plant attribute diversity, resilience, and ecosystem...

ORIGINAL ARTICLES

Plant Attribute Diversity, Resilience,and Ecosystem Function: The Nature

and Significance of Dominantand Minor Species

Brian Walker,1* Ann Kinzig,2 and Jenny Langridge1

1Division of Wildlife and Ecology, CSIRO, PO Box 84, Lyneham, Canberra, Australia 2602; and 2Department of Ecologyand Evolutionary Biology, Princeton University, Princeton, New Jersey 08540, USA

ABSTRACTThis study tested an hypothesis concerning patternsin species abundance in ecological communities.Why do the majority of species occur in low abun-dance, with just a few making up the bulk of thebiomass? We propose that many of the minorspecies are analogues of the dominants in terms ofthe ecosystem functions they perform, but differ interms of their capabilities to respond to environmen-tal stresses and disturbance. They thereby conferresilience on the community with respect to ecosys-tem function. Under changing conditions, ecosys-tem function is maintained when dominants de-cline or are lost because functionally equivalentminor species are able to substitute for them. Wehave tested this hypothesis with respect to ecosys-tem functions relating to global change. In particu-lar, we identified five plant functional attributes—height, biomass, specific leaf area, longevity, andleaf litter quality—that determine carbon and waterfluxes. We assigned values for these functionalattributes to each of the graminoid species in alightly grazed site and in a heavily grazed site in anAustralian rangeland. Our resilience proposition

was cast in the form of three specific hypotheses inrelation to expected similarities and dissimilaritiesbetween dominant and minor species, within andbetween sites. Functional similarity—or ecologicaldistance—was determined as the euclidean distancebetween species in functional attribute space. Theanalyses provide evidence in support of the resil-ience hypothesis. Specifically, within the lightlygrazed community, dominant species were function-ally more dissimilar to one another, and function-ally similar species more widely separated in abun-dance rank, than would be expected on the basis ofaverage ecological distances in the community. Be-tween communities, depending on the test used,two of three, or three of four minor species in thelightly grazed community that were predicted toincrease in the heavily grazed community did in factdo so. Although there has been emphasis on theimportance of functional diversity in supporting theflow of ecosystem goods and services, the evidencefrom this study indicates that functional similarity(between dominant and minor species, and amongminor species) may be equally important in ensur-ing persistence (resilience) of ecosystem functionunder changing environmental conditions.

Key words: ecosystem; function; diversity; redun-dancy; resilience.

Received 12 August 1998; accepted: 24 November 19982Current address: Department of Biology, Arizona State University,Tempe, Arizona, USA.*Corresponding author, email: [email protected]

Ecosystems (1999) 2: 95–113 ECOSYSTEMSr 1999 Springer-Verlag

95

INTRODUCTION

Most diversity–function studies have related, in oneway or another, number of species to ecosystembiomass or production. Some [for example, Mc-Naughton (1985) and Tilman (1996)] have shownthat year-to-year variation in species abundancetends to stabilize community biomass, and a few[Vitousek and Hooper (1993) and Hooper andVitousek (1997), for example] have consideredaspects of ecosystem function other than biomass.Less emphasis has been given to the differentcharacteristics or performance attributes of the indi-vidual species present. The debate is now shifting,however, to recognize that the provision of ecosys-tem services and functions is likely to be related tothe distribution of species among guilds or func-tional groups, and that these distributions may beonly weakly related to diversity as measured bynumbers of species [for instance, see Leps andothers (1982), MacGillivray and Grime (1995), Til-man and others (1997), Wardle and others (1997),and Naeem (1998)]. Improving our understandingof diversity–function relationships across ecosys-tems will require a categorization of species, or ofspecies attributes, that can be related to function.

In this report, we explore the hypothesis thatsome groups of dominant and minor species withinan ecosystem are functionally similar, and that thisfunctional similarity provides ‘‘buffering’’ or resil-ience against perturbations or environmental vari-ability. Thus, the species that dominate under agiven set of environmental conditions serve tomaintain ecosystem function under those condi-tions. Minor species, on the other hand, will befunctionally similar to dominant species, but withdifferent environmental requirements and toler-ances; these species maintain resilience in ecosys-tems by allowing the maintenance of functionunder changing conditions. Thus, under our hypoth-esis, a classification scheme that relates speciesattributes to function should produce guilds inwhich both dominant and minor species are pre-sent; moreover, dominant and minor species should‘‘switch’’ in abundance under changing environmen-tal conditions, and this abundance shift shouldaffect functional roles as well.

We develop a method for classifying plant func-tional types to examine the similarities in functionalattributes between dominant and minor species,and apply this to heavily grazed and lightly grazedsites in an Australian rangeland.

PLANT FUNCTIONAL TYPES

The literature on functional types [for example,Smith and others (1997)] is more concerned withpredicting the distribution of plant types around theworld, or with the related question of how plantspecies persist in different ecosystems, than it is withanalyzing the impact of functional–type diversity onparticular aspects of ecosystem function. Few inves-tigations thus far have developed categorizationschemes that group species into types relating to theecosystem-function role they perform. Most ‘‘func-tional’’ classification schemes have had as their goalpredicting patterns in species distributions ratherthan predicting the effects of diversity on the provi-sion or maintenance of ecosystem function. In thissense, these schemes are more correctly labeledplant–ecology–strategy schemes (PESSs) (Westoby1998) than plant–function–type schemes (PFTs).Nonetheless, in keeping with the tradition of theliterature, we call most classification schemes PFTs,even when they have been proposed as a means ofclassifying species with respect to adaptation strate-gies and thus distributions. The PFT we proposebelow, however, differs from these previous studiesin that we seek a classification that enables a directmapping to ecosystem function; we briefly reviewexisting PFTs before introducing our own scheme.

Probably the best-known scheme for plant adap-tation to the environment is the triangular model ofGrime (1979), which is based on three generalresponse strategies (competitiveness, weediness, andsurvival). Westoby (1998) has proposed an explicitthree-dimensional PFT, using three particular mea-surable plant attributes (specific leaf area, canopyheight, and seed size) that allows any plant speciesto be easily and exactly placed in the classificationscheme. The value of this approach is that it isminimal and will enable it to be widely used; thesame minimalist approach will be a requirement forany successful PFT scheme for ecosystem function.Although Westoby’s three axes do reflect functionalcontribution to some extent, they are designed tocapture in an overall way the strategies that specieshave developed for persisting in their environ-ments. These strategies for persistence may havesome bearing on the plant attributes that relate tofunction, but there is no a priori reason to expectclassification schemes based on how individual spe-cies persist over time to resemble one that is relatedto the functions that these species perform in anecosystem.

Box (1981) introduced a scheme for predictingthe presence of 90 different plant types, based on anenvironmental envelope comprised of eight biocli-

96 B. Walker and others

matic indices. Though this scheme produces a veg-etation description, the description does provide fora more functional interpretation than one based onfloristics. Similarly, Leishman and Westoby (1992)determined 43 plant attributes for some 300 speciesfrom the semiarid mulga woodlands of western NewSouth Wales in Australia. They used 8 vegetative, 9life-history, 15 phenology, and 11 seed-biology at-tributes, and concluded that the 300 species fell intofive groups that were related with respect to growthcharacteristics, reflecting adaptations of plants totheir environments. The reproductive attributes (todo with seed size and dispersal) were unrelated tothese five groups.

