Forum ORIGINAL ARTICLE OA 000 EN. Does biodiversity determine ecosystem function? The Ecotron experiment reconsidered

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1 Functional Ecology 1998 Ecological Society ORIGINAL ARTICLE OA 000 EN Does biodiversity determine ecosystem function? The Ecotron experiment reconsidered The recent experiment by Naeem et al. (1994, 1995, 1996) has been extremely influential in the current debate concerning the relationship between biodiversity and ecosystem function. This study used a system of controlled-environment chambers (the Ecotron) to examine the response of five ecosystem properties to manipulation of the species richness of an experimental annual plant community. The intention was apparently to vary only species richness ( The only experimentally manipulated factor was the number of plant and animal species [our italics], Naeem et al. 1995), although the authors acknowledged that other variables (e.g. architectural complexity) are almost inevitable correlates of such variation. In any case, others have generally assumed that the results are attributable only to variation in species richness; for example in a recent review Johnson et al. (1996) noted merely that primary productivity [in the Ecotron] increased with plant species diversity. In view of the importance of their conclusions, it is surprising that until recently few attempts to evaluate critically the work of Naeem et al. (1995) have been published (but see André, Bréchignac & Thibault 1994). The most comprehensive critique of Naeem et al. (1995), and of other biodiversity-manipulation experiments, has recently been published by Huston (1997) who makes three major criticisms, of which two apply to the Ecotron: (1) selection of species confounds diversity of species with diversity of functional types and (2) increased probability of including one or more dominant species in larger groups of randomly selected species (see also Lamont 1995). In this paper, we (1) examine the first criticism in more detail and (2) question the levels of diversity employed by Naeem et al. (1995). In both cases, we use existing published surveys and data sets (chiefly Grime, Hodgson & Hunt 1988) augmented by unpublished survey data and additional simple autecological measurements. We then go on to consider briefly what the relationship between biodiversity and ecosystem function might be and how it might best be investigated. Correlations between species richness and the diversity of plant functional types within the Ecotron mesocosms Because no two species are functionally identical, the aim of manipulating only species richness in the Ecotron experiment must have been violated to some extent. We analyse the functional traits of the Ecotron species, in the context of variation within the UK annual flora, to see how far this may have influenced the outcome. The relative success of coexisting species depends on many functional attributes; one of the most important (and easiest to measure) is size. Large seeds may confer advantages during seedling establishment and in annual communities these advantages often persist throughout the life cycle (e.g. Black 1958; Stanton 1984). Equally, the possession of a tall and/or laterally extensive canopy may facilitate the monopolistic use of above-ground resources (Grime 1979; Gaudet & Keddy 1988). We estimated for the Ecotron species four measures of size; canopy height and seed mass [both abstracted from Grime et al. (1988)], canopy diameter (assessed in the field) and maximum individual leaf area (for well-grown plants collected from unshaded field sites, measured using a Delta T Mk 2 area meter). We constructed a simple index of plant size by adding the class score for canopy height to that for canopy diameter. The raw data, which correspond closely to those already presented in Lawton et al. (1993), are summarized in Table 1. The size variables measured were highly correlated (Table 2). For a large unpublished database for annual plants, all attributes were significantly correlated with each other. Even within the small subset of 16 species used in the Ecotron experiment, five of the eight valid correlations were statistically significant or nearly so. All individual size variables are also positively correlated (significantly or nearly so) with the biomass of individual Ecotron species grown in monoculture (see Fig. 1 of Naeem et al. 1996), while the index of plant size explains much of the variation in biomass (Fig. 1). These results provide compelling evidence that, because of correspondence between size-related attributes, small annual species are functionally different from large ones (see also Bogaard et al. 1998). It is therefore unfortunate that in the Ecotron experiment described in Naeem et al. (1994, 1995, 1996), increased species richness was also associated with an increased diversity of size-related attributes (Fig. 2). The most diverse Ecotron community contained not only larger species than the least diverse, as pointed out by Huston (1997), but a wider range at both ends of the size spectrum. This is both an inevitable and foreseeable consequence of the experimental design. The most species-poor community in the Ecotron, containing only two species, could not contain more than two from the possible range of functional types and was therefore inevitably deficient within parts of the functional spectrum. By contrast the most speciesrich community, with 16 species, contained a wider range of functional attributes (Fig. 2). Thus a hidden treatment, sensu Huston (1997), prevents us from dis- 843

