, K., 2008. Species traits are associated withthe quality of bioclimatic models. Glob. Ecol. Biogeogr. 17, 403–414.

Rachello-Dolmen, P.G., Cleary, D.F.R., 2007. Relating coral species traits to environ-mental conditions in the Jakarta Bay/Pulau Seribu reef system, Indonesia. Estuar.Coast. Shelf Sci. 73, 816–826.

Reise, K., Olenin, S., Thieltges, D.W., 2006. Are aliens threatening European aquaticcoastal ecosystems? Helgol. Mar. Res. 60, 77–83.

Resetarits, W.J., Chalcraft, D.R., 2007. Functional diversity within a morphologicallyconservative genus of predators: implications for functional equivalence andredundancy in ecological communities. Funct. Ecol. 21, 793–804.

Resh, V.H., Beche, L.A., McElravy, E.P., 2005. How common are rare taxa in long-termbenthic macroinvertebrate surveys? J. North Am. Benthol. Soc. 24, 976–989.

Reynolds, J.D., Dulvy, N.K., Goodwin, N.B., Hutchings, J.A., 2005. Biology of extinctionrisk in marine fishes. Proc. R. Soc. Lond., Ser. B: Biol. Sci. 272, 2337–2344.

Ribera, I., Doledec, S., Downie, I.S., Foster, G.N., 2001. Effect of land disturbance andstress on species traits of ground beetle assemblages. Ecology 82, 1112–1129.

Root, T.L., price, J.T., Hall, K.R., Schneider, S.H., Rosenzweig, C., Pounds, J.A., 2003.Fingerprints of global warming on wild animals and plants. Nature 421, 57–60.

Schiel, D.R., 2006. Rivets or bolts? When single species count in the function oftemperate rocky reef communities. J. Exp. Mar. Biol. Ecol. 338, 233–252.

Schratzberger, M., Warr, K.J., Rogers, S.I., 2007. Functional diversity of nematodecommunities in the southwestern North Sea. Mar. Environ. Res. 63, 368–389.



Schweiger, O., Musche, M., Bailey, D., Billeter, R., Diekotter, T., Hendrickx, F., Herzog, F.,Liira, J., Maelfait, J.P., Speelmans, M., Dziock, F., 2007. Functional richness of localhoverfly communities (Diptera, Syrphidae) in response to land use acrosstemperate Europe. Oikos 116, 461–472.

Shipley, B., Vile, D., Garnier, E., 2006. Fromplant traits to plant communities: A statisticalmechanistic approach to biodiversity. Science 314, 812–814.

Somerfield, P.J., Clarke, K.R., 1995. Taxonomic levels, in marine community studies,revisited. Mar. Ecol. Prog. Ser. 127, 113–119.

Southwood, T.R.E., 1977. Habitat, the templet for ecological strategies - presidentialaddress to the British Ecological Society, 5 January 1977. J. Anim. Ecol. 46, 337–365.

Stachowicz, J.J., Byrnes, J.E., 2006. Species diversity, invasion success, and ecosystemfunctioning: disentangling the influence of resource competition, facilitation, andextrinsic factors. Mar. Ecol. Prog. Ser. 311, 251–262.

Statzner, B., Bis, B., Doledec, S., Usseglio-Polatera, P., 2001. Perspectives for biomonitor-ing at large spatial scales: a unified measure for the functional composition oninvertebrate communities in European running waters. Basic Appl. Ecol. 2, 73–85.

Statzner, B., Bady, P., Doledec, S., Scholl, F., 2005. Invertebrate traits for the biomonitoringoflarge European rivers: an initial assessment of trait patterns in least impacted riverreaches. Freshwat. Biol. 50, 2136–2161.

Suding, K.N., Miller, A.E., Bechtold, H., Bowman, W.D., 2006. The consequence of speciesloss on ecosystem nitrogen cycling depends on community compensation. Oecologia149, 141–149.