Of the 18 chapters in the recent InternationalGlobal Biosphere Project (IGBP) sponsored bookPlant Functional Types (Smith and others 1997), byfar the majority are concerned with the use of PFTsin dynamic models of vegetation change. To be sure,the underlying purpose of the book was to derive aglobal description of vegetation that could contrib-ute to an improved understanding of vegetation–atmosphere interactions, and some of the proposedschemes or outlines do include both demographicand ecosystem function attributes (for example, thechapters by Scholes and others, Lauenroth andothers, Walker, and Hobbs). Scholes and colleagues(1997) suggested 18 attributes for a functionalclassification of South African grasses, incorporatingcharacteristics that relate to (a) the distribution ofthe grass species in environmental space, (b) theresponses of the grasses to disturbance, and (c)functional aspects such as production. In most of thework to date, though, the emphasis has been primar-ily on how vegetation composition will respond tochanges in climate or to disturbance of some sort, asexemplified by the ‘‘vital attributes’’ scheme ofNoble and Slatyer (1980).

A review of plant functional classifications byLavorel and others (1997) identified four types offunctional groupings, one of which (their thirdtype) concerns the functions that plants perform.However, this type is defined in relation to ‘‘eitherthe contribution of species to ecosystem processes orto the response of species to changes in environmen-tal variables.’’ The species within such functionalgroups are therefore assumed to be similar in bothrespects—contribution to processes and response toenvironment. In accordance with the distinctionmade by Walker (1997) between ‘‘response func-tions’’ and ‘‘feedback functions,’’ we believe thesetwo types of functions—response and contribution—are significantly different and the differences are thebasis for maintaining ecosystem resilience, as weproposed above and shall demonstrate below. In

other words, dominant and minor species may besimilar in their contribution to function, but will bedifferent in response, thus permitting a ‘‘reservoir ofresilience’’ that allows maintenance of functionunder shifting conditions. Hurlbert (1997) has ad-dressed the influence species have on the ‘‘bioceno-ses’’ in which they occur and offers a measure of thefunctional importance of a species, which he definesas the sum, over all species, of the changes (signignored) in productivity that would occur on re-moval of the particular species from the biocenosis.As he points out, however, the functional values sodefined cannot reasonably be empirically measured.

Pahl-Wostl (1995) offers a diversity measure forprimary producers, Dp, which she defines as ‘‘ameasure of dynamic and functional diversity.’’ Shehas developed a theory of ecosystems as networksand uses information theory to measure the level oforganization (and, conversely, of redundancy) in anecosystem. Her concept is based on placing allorganisms into delineated overlapping groups. Shedefines ‘‘dynamic classes’’ (based on turnover times)and ‘‘functional niches’’ in a number of ‘‘spatialdimensions’’ that co-occur in particular ‘‘time inter-vals.’’ While her derived ‘trophic dynamic modules’are worth further consideration, her diversity mea-sure is difficult to use. It does not relate to anyspecific functions, and it would be very difficult toget the information needed to apply it to anyecosystem.

In keeping with the emphasis of the meeting thatstimulated this study (see the Acknowledgments),we concentrate on how to use plant functionalattributes in analyses of ecosystem function. Thequestion we are concerned with, therefore, is notone of how the vegetation on a site might change inresponse to climate change or some other distur-bance, but rather, given a change in the vegetation(that is, a change in or loss of plant biodiversity, forwhatever reason), what will be the consequencesfor ecosystem function? It is analogous to Hurlbert’s(1997) definition of functional importance, butcould and should include more than just productiv-ity as a measure of function.

THE ROLES OF DOMINANT AND MINOR

SPECIES: AN HYPOTHESIS RELATING

FUNCTIONAL DIVERSITY TO RESILIENCE

IN ECOSYSTEM PROCESSES

Figure 1, from a savanna rangeland in southwestQueensland, is an example of the classic distributionof species abundance in a community. A few speciesmake up the bulk of the biomass, and there is a longtail of relatively unabundant species. The particular

Ecosystem Function and Plant Attribute Diversity 97

shape of the curve varies between ecosystem types(flatter for tropical forests) and stages of succession[flatter for older communities; for example, seeBazzaz (1975)]. Whatever the particular shape,most of the biodiversity in the world lies in this tail.It includes the bulk of what Hurlbert (1997) de-scribes as the ‘‘great biocenotic proletariat.’’ Takingbiomass as one indicator of ecosystem function(carbon storage, for instance), it is therefore reason-able to conclude that it is the small set of relativelyabundant species that are functionally important.These few species are doing the bulk of photosynthe-sis, transpiration, nutrient uptake, and so on. If weconsider other functions, such as nitrogen fixation,it is likely, in systems where there is significantnitrogen fixation, that most of the symbiotic nitro-gen fixation will be done by just a few, relativelyabundant, plant species. What, then, is the role ofthe tail-end species? We propose, in line with the‘‘insurance’’ hypothesis (Main 1982; Walker 1995;Naeem and Li 1997), that the abundant speciescontribute to ecosystem function or performance atany particular time, whereas the tail-end speciescontribute to ecosystem resilience.

We hypothesize that the small number of domi-nant plant species have somewhat different at-tributes in terms of the ecosystem functions theyperform (CO2 fixation, water uptake from the soil,and the like). The numerous other species, which all

individually make up just a small percentage ofplant biomass or cover, are mostly functional equiva-lents of the dominant species, but with differentenvironmental requirements and tolerances. Particu-lar species in the tail are in the same functional typeas a dominant species, in terms of the ecosystemfunction they perform, but they are in differentfunctional types in terms of their response to envi-ronmental variables. Because of these differences,they provide the response capability of the ecosys-tem to disturbance and change. In other words, theycontribute to ecosystem resilience. They are low inabundance because the conditions at the time favorthe dominants. Some, for example, are competi-tively inferior to similar but more abundant species,and thus interspecific competitive interactions sup-press their abundance in the community.

There are, of course, exceptions to this pattern,since there are other reasons why species may berare or low in abundance within a community.Some are habitat specialists, others are importantkeystone species, and some are minor ‘‘passenger’’species (Walker 1992) that manage to maintainthemselves in the ecosystem but do not seem to playany role in driving it.

For the most part, however, we contend that theminor species differ in their response capabilities(traits) from their abundant counterparts, and thefunction to which they (that is, the dominantspecies plus its minor counterpart species) collec-tively contribute is secured in the face of environ-mental change because of this diversity of responsecapability. It is easy to imagine how this might be sofor tail-end species that are at the edges of theirenvironmental ranges. Arid-adapted species hang-ing on in small amounts in a mesic communityprovide the capacity for the community to respondduring periods of drought, and so on.

ECOLOGICAL DISTANCE IN PLANT

ATTRIBUTE SPACE

For an analysis of the role of biodiversity in ecosys-tem function, it is appropriate to consider only thoseplant attributes that relate to the functions of inter-est. In the sense of the conceptual model of PFTsproposed by Smith and colleagues (1993), we focuson the intensive characters that are related to param-eters in models of ecosystem function, rather thanthe extensive characters that are related more to lifecycle and ‘‘response’’ features. Furthermore, in or-der to contribute to resource-use policy and manage-ment, ecosystem function has to be defined in termsof human use or interest, and the relationshipbetween biodiversity and function has to be exam-

Figure 1. (a) Relative abundance of all species and (b)standardized abundance of grass and sedge species in alightly grazed rangeland site in southwest Queensland,Australia.


ined in the context of specific functions. A generalrelationship is unlikely to be meaningful (Wood-ward and others 1997). Since the focus of thisanalysis was global change, the functions of concernare therefore

● Carbon stocks

● Carbon fluxes

● Nitrogen fluxes

● Evapotranspiration

Different plants have different attributes thataffect the above functions in different ways. Combin-ing these attributes leads to the formation of eitherattribute sets or PFTs.

The distance that two PFTs (or species) are apartin the attribute space is a measure of their ‘‘ecologi-cal distance.’’ The ecological distances provide ameasure of both functional diversity and functionalredundancy (resilience); large ecological distancesbetween species implies functional diversity, whereassmall distances implies some degree of functionalredundancy. If a function-based ecological distanceis used in the estimation of biodiversity, the func-tional group diversity so obtained will (it is asserted)give stronger relationships between diversity andfunction than those obtained so far. Tilman andcolleagues (1997) and Roi (CNRS, Montpellier, per-sonal communication) have both shown, experi-mentally, that it is the inclusion of plants fromdifferent functional groups that influences totalbiomass, rather than just the addition of morespecies.

For the global-change functions of concern, theset of plant functions and their associated plantattributes are likely to include the following:

1. C & N cycling (C stocks, C fluxes, and N fluxes)Plant functions: Net amount of carbon fixed andstored per year; maximum carbon storage; sea-sonal changes in carbon storage; annual nitrogenreleases from litter; nitrogen retention in plants;nitrogen fixation rate.Plant attributes: Relative growth rate [approxi-mated by specific leaf area (SLA); see Westoby(1998) for discussion]; maximum total biomass(on a per-hectare basis); deciduousness; longev-ity (annual, biennial, and so on); growth phenol-ogy; plant architecture (for example, height);N-fixing capacity; leaf litter quality (for example,nitrogen–carbon or lignin–nitrogen ratios), whichdetermines the rate of litter decomposition andtherefore release of both carbon and nitrogen.

2. Water budgetPlant functions: Total transpiration; water uptakeby roots from different soil layers.

Plant attributes: Water-use efficiency; transpira-tion rate; rooting depth; root-distribution in pro-file.

For most ecosystems, some of these attributes willbe difficult to assess because the data are notavailable and cannot be acquired on reasonabletime scales. To be useful, a PFT classification willhave to include attributes that can be easily mea-sured for all species. For an initial test of ourhypothesis, we selected those attributes for whichwe already had data or for which we could assign aclassification in a multilevel ‘‘high/low’’ pointscheme. Thus, we consider the following five at-tributes of plants as a suggested set that (a) can beeasily measured and (b) are related to the functionsimportant for global change, outlined above:

HeightMature plant biomassSLA (related to relative growth rate)LongevityLeaf litter quality

We thus omit growth phenology, N-fixing capac-ity, and root distribution from consideration. Thesemeasures are difficult to obtain and were not avail-able for the Australian rangeland used in this report.Moreover, we did not explicitly include matureplant biomass or litter quality in our attribute set,but instead used related measures of lateral coverand leaf coarseness.

Some cautionary comments about the use of thisapproach are appropriate here. To begin with, theplacement of species in this five-dimension attributespace implies orthogonality between the attributes,and this is unlikely to be true. For example, if theSLA of a plant is related in some way to plantlongevity or leaf coarseness, then the loss of aspecies with a particular SLA also means the loss of aspecies with a particular life span or litter quality.

A further complication is the long-term versusshort-term effects of species. Although two speciesmay share the same attribute values for the aboveset, they may differ in terms of their longer-termfeedback effects on the ecosystem. For example, J.Roi (CNRS, Montpellier, personal communication)has shown that although it makes no difference interms of annual biomass production whether hisexperimental plots have one or several C3 grassspecies, each grass species induces a different compo-sition of soil biota, and the long-term effect on soilproperties may therefore be different. If a long-termview of function is considered, then the associatedsoil biota may need to become another attribute axisalong which plant species differ.

Finally, several of the attributes deemed to be


important in terms of contribution to ecosystemfunction are also important in terms of species’abilities to respond to environmental change (forexample, rooting depth and longevity). Because ofthis, there is unlikely to be a simple, linear relation-ship between total attribute diversity and currentecosystem function. The relationship will be stron-ger if function is considered as sustained perfor-mance over a long period, and potentially weaker ifone correlates function immediately after a pertur-bation with total attribute diversity.

MEASURING FUNCTIONAL

ATTRIBUTE DIVERSITY

We suggested two appropriate measures of func-tional attribute diversity (FAD):

FAD1: The number of different attribute combina-tions that occurs in the community. This must beequal to or less than the number of species. In thecontext of phylogenetic diversity, it is analogous tothe number of species, or species richness.FAD2: The standardized distance the species areapart in attribute space. Use of absolute values isinappropriate, since the attributes are measured indifferent units. Also, given the state of knowledgeabout the quantitative values of these attributes, it isonly possible to put many of them into a number ofclasses. The use of a normalized scale allows us todevelop at least a preliminary estimate of functionaldiversity, and in the example below we have used afive-point scale.

The simplest measure of distance apart that hasbeen used in ecology is the euclidean distance(ecological distance, ED):

EDjk 5 3oi51

I

(Aij 2 Aik)241/2

(1a)

where Aij and Aik are the attribute values of species j,k for attribute i, and I is the total number ofattributes being considered.

We have used a modified version of ED for mostof our analyses, and omit the square-root from Eq.(1a); thus, our ecological distance is given by

EDjk 5 3oi51

I

(Aij 2 Aik)24 (1b)

Use of Eq. (1b) over Eq. (1a) has the effect ofspreading species out in attribute space, and thuscan make similarities and differences in functionalattributes easier to identify. Because the two ecologi-cal distances are directly related to each other, use of

Eq. (1b) over Eq. (1a) does not affect the conclu-sions presented below.

If sites or individuals differ in the number ofspecies (or attributes), the use of euclidean distancecan have drawbacks, but in this case all five at-tributes are measured for all species in the calcula-tion of ED and it is therefore an appropriate mea-sure.

Having created a matrix of ED values for thespecies, the index of FAD can be calculated as thesum of the distances the species are apart:

FAD2 5 oi51

n

oj5i

n

EDij (2)

where n 5 the number of speciesThere is no direct analogue of this measure in

phylogenetic diversity terms, but the closest wouldbe a measure of phylogenetic distance, involvingdifferences in genera and families [for example, seeFaith (1992)]. This index takes no account of theabundances of the species. Weighting the FAD2 byabundance of species would bring it to the equiva-lent of the Shannon-Weaver measure (H) or Simp-son’s index, but we see no reason to do this (as willbecome evident).

TESTING THE HYPOTHESIS: AN EXAMPLE

FROM A SAVANNA COMMUNITY

To provide a focus, we have used a savanna range-land community in southwest Queensland, Austra-lia (Figure 1, lightly grazed site). The data are from astudy examining the effects of artificial water sup-plies on rangeland biodiversity (Landsberg and oth-ers 1997) and includes five sites along a grazinggradient, from very heavy grazing near the waterpoint (site 1) to very light grazing around 6 km fromwater (site 5). Table 1 presents the species composi-tion of sites 1 and 5 (the heavily grazed and thelightly grazed sites).

Since the focus of our interest was on the func-tional diversity of the graminoids and how they (a)contribute to overall grass production and (b) re-spond to grazing pressure, and because we wereunable to get estimates of the attributes for thedicotyledonous species, we have, for the purposes ofthis study, restricted our attention to the graminoidcommunity (see Figure 1b for the distribution ofgraminoid abundance at the lightly grazed site). Weestimated the values of the five functional attributesfor each of the 21 grass species and one sedge speciesin the rangeland, based on what is known aboutthem and using specimens from a reference collec-tion from the study area. To standardize for compari-


sons between attributes, we converted each at-tribute to a scale of 1–5. The five-point classificationscheme for each of the five attributes is presented inTable 2. SLA (dry weight/leaf area) was determinedfrom leaf samples from the reference collection. For

leaf litter quality, we used a very rough estimate ofleaf coarseness and have included it only for thesake of the example. We did not have data formature plant biomass and have used a measure oflateral cover instead. Together with height, this

Table 1. Relative Abundance (RA), Determined as Percentage Frequency of Species in 80 by 1-m2 Quadratsat the Lightly Grazed (LG) and Heavily Grazed (HG) Sites