Sutherland, S., 2004. What makes a weed a weed: life history traits of native and exoticplants in the USA. Oecologia 141, 24–39.

Thuiller, W., Lavorel, S., Midgley, G., Lavergne, S., Rebelo, T., 2004. Relating plant traitsand species distributions along bioclimatic gradients for 88 Leucadendron taxa.Ecology 85, 1688–1699.

Thuiller, W., Lavorel, S., Araujo, M.B., Sykes, M.T., Prentice, I.C., 2005. Climate changethreats to plant diversity in Europe. Proc. Natl. Acad. Sci. U. S. A. 102, 8245–8250.

Thuiller, W., Lavorel, S., Sykes, M.T., Araujo, M.B., 2006a. Using niche-basedmodelling toassess the impact of climate change on tree functional diversity in Europe. Divers.Distrib. 12, 49–60.

Thuiller, W., Richardson, D.M., Rouget, M., Proches, S., Wilson, J.R.U., 2006b. Interactionsbetween environment, species traits and human uses describe patterns of plantinvasions. Ecology 87, 1755–1769.

Tillin, H.M., Hiddink, J.G., Jennings, S., Kaiser, M.J., 2006. Chronic bottom trawling alters thefunctional composition of benthic invertebrate communities on a sea-basin scale.Mar.Ecol. Prog. Ser. 318, 31–45.

Townsend, C.R., Hildrew, A.G., 1994. Species traits in relation to a habitat templet forriver systems. Freshw. Biol. 31, 265–275.

Usseglio-Polatera, P., Bournaud, M., Richoux, P., Tachet, H., 2000. Biomonitoring throughbiological traits of benthic macroinvertebrates: how to use species trait databases?Hydrobiologia 422, 153–162.

van Kleef, H.H., Verberk, W., Leuven, R., Esselink, H., van der Velde, G., van Duinen, G.A.,2006. Biological traits successfully predict the effects of restorationmanagement onmacroinvertebrates in shallow softwater lakes. Hydrobiologia 565, 201–216.

Vellend, M., Lilley, P.L., Starzomski, B.M., 2008. Using subsets of species in biodiversitysurveys. J. Appl. Ecol. 45, 161–169.

Virginia, R.A., Wall, D.H., 2001. Ecosystem function, principles of. In: Levin, S.A. (Ed.),Encyclopedia of Biodiversity, pp. 345–352.

Walker, B.H., 1992. Biodiversity and ecological redundancy. Conserv. Biol. 6, 18–23.Walker, B., Kinzig, A., Langridge, J., 1999. Plant attribute diversity, resilience, and

ecosystem function: The nature and significance of dominant and minor species.Ecosystems 2, 95–113.

Wallentinus, I., Nybert, C.D., 2007. Introduced marine organisms as habitat modifiers.Mar. Pollut. Bull. 55, 323–332.

Weithoff, G., 2003. The concepts of 'plant functional types' and 'functional diversity' inlake phytoplankton - a new understanding of phytoplankton ecology? Freshw. Biol.48, 1669–1675.

Wohl, D.L., Arora, S., Gladstone, J.R., 2004. Functional redundancy supportsbiodiversityandecosystem function in a closed and constant environment. Ecology 85, 1534–1540.

Wright, J.P., Naeem, S., Hector, A., Lehman, C., Reich, P.B., Schmid, B., Tilman, D., 2006.Conventional functional classification schemes underestimate the relationshipwith ecosystem functioning. Ecol. Lett. 9, 111–120.

Zobel, M., 1997. The relative role of species pools in determining plant species richness.An alternative explanation of species coexistence? Trends Ecol. Evol. 12, 266–269.

Zou, J., Rogers, W.E., Siemann, E., 2007. Differences in morphological and physiologicaltraits between native and invasive populations of Sapium sebiferum. Funct. Ecol. 21,721–730.

species' traits and ecological functioning in marine conservation and management

Documents