Species

RA%

Species

RA%

LG HG LG HG

GrassAristida contorta 6.56 4.59Tripogon loliiformis 5.91 10.11Enneapogon polyphyllus 4.60 3.68Aristida latifolia 3.94 —Themeda triandra 2.52 —Digitaria brownii 2.19 1.68Chloris pectinata 1.42 2.45Eragrostis microcarpa 0.98 1.23Eriachne pulchella 0.88 3.06Panicum effusum 0.88 —Sporobolus actinocladus 0.77 —Digitaria ammophila 0.77 —Dichanthium sericeum 0.66 —Austrochloris dicanthioides 0.55 —Tragus australianus 0.33 0.61Eragrostis basedownii 0.33 —Monachather paradoxa 0.33 —Amphipogon caricinus 0.22 —Eragrostis dielsii 0.22 3.22Thyridolepis mitchelliana 0.22 0.46Eragrostis xerophila — 1.07

SedgeFimbristylis dichotoma 4.38 8.27

ForbsEvolvulus alsinoides 5.36 2.14Calotis hispidula 5.25 6.58Calotis plumulifera 4.70 5.51Rhodanthe floribunda 4.49 8.42Plantago turrifera 2.74 3.52Goodenia pinnatifida 2.63 2.91Stenopetalum nutans 2.52 —Vittadinia constricta 2.30 1.84Phyllanthus lacunellus 2.08 0.92Centipeda thespidioides 1.97 3.68Daucus glochidiatus 1.53 0.15Ptilotus macrocephalus 1.53 —Chamaesyce drummondii 1.53 0.15Trachymene ochracea 1.53 0.31Alternanthera angustifolia 1.42 1.53Calandrinia eremaea 1.20 0.31Lepidiummuelleri–ferdinandii 1.09 5.82Chenopodium melanocarpum 0.88 1.38

Forbs cont.Glycine canescens 0.88 0.31Bulbine alata 0.88 0.15Boerhavia repleta 0.88 0.46Ptilotus gaudichaudii 0.77 0.77Marsilea drummondii 0.77 —Calocephalus knappi 0.77 —Calotis inermis 0.66 1.53Convolvulus erubescens 0.66 0.31Portulaca filifolia 0.66 —Goodenia cycloptera 0.66 —Wahlenbergia sp. 0.66 0.46Gnephosis arachnoidea 0.55 —Portulaca oleracea 0.55 1.07Chrysocephalum sp. 0.44 1.84Lepidium oxytrichum 0.33 0.61Heliotropium tenuifolium 0.33 0.15Tribulus terrestris 0.33 —Goodenia lunata 0.33 0.77Goodenia berardiana 0.22 —Pimelea elongata 0.22 —Goodenia glauca 0.11 0.15Hyalosperma semisterile 0.11 —Calotis cuneifolia 0.11 —Dianella longifolia var. porracea 0.11 —Spergularia sp. 0.11 —Tricoryne elatior 0.11 —Ptilotus helipteroides var.helipteroides — 0.46Calandrinia ptychosperma — 0.77Chenopodium cristatum — 0.61Dysphania glomulifera — 0.15Oxalis corniculata — 1.38

SubshrubsAbutilon macrum 1.31 0.77Sida cunninghamii 1.09 —Sida platycalyx 0.88 0.77Sida species nov. aff. filiformis 0.55 0.15Solanum quadriloculatum 0.22 —Abutilon otocarpum 0.11 —Malvastrum americanum 0.11 —Sclerolaena cornishiana 0.11 0.46Solanum esuriale 0.11 0.15Sclerolaena diacantha — 0.15


reflects the overall size of a plant. Height wasdetermined as the maximum height of the basalleaves (that is, excluding culms).

Very little is known about the functional at-tributes of these (or any other) species, and for anumber of the attributes it was difficult to placesome species with confidence into a particular class.In these cases, we had to resort to informed guessesbased on what was known about the species. Thevalues given are likely ranges for different kinds ofspecies in this savanna, and the example serves thepurpose of illustrating how functional attribute

diversity might be measured and used to examinethe structure of ecosystems.

The final set of five attribute values for the 22grass/sedge species is presented in Table 3, and thematrix of ecological distances [using Eq. (1b)] for all22 species is presented in Table 4.

TEST 1: THE LIGHTLY

GRAZED COMMUNITY

Our hypotheses concerning the role of dominantand minor species in maintaining functional diver-

Table 2. Functional Attributes of the Herbaceous Layer

FunctionalAttribute Value Height (cm) SLAa (mm mg21) Longevity (years) Cover (%) Leaf Coarseness

1 ,5 ,4 Annual 40–60 Coarse2 5–10 4–83 10–15 8–12 Biannual 60–80 Medium4 15–20 12–165 .20 .16 .2 years .80 Soft

aCorrelated with relative growth rate (see the text) where a rank of 1 is slow and 5 is fast.

Table 3. Frequency (Maximum of 80) and Functional Attribute Values for the Graminoid Speciesat the Lightly Grazed (LG) and Heavily Grazed (HG) Sites

Species

Frequency Functional Attribute

LG HG Height SLA Longevity Cover Leaf Coarseness

(1)Aristida contorta 60 30 4 2 3 5 1(2)Tripogon loliiformis 54 66 1 3 5 3 5(3)Enneapogon polyphyllus 42 24 3 2 3 1 5(4)Fimbristylis dichotoma 40 54 1 5 5 1 3(5)Aristida latifolia 36 — 4 2 5 5 1(6)Themeda triandra 23 — 4 1 5 5 3(7)Digitaria brownii 20 11 5 5 5 3 3(8)Chloris pectinata 13 16 1 3 3 3 3(9)Eragrostis microcarpa 9 8 3 2 3 3 1

(10)Eriachne pulchella 8 20 3 2 1 1 3(11)Panicum effusum 8 — 3 1 3 3 3(12)Sporobolus actinocladus 7 — 3 1 3 3 3(13)Digitaria ammophila 7 — 5 5 5 3 3(14)Dichanthium sericeum 6 — 5 3 3 3 3(15)Austrochloris dicanthioides 5 — 5 3 5 3 3(16)Tragus australianus 3 4 1 5 1 3 1(17)Eragrostis basedownii 3 — 2 3 1 1 3(18)Monachather paradoxa 3 — 3 3 5 3 3(19)Eragrostis dielsii 2 21 3 2 3 1 3(20)Amphipogon caricinus 2 — 5 3 5 5 3(21)Thyridolepis mitchelliana 2 3 4 3 5 1 3(22)Eragrostis xerophila — 7 4 2 5 5 1

SLA, specific leaf area.


sity and resilience in ecosystems leads to certainpredictions regarding species relationships and eco-logical distances within an unperturbed system. Inparticular, we would expect that

1. Dominant species would be functionally dis-similar to each other (as it would be the differencesin functional ‘‘niches’’ that would allow thesespecies to be codominant in a system) and, con-versely,

2. Functionally similar species would be separatedin rank—that is, those species most functionallysimilar to dominant species would be found amongthe tail-end (minor) species.

But which ecological distances could be catego-rized as being functionally similar, and what ecologi-

cal distance would two species have to exceed tobe considered functionally dissimilar? Figure 2shows the histogram of ecological distances takenfrom Table 4. The average ED for all species pairsin the community is 18. Based on apparent group-ings, we have divided the histogram into fourcategories of relatedness. Thus, functionally similarspecies are taken to be those whose EDs are # 6. Thenext clustering of EDs occurs for 8 # ED # 14, andso on. Other categorizations were possible—forinstance, one can subdivide the above grouping andidentify a clump for 8 # ED # 10 and another for12 # ED # 14—but for our purposes fewer largecategories were more useful than several smallcategories.

Figure 2. Frequencies ofecological distances for allspecies pairs, taken fromTable 4. Groupings reflectapparent clusters of fre-quent ecological distances(black, stippled, striped, orwhite bars); the lower theecological distance, themore functionally similarare the two species.

Table 4. Ecological Distances Between Species


Therefore, from Figure 2, we have

Functionallysimilar

0 $ ED # 6 12% of all pair-wisecomparisons

Similar toaverage

7 # ED # 14 37% of all pair-wisecomparisons

Average todissimilar

16 # ED # 30 38% of all pair-wisecomparisons

Functionallydissimilar

ED $ 33 14% of all pair-wisecomparisons

Note that for two species to have an ED 5 6, theycan, from Eq. (1b), differ by at most 1 unit for eachof the five attributes, or 2 units for one attribute and1 unit for two attributes (being equal in two otherattributes). Note also that if we had chosen morethan five attributes for classification, our thresholdvalue of ecological distance for similar species mayhave exceeded 6. If, for instance, we had chosen 10attributes for classification, we might have foundthat functionally similar species had ED , 12.

Consider hypothesis 1 above: Are the dominantspecies functionally dissimilar? The top five speciesaccount for two-thirds of the relative abundances ofthe graminoid species in this system (Aristida con-torta to A. latifolia in Table 3). If we consider only theecological distances between these species (shownin Table 5), we find that, of the 10 possible EDs, 50%can be categorized as being ‘‘functionally dissimilar’’(ED $ 33). In contrast, only 14% of the EDs amongthe full complement of 22 species (Table 4) aregreater than 33. Thus, the expectation for func-tional dissimilarity among the top five species basedon the average ecological distance in the commu-nity would be 1 or 2 $ 33, rather than the fiveobserved. Using a x2 test, the probabilities of obtain-ing the observed five EDs $ 33 are either just over10% (for expected 5 2) or less than 1% (forexpected 5 1). Moreover, though not statisticallysignificant, 70% of the EDs are more dissimilar thanthe community average of 18, compared with 44%of the EDs in the full community. Thus, the domi-nant species are more dissimilar than one wouldexpect given the average ecological distances pres-ent in the community.

In addition, we predict (from hypothesis 2 above)that functionally similar species are more likely tobe widely separated in rank (as determined byabundance). Consider Figure 3, which again showsthe rank–abundance curve for the lightly grazedcommunity, as in Figure 1. In this figure, however,species are grouped by ecological distance. Forinstance, the highest ranking species (no. 1: A.contorta) has two functionally similar species (ED #6)—A. latifolia (rank 5) and Eragrostis microcarpa(rank 9). All three species are thus labeled A. [Notethat A. latifolia and E. microcarpa are in the ‘‘similarto average’’ category in regard to each other (ED 59, Table 4). The comparison here is between each ofthem and the most dominant species, A. contorta.)Similarly, the third-ranked species, Enneapogon poly-phyllus, is functionally similar to the least-abundantspecies in the lightly grazed community, Thyridolepismitchelliana. These two species are grouped togetherand labeled B. Continuing in this fashion for the top10 dominants, we get the pattern shown in Figure 3.(Note that once a species is assigned to a group—A,B, C, and so on—it is not considered for member-ship in another group.)

Of the species falling in the top half of therank–abundance curve, three have no functionallysimilar species [Tripogon loliiformis (no. 2), Fimbristy-lis dichotoma (no. 4), and Chloris pectinata (no. 8)].Four have functionally similar counterparts in the

Figure 3. Functional similarities between dominant andminor species. See the text for an explanation of thegrouping procedure.

Table 5. Ecological Distances Between the Dominant Species (Five Most Abundant Speciesin the Lightly Grazed Community)

Aristida Contorta Tripogon Loliiformis Enneapogon Polyphyllus Fimbristylis Dichotoma

Tripogon loliiformis 34 — — —Enneapogon polyphyllus 33 13 — —Fimbristylis dichotoma 42 12 21 —Aristida latifolia 4 30 37 38


minor, tail-end species (groups B, C, D, and E).Three are functionally similar to each other (groupA); note, however, that although E. microcarpa (no.9) is in the top half, it is minor relative to thedominant A. contorta (no. 1). Thus, we do findevidence for significant functional similarity be-tween dominant and minor species in the lightlygrazed community.

Other functionally similar species pairs are notrepresented in Figure 3. For instance, the minorspecies Monachather paradoxa (no. 18), Amphipogoncaricinus (no. 20), and T. mitchelliana (no. 21) are allfunctionally similar to another minor species, Austro-chloris dicanthioides (no. 15). According to the secondpart of our hypothesis (which we test in the follow-ing section), A. dicanthioides could increase in abun-dance if a disturbance caused its functionally similardominant species, Digitaria brownii (both labeled Din Figure 3), to decrease in abundance. Then M.paradoxa, Amphipogon caricinus, and T. mitchellianawould provide the ‘‘reservoir of resilience’’ for thenow dominant Austrochloris dicanthioides. This sug-gests that maintaining resilience in ecosystems mightnot only require that there be functional similaritybetween dominant and minor species, but thatthere be functional similarity among minor speciesas well, so that resilience is maintained in the face offurther perturbations and shifts in abundance. Wereturn later to the question of ‘‘ideal’’ communitydistributions for ecological distances and functionalsimilarities or dissimilarities.

Taking the same approach to creating Figure 3,but with a different definition of ‘‘functionally simi-lar’’ (ED # 14, thus incorporating the first twogroupings in Figure 2), produces qualitatively simi-lar results. In the interest of space, we do not showthe figure here, but in this case all of the speciesfalling in the top half of the abundance curve havefunctionally similar species falling into four possiblecategories (A–D), and the functionally similar spe-cies in groups A, C, and D span the two halves of thecurve. It is only those species in group B (that is,those species functionally similar to the second-rank species Tripogon loliiformis) that do not havecounterparts in the tail of the rank–abundancecurve, but Chloris pectinata (no. 8) is functionallysimilar to T. loliiformis and could be consideredminor relative to T. loliiformis.

We conclude from these tests that the distributionof EDs in the lightly grazed community lends sup-port to our hypothesis. The dominant species areresponsible for function, and they are functionallydissimilar from one another. The minor speciesprovide resilience in the system—they are function-ally similar to dominant species and could increase

in abundance and maintain function if dominantspecies were to decline or disappear.

TEST 2: A COMPARISON OF THE HEAVILY

GRAZED AND LIGHTLY GRAZED

COMMUNITIES

Our hypothesis goes beyond predictions of thedistribution of ecological distances within a commu-nity. In particular, we would predict that the loss ordecline of a dominant species would lead to acompensatory increase in abundance of a function-ally similar minor species. Thus, we examine differ-ences in abundances and species composition be-tween the lightly grazed (relatively unperturbed siteabove) and a previously similar community that hasexperienced intensive grazing, and determinewhether a species decline under heavy grazing isaccompanied by an abundance increase in a func-tionally similar species. Due to inherent site differ-ences, the two communities are unlikely to havebeen identical prior to grazing by livestock, so wecannot expect a perfect fit with the hypothesis;nonetheless, we seek evidence that minor speciesare contributing to a compensatory functional re-sponse in the system under grazing stresses.

Analyzing this dynamic first requires that we areable to identify which species have undergone a‘‘significant’’ decline in abundance and which haveexhibited a ‘‘significant’’ increase. If we fit an expo-nential to the scaled (that is, sum to 100%) rank–abundance data in Table 1 (lightly grazed commu-nity), we find that, for the nth-ranked species, theabundance is approximated by

A(n) 5 A(dominant) Exp [20.19(n 2 1)]

where A(dominant) is the scaled relative abun-dance of the dominant species, Aristida contorta. Ashift in rank of 5, therefore, would correspondapproximately to an increase or decrease in abun-dance of a factor e [5 Exp(1)]. Therefore, we (ratherarbitrarily) take as our measure of significance ashift in abundance that would increase or decreaserank by five steps (if all other species were tomaintain the same relative abundance)—in otherwords, a significant increase in abundance requiresLn[lightly grazed abundance 4 heavily grazed abun-dance] .1, and a significant decrease requiresLn[lightly grazed abundance 4 heavily grazed abun-dance] , 21.

There are 10 grass species that disappear in theheavily grazed community relative to the lightlygrazed community (Table 1) and thus are consid-ered to show significant decreases in abundance(though, as previously mentioned, some of them


may not have been present in the original lightlygrazed community). No other species meet theaforementioned requirements for significant de-crease. Three grass species that show a significantincrease in abundance are listed in Table 6.

Our hypothesis would suggest that the speciesundergoing an increase in abundance under heavygrazing should be functionally similar to at least onespecies undergoing a decrease. Are those functionalsimilarities evident? Table 7 shows that each of thethree species that increase in abundance is function-ally similar (ED # 6) to at least one species thatdisappears under heavy grazing. Moreover, the sumof the minimum ecological distances for each of thethree species—as measured from those species thatdecline in abundance—is only 7.

Perhaps, however, this appearance of functionalsimilarity is only coincidental. If we were to ran-

domly select 13 species from the full complement of22 grass/sedge species and designate 10 as decreas-ing in abundance (high to low, or H–L) and theremaining 3 as increasing in abundance (low tohigh, or L–H), would we find equally low ecologicaldistances (Table 4)? We randomly generated 1000such species collections and calculated the ecologi-cal distance between each L–H species and the mostfunctionally similar H–L species. Of the 1000 com-munities so generated, 27% had all three minimumEDs fall in the ‘‘functionally similar’’ category (thatis, ED # 6). Only 5% of the communities, however,had a sum of the three minimum EDs that was lessthan 7 (the sum given in Table 4 for the actualcommunity).

Note again that this result holds even if we changeour definition of ‘‘functionally similar’’ to include allspecies pairs with ED # 14. We would still find thatthe functional similarities among species that shiftin abundance in the heavily grazed and lightlygrazed communities are closer than would be ex-pected—given the existing distribution of EDs in thecommunity—if such abundance shifts were ran-dom, or appeared random because they were beingdriven by mechanisms other than functional similar-ity and competitive exclusion.

Taken together, the foregoing results providesupporting evidence that functionally similar minorspecies in our rangeland site were able to increase inabundance and thus maintain some function in theecosystem under changing conditions, when theirdominant counterparts declined in abundance. Butcan we provide a further test? Given that we knowwhich 10 species disappeared from the systemunder heavy grazing, can we predict which speciesshould increase in abundance?

TEST 3: PREDICTING WHICH SPECIES

SHOULD INCREASE IN RESPONSE

TO DISTURBANCE

The species we select should be (a) functionallysimilar to a disappearing species and (b) significantlyless abundant in the lightly grazed system than thedisappearing species (so that it qualifies as being a‘‘minor’’ species relative to a ‘‘dominant’’ species).Thus, for each species that disappears under heavygrazing, we identify the species that have ED # 6,and A(UG)minor , A(UG)dominant/Exp(1); we hypoth-esize that the species meeting these criteria arelikely to increase in abundance under heavy grazingafter the demise of their functionally similar domi-nant counterparts.

Table 8 identifies each of these species. Threespecies emerge as likely to increase in abundance

Table 6. Significant Shifts in Species AbundancesBetween the Lightly Grazed and HeavilyGrazed Sites

Species ShowingSignificant Decreasein Abundance Dueto Heavy Grazing

Species ShowingSignificant Increasein Abundance Dueto Heavy Grazing

Aristida latifolia Eriachne pulchellaThemeda triandra Eragrostis dielsiiPanicum effusum Eragrostis xerophilaSporobolus actinocladusDigitaria ammophilaDichanthium sericeumAustrochloris dicanthioidesEragrostis basedowniiMonachather paradoxaAmphipogon caricinus

Table 7. Functional Similarities BetweenDecreasing and Increasing Species

Species withIncreasedAbundanceUnder HeavyGrazing

Functionally SimilarSpecies ShowingDecline in AbundanceUnder Heavy Grazing

EcologicalDistanceBetweenSpecies

Eriachne pulchella Eragrostis basedownii 2

Eragrostis dielsii Panicum effusumSporobolus actinocladusEragrostis basedownii

556

Eragrostis xerophila Aristida latifoliaThemeda triandraAmphipogon caricinus

053


under heavy grazing: Amphipogon caricinus, Eragros-tis xerophila, and Eragrostis dielsii. The latter twoactually do increase in abundance; the first disap-pears under heavy grazing. Two other species—Thyridolepis mitchelliana and Tragus australiensis—increase in relative abundance, but not significantlyby our arbitrary definition. If we regarded a shift inabundance rank of 4 as significant, then T.mitchelliana would be just on ‘‘significance.’’ Tragusaustraliensis changes only three rank positions. (Notethat the use of the changes in rank to indicatesignificance of relative abundance requires use ofscaled, relative values). In addition, Eriachne pul-chella does increase in abundance under heavygrazing, though we fail to predict its increase in

Table 8. Eriachne pulchella is functionally similar toEragrostis basedownii, but the abundance differencesin the lightly grazed system are not such that onewould expect a significant increase in E. pulchellaafter the disappearance of E. basedownii. If E. basedow-nii were the functionally similar and functionallysuperior species resulting in a competitive suppres-sion (and thus low abundance) for E. pulchella in thelightly grazed system, then one would expect higherabundances for E. basedownii than for E. pulchella inthe lightly grazed system; the opposite pattern isobserved.

Note that, for a number of reasons, we would notexpect this approach to provide perfect predictionsfor abundance shifts under heavy grazing. We pre-

Table 8. Method for Predicting Which Species Should Increase in Abundance Under Heavy Grazingwhen ‘‘Functionally Similar’’ Is Defined as Ecological Distance I6

Species that DisappearUnder Heavy Grazing

All Functionally Similar Species(Ecological Distance in Parentheses)

Are Functionally SimilarSpecies SignificantlyLower in Abundance?

Species that ShouldIncrease in AbundanceUnder Heavy Grazing

Aristida latifolia E. xerophila (0) Yes E. xerophilaT. triandra (5) NoA. caricinus (3) Yes A. caricinus

Themeda triandra A. latifolia (5) NoA. caricinus (6) Yes A. caricinusE. xerophila (5) Yes E. xerophila

Panicum effusum S. actinocladus (0) NoE. dielsii (5) Yes E. dielsiiE. microcarpa (5) No

Sporobolus actinocladus P. effusum (0) NoE. microcarpa (5) NoE. dielsii (5) Yes E. dielsii

Digitaria ammophila D. brownii (1) NoA. dicanthioides (5) No

Dichanthium sericeum A. dicanthioides (4) No

Austrochloris dicanthioides D. sericeum (4) NoD. brownii (4) NoD. ammophila (5) NoM. paradoxa (4) NoA. caricinus (5) No

Eragrostis basedownii E. pulchella (2) NoE. dielsii (6) No

Monachather paradoxa A. dicanthioides (4) No

Amphipogon caricinus A. dicanthioides (5) NoT. triandra (6) NoA. latifolia (3) NoE. xerophila (3) Yes E. xerophila

See Table 1 for genus names.


dict, for instance, that Amphipogon caricinus shouldincrease in abundance because its functionally simi-lar dominants—Aristida latifolia and Themeda trian-dra—decrease in abundance under heavy grazing.We do not, however, consider potential competitivesuppression by other remaining dominant species.In particular, Amphipogon caricinus is similar to Aris-tida contorta (ED 5 7); A. contorta may be function-ally suppressing A. caricinus and preventing its com-petitive release even after the loss of A. latifolia andT. triandra. Greater predictive power for shifts inabundance would require a more sophisticated un-derstanding of the relationship between functionalsimilarity and competitive exclusion than we havebeen able to develop here. In addition, factors otherthan interspecific competition can result in lowabundance or compensatory increases under pertur-bations. Here we seek only to test the hypothesisthat both functional similarities and functional dif-ferences will play important roles in communityresponse to perturbation; future improvements inmethodology would serve to increase predictivepower.

Finally, note that not all species that disappearunder heavy grazing have functionally similar mi-nor species that can take over their role (Table 8).Thus, although there will be some maintenance ofsystem function, this functional substitutability willnot be perfect; we would therefore expect somedecline in function in the system under heavygrazing.

To test the robustness of these results, we canagain repeat the preceding analysis by using themore generous definition of functionally similar;that is, by defining as functionally similar thosespecies with ED # 14. In this case, a slight modifica-tion to the approach is required. Note that in Table 8there were never more than two species thatemerged as being ‘‘likely to increase’’ under thedecline of a single species (for example, Eragrostisxerophila and Amphipogon caricinus were both pre-dicted to increase in response to the decline inAristida latifolia, but there was never a case wherethree or more species were affected by the decline ofa single species). If, however, we adopt the moregenerous definition of functionally similar (ED #14), seven species emerge as being both functionallysimilar to, and significantly less abundant than, A.latifolia (Table 9). Although the competitive releaseof two species given a decline in one seems plau-sible, the competitive release of seven species giventhe loss of one seems less plausible. Thus, for eachspecies that declined in abundance (as given in Table6), we first identified those species that were bothfunctionally similar and significantly less abundant.

We then hypothesized that the most similar speciesfrom this list was likely to increase in abundanceto fill the functional niche abandoned by its domi-nant counterpart. The remaining species were onlyassumed to increase in abundance if they werefunctionally dissimilar to this ‘‘new’’ dominant;otherwise, they were assumed to be competi-tively suppressed—due to functional similarity—by this new dominant. The details are listed inTable 9.

We predict that Amphipogon caricinus, Eragrostisxerophila, Eragrostis dielsii, and Thyridolepis mitchellianashould increase in abundance, similar to the resultswhen using the more restrictive definition of func-tional similarity, but with the addition of T.mitchelliana (which would have been included inthe more restrictive set had we used a change inrank of 4 rather than 5 to indicate a significantchange). Thus, at least in this case, the results arefairly insensitive to the exact threshold used todefine functional similarity. Note, however, that thepredictions for which species should increase inabundance upon the loss of a single species varybetween the two approaches. For instance, usingTable 8, we would predict that the loss of Aristidalatifolia would lead to increases in abundance forboth E. xerophila and A. caricinus; using Table 9, wewould predict increases for only E. xerophila. Moreextensive datasets with different patterns of specieslosses among sites would aid us in further testingthis hypothesis and determining the ‘‘appropriate’’threshold for functional similarity.

Overall, both tests we used support the proposi-tion that the minor species contain functional ana-logues of the dominants, able to increase when thedominants declined in abundance. Depending onthe test, two of three or three of the four speciespredicted to increase in abundance in the heavilygrazed site did in fact do so. Our analysis thereforeprovides some evidence that minor species in ecosys-tems do provide a ‘‘reservoir of resilience’’ throughtheir functional similarity to dominant species andtheir ability to increase in abundance and thusmaintain function under ecosystem perturbation orstress.

COMMUNITY-BASED MEASURES

OF DIVERSITY AND PERFORMANCE

Most studies on diversity–function relationshipshave attempted to examine the effects of increasingdiversity on function. Our hypothesis supports thecontention that, under a constant set of biogeocli-matic conditions, an increase in functional diversityamong the dominant species will correlate with


increased provision of certain functions in ecosys-tems (such as primary production).

If, however, the set of ‘‘functions of interest’’ isexpanded to include resilience—or the ability of asystem to maintain function under changing condi-tions—then it is not functional diversity but ratherfunctional redundancy or substitutability that main-tains the function of resilience.

These dual requirements—for diversity to main-tain current function and redundancy to maintainfuture function—suggest that one measure of diver-

sity is unlikely to capture the important functionalfeatures of an ecosystem. We simultaneously re-quire measures for functional diversity among domi-nant guilds or species, functional redundancy be-tween dominant and minor species, and functionalredundancy among minor species. Note that increas-ing both functional diversity and functional redun-dancy in ecosystems requires adding additionalspecies, but species number as a measure of func-tional contribution is inadequate to capture the dualrequirements of diversity and redundancy. Even the

Table 9. Method for Predicting Which Species Should Increase in Abundance Under Heavy Grazing when‘‘Functionally Similar’’ Is Defined as Ecological Distance (ED) I14

Species that DisappearUnder Heavy Grazing

All Functionally Similar andSignificantly Less AbundantSpecies (Ecological Distancein Parentheses)

Functionally Similar to Specieswith Lowest ED from Column 2(Shown with *)?

Species Predictedto Increase UnderHeavy Grazing

Aristida latifolia E. xerophila (0) * E. xerophilaA. caricinus (3) YesP. effusum (14) YesS. actinocladus (14) YesD. sericeum (14) YesA. dicanthioides (10) YesM. paradoxa (10) Yes

Themeda triandra E. xerophila (5) * E. xerophilaA. caricinus (6) YesP. effusum (9) YesS. actinocladus (9) YesA. dicanthioides (9) YesM. paradoxa (9) YesD. sericeum (13) YesE. microcarpa (14)

Panicum effusum E. dielsii (5) * E. dielsiiT. mitchelliana (13) YesE. xerophila (14) No E. xerophila

Sporobolus actinocladus E. dielsii (5) * E. dielsiiT. mitchelliana (13) YesE. xerophila (14) No E. xerophila

Digitaria ammophila T. mitchelliana (10) * T. mitchellianaA. caricinus (12) No A. caricinus

Dichanthium sericeum E. dielsii (9) * E. dielsiiT. mitchelliana (9) * T. mitchellianaA. caricinus (9) * A. caricinus

Austrochloris dicanthioides E. xerophila (10) * E. xerophila

Eragrostis basedownii

Monachather paradoxa E. xerophila (10) * E. xerophila

Amphipogon caricinus E. xerophila (3) * E. xerophila

See Table 1 for genus names.


functional attribute diversity measures we havesuggested (FAD1 and FAD2) fail to capture thedistributions of ecological distances in ecosystems inways that would elucidate the presence of bothfunctional diversity and functional redundancy. Table10 presents a summary analysis of communitydiversity along the grazing gradient, according toconventional species indices and analogous FADmeasures. The trends are similar, but the interpreta-tion is very limited. The decline in the standardizedFAD2 from site 1 to site 5 reflects decreased averagedistances apart in attribute space and thereforeincreased similarity in attributes between species.This is in line with the expected increase in redun-dancy at site 5 but, as Figure 2 clearly illustrates, theaverage distance has very little significance. There-fore, although we are able to develop single indicesof functional diversity, they suffer from the samedrawbacks of all such indices.

The histogram in Figure 3 may provide a measureof both functional diversity and redundancy. Butnote that there is no a priori definition of ‘‘ideal’’levels of diversity and/or redundancy in ecosys-tems. We may find that ecosystems that have beensubjected to relatively low biogeoclimatic variabilityover evolutionary time scales show greater func-tional diversity and less functional redundancy,whereas ecosystems subjected to greater biogeo-climatic variability might exhibit more functionalredundancy than diversity. Therefore, there is noone pattern for the distribution of functional diver-sity or redundancy that we should expect or desirein ecosystems, and no preexisting expectation of

how a histogram like that in Figure 3 ‘‘should’’ look.This also suggests that no one general pattern willemerge for diversity–function relationships in eco-systems, particularly as many of the publishedrelationships tend to examine the system under aparticular set of conditions and thus miss the poten-tially important role of functional redundancy andresilience.

The diversity–function debate needs to be ex-panded to include assessment of these complemen-tary and, in some cases, competing roles for func-tional types in ecosystems, and assessments of thepositive influences of increased diversity need to beaccompanied by assessments of the positive influ-ences of redundancy in maintaining ‘‘latent function-ality,’’ or resilience, in systems. Observations of theimportance of functional redundancy in maintain-ing ecosystem function have, of course, been madeelsewhere, but these observations have yet to mani-fest themselves in the diversity–function debate inany systematic way.

DISCUSSION

The tests of the various hypotheses relating toecological distances among species all lend supportto the proposition that minor species in ecologicalcommunities confer resilience in terms of ecosystemfunction. [It should be noted that we take resilienceto mean the persistence of function, or the capacityfor function to be restored after major change,rather than just the rate of return following a minorperturbation (cf. Ludwig and others 1997)]. The

Table 10. Comparison of Phylogenetic and Functional Diversity Along the Grazing Gradient from Heavy(1, near a Water Point) to Very Light (5)

Phylogenetic Index

Site

Functional Index

Site

1 2 3 4 5 1 2 3 4 5

Species richness (no. ofspecies)

12 13 16 15 21 No. of unique com-binations (FAD1)

12 12 15 15 19

a DiversitySimpsons index

C 5 oi51

s ni(ni 2 1)

N(N 2 1)

Shannon-Weaver index

H 8 5 2 oi51

s

ri ln ri

0.14

2.16

0.20

1.84

0.14

2.19

0.13

2.26

0.10

2.53

S distances apart infunctional attributespace (FAD2)

Totala

Standardized by no.of interspeciescomparisonsb

36.00.54

40.80.52

47.20.39

45.90.44

65.30.31

FAD, functional attribute diversity.aEquation 1a has been used.bThe maximum possible sum of distances has been roughly approximated.


ability of these minor species to increase in abun-dance in response to a decrease in their functionallyequivalent, dominant counterparts enables themaintenance of ecosystem function under stress ordisturbance. Of course, this is but a single test of theoverall proposition, and further investigations ofthis kind are needed. They would greatly add to ourunderstanding of the relationships between biodiver-sity and ecosystem function, and would provide thebasis for the theoretical framework needed to applythe insights gained from such studies to the under-standing and management of other ecosystems. Theapproach adopted in this study, and our attempts atdefining, measuring, and analyzing functional at-tributes, raise a number of conceptual and method-ological issues. A few of these are discussed next.

We have used a set of available data for thepurpose of setting out and exploring the proposi-tion, and it has served the purpose. Before develop-ing the approach further, however, the choice ofvariables and the measures we have used must beaddressed in more detail. In particular, the choice ofan abundance measurement for the species (thecombined relative abundance measure we haveused is not without problems), the choice of func-tional attributes, their definition, and how best toestimate them in a standardized way are all subjectto debate. There is a need for ease of measurementand repeatability [the same arguments as in Westo-by’s (1998) criteria for the PESS attributes] if func-tional diversity analysis is to become widely used.

One particular aspect of the choice of ecologicalseparation concerns the use of ecological distance(as used in this study) versus the use of minimumdistance along one axis. It is possible that resilienceis maintained in ecosystems not by each dominantspecies having one or two functionally similar mi-nor counterparts, but by having several, with eachminor counterpart similar with respect to only oneor two attributes or functions. Again, understandingthe patterns of functional compensation and abun-dance shifts under changing conditions will requiremore data and a greater range of conditions than wehave here.

Assuming the measurement issues can be re-solved (and we are confident they can be), anumber of theoretical issues arise. One of theseconcerns the argument that diversity measures basedon a phylogenetic classification capture all of theimportant, heritable differences in plant attributes[for example, see Williams and others (1997)]. Sucha proposition is initially appealing, given the presentlack of data on functional attributes. However,while the phylogeny may well capture differenttraits in a species, unless the traits can be individu-

ally identified it is not possible to get a mechanisticunderstanding of the relationship between biodiver-sity and ecosystem function. The sort of predictiveunderstanding that emerges from our analysis offunctional distances cannot be derived from a phylo-genetic classification. The similarity in patterns ofoverall trends in the phylogenetic and FAD indicesin Table 10 lends support to the argument ofWilliams and colleagues (1997), but we contendthat neither kind of index provides much insight.Only through the use of a functional analysis of thesort outlined in this report can we develop a predic-tive understanding of the relationships betweenbiodiversity and ecosystem function.

A second, interesting consideration arises out ofthe similarity in the pattern of occurrences ofecological distances in Figure 2, and the patternobtained by Holling (1992) for his data on thebody-mass difference index for various groups ofanimals. Holling’s interpretation centered on theinfluence of a few structuring processes interactingacross scales, resulting in this ‘‘lumpy’’ distribution.The significance of scale effects on ecological resil-ience is further developed by Peterson and others(1998), who propose that resilience is generated byhaving diverse, but overlapping, function within ascale and by ‘‘apparently redundant species thatoperate at different scales, thereby reinforcing func-tion across scales.’’ Our interpretation of the Austra-lian rangeland data is that the resilience is generatedby having, within each functional type, a number ofspecies with a diversity of environmental responsecapabilities. It may be that one dimension of thisresponse capacity relates to differences in space andtime scales of response (for example, dispersal dis-tances and rates of regeneration), but the mostsignificant component of diversity in our case (re-lated to the dominance of grazing as an environmen-tal pressure) involves the diversity of responses tobeing defoliated. In a general sense, it seems mostlikely that resilience in communities is generated bya diversity of response capabilities, and that theseresponse capabilities can involve both responses todifferent scales of disturbance, as well as differentresponses to an environmental disturbance at aparticular scale.

A final theoretical issue arises out of the predict-ability of the functional attributes portrayed in thisanalysis. It raises the question of how such acomplementary functional composition arises. Is itselected? If each species is selected (in an evolution-ary sense) for its survival attributes, how does afunctionally complementary set eventuate? A fortu-itous juxtapositioning of such species seems un-likely, given the results of our tests. A possible


explanation for the pattern lies in an iterativeprocess—a reciprocal feedback between individualselection and persistence of ecosystem function,something like as follows: A particular environmen-tal pattern favors a particular suite of species, andthe dominants among these are sorted out throughperformance, resulting in a complementary (ratherthan a strongly overlapping, intensely competing)set. Those that lose out in the competition (and theywould be species that do strongly overlap in perfor-mance with dominants) are either eliminated orrelegated to minor species status. If an environmen-tal change leads to a decline in a dominant, theminor species that emerges to replace it is one thatcan both thrive under the new environmentalconditions and also complement the performance ofthe remaining dominants. A complementary pat-tern of functional attributes is therefore favored,leading to persistence of the existing levels of func-tion. The continuous interplay between ecosystemform and function, between the players and theperformance, ensures that the nature of the speciescomposition of a community tends to a combinationof functional diversity and redundancy, as outlinedin this report.

In conclusion, we mentioned in the precedingsection that community-based measures of func-tional diversity/redundancy raise the question ofhow much of each (redundancy and diversity)might or should be expected. Norms of this kind willonly emerge from comparisons of many sites acrossa wide range of environmental and managementconditions. Questions such as how many and whatkinds of attributes are needed, how ‘‘full’’ the at-tribute space is or should be, and overall patterns inthe tables of species by attributes, can (for example)be addressed through the techniques of ordinationand will be worth pursuing in further developmentof this approach, within and between sites. The nextstep is to assemble a set of comparative datasetsfrom different ecosystem types.

ACKNOWLEDGMENTS

We thank NASA and NERC UK for supporting ourparticipation in the workshop that gave rise to thisreport (Biodiversity and Ecosystem Processes: Theory andModelling, cosponsored by Diversitas, GCTE, NASA,& TERI, Imperial College, Silwood Park, UnitedKingdom, in June 1997), and Prof. H. H. Shugartand the Department of Environmental Sciences atthe University of Virginia, who hosted Brian Walkerfor the period during which the first draft of thisreport was written. We are indebted to Jill Land-sberg and Craig James for use of data from their

rangeland study. We also thank Tom Smith andSteve Pacala for useful discussion on the topic offunctional attributes, Mike Austin for comments onthe measurement of ecological distance, and C. S.Holling and an anonymous referee for valuablesuggestions.

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