2 844 Table 1. The simple autecological data set utilized to interpret the Ecotron biodiversity experiments. Canopy height class (from Grime et al. 1988): 1, 100; 2, ; 3, ; 4, ; 5, 1000 mm. Canopy diameter class: 1, 50; 2, ; 3, ; 4, ; 5, 1000 mm. Index of plant size = canopy height class + canopy diameter class. Maximum leaf area was determined from field material and typically values represent the means from three geographically distant populations. Seed mass data abstracted from Grime et al. (1988). *Species excluded from Grime et al. (1988); data from unpublished UCPE sources Canopy height Canopy diameter Index of Log 10 max. leaf Log 10 seed Species name class class plant size area (mm 2 ) mass (mg) Aphanes arvensis Arabidopsis thaliana Capsella bursa-pastoris Cardamine hirsuta Chenopodium album Conyza canadensis* Lamium purpureum Poa annua Senecio vulgaris Sinapis arvensis Sonchus oleraceus Spergula arvensis Stellaria media Tripleurospermum inodorum Veronica arvensis Veronica persica tinguishing between changes in ecosystem function associated with altered biodiversity and those resulting from modifying the number of functional types present. Because the low-diversity Ecotron communities were so species-poor, some restriction of the range of functional types in these communities was inevitable. The problem could, however, have been partly overcome by careful choice of species and, in particular, by restricting the functional diversity of the most species-rich community. Unfortunately this was not carried out; in terms of the five size variables, the heterogeneity of the 16 Ecotron species is great (Fig. 2). If we compare the range of the sizerelated traits (from Table 1) in the Ecotron species with the range of the same traits in an unpublished database for 157 species (representing 83% of the native and naturalized annuals in the Sheffield region), the 16 Ecotron species represent between 63% (log 10 seed mass) and 100% (canopy height class) of the potential variation. Level of biodiversity in the Ecotron experiment In discussing the results of Naeem et al. (1995), much depends on how we interpret their Fig. 1 (our Fig. 3). Two questions in particular are crucial. First, what are we to understand, in absolute terms, by the dimensions of the species richness axis? Second, what proportion of this axis is occupied by the portion near the origin in which all hypotheses, except the null hypothesis, predict that ecosystem function declines monotonically with declining species richness? In principle, the answer to the first question is straightforward; it is the current level of species richness, not necessarily the maximum species richness possible in a community (Naeem et al. 1995). Because determining the maximum possible species richness is probably impossible anyway, we looked at survey data for the plant communities in which the Ecotron species grow. The 16 species rarely if ever cooccur, but the closest approach to a community which often contains many of them is the fallow arable com- Table 2. Correlations in annual plants between variables relating to plant size: *n = 147 Index of plant size Canopy diameter Canopy height Maximum leaf size Species from Ecotron experiment (n = 16) Canopy height r s = 0 24; NS Maximum leaf size r s = 0 64; P < 0 01 r s = 0 51; P < 0 05 r s = 0 50; P < 0 05 Seed mass r s = 0 50; [P < 0 1] r s = 0 67; P < 0 01 r s = 0 24; NS r s = 0 24; NS All species from annual database (n = 157) Canopy height r s = 0 49; P < Maximum leaf size r s = 0 71; P < r s = 0 56; P < r s = 0 65; P < Seed mass* r s = 0 56; P < r s = 0 44; P < r s = 0 52; P < r s = 0 38; P < 0 001

3 845 munity, i.e. the arable weed community when temporarily freed from the constraints imposed by cultivation and herbicides. Data for this community from extensive Unit of Comparative Plant Ecology (UCPE) surveys (Grime et al and unpublished data) show that species richness in this community varies Fig. 1. A comparison of species-specific plant productivities measured in a glasshouse (from Fig. 1 of Naeem et al. (1996)) and index of plant size. In Naeem et al. (1996), Sonchus oleraceus clearly achieved only a fraction of its potential biomass. Data for Sonchus (x) are omitted from the correlation. from three to 34 spp. m 2, with a mean of 15 5 ± 6 1 (SD). An alternative approach is to consider the richness of all quadrats containing any of the Ecotron species; the mean of these data is very similar but the range is wider (minimum two spp. m 2, maximum 45, mean 15 0 ± 6 4). The maximum current level of species richness is therefore somewhere between 34 and 45 spp. m 2, still quite a wide range. Maybe 45 is too high, but we suggest that 34 is too low, for two reasons. First, UCPE survey data were not collected with high diversity in mind and it would be remarkable if more diverse fallow arable communities did not exist. Second, a substantial fraction of the potential arable weed flora is already extinct in central England (Hodgson 1986). We therefore suggest that a reasonable scale for the richness axis of Fig. 3 would be from zero to 40 spp. m 2. In seeking to answer the second question, we are on much less firm ground. A simple answer would be nobody knows. We have therefore adopted the scaling employed in Naeem et al. (1995), in which the rising portion of the redundant hypothesis occupies slightly more than one third of the richness axis, in other words up to about 14 spp. m 2. We are now in a position to locate the Ecotron communities (two, five and 16 species m 2 ) on the graph of Naeem et al. (1995). Clearly, the Ecotron experiment examined the relationship between ecosystem function and species richness over somewhere between one third and one half of the range of the lat- Fig. 2. (1) Range of functional attributes associated with Ecotron mesocosm communities. (2) Range of functional attributes in an unpublished UCPE database of 157 annual species, scaled to same species richness as Ecotron communities.

4 846 Fig. 3. Relationships between species richness and level of expression of ecosystem function according to the null, idiosyncratic, redundant and rivet hypotheses. The vertical bars represent the location of the Ecotron communities and do not imply anything about the level of ecosystem function in those communities. Redrawn from Naeem et al. (1995). See text for discussion of axis scaling. ter variable which is observed in real communities of annual plants (Fig. 3). This is particularly unfortunate, because over this range the three main competing hypotheses make qualitatively identical predictions. Only the unrealistic null hypothesis, which assumes no connection between diversity and ecosystem function at any level of diversity, is capable of being falsified by the Ecotron experiment. Discussion PROBLEMS WITH THE ECOTRON EXPERIMENT We restricted our functional analysis to a small number of simple, size-related attributes (Table 1). In reality, the composition and function of plant communities will vary along other important axes. In the case of annual communities, these other axes will include, inter alia, germination timing, seed dispersal and seed persistence in the soil. However, the species concerned were selected specifically because they require no special germination conditions and reproduce continuously in the absence of seasonality (Naeem et al. 1995). We therefore felt that our limited and rather static analysis, which essentially ignores processes operating across generations, was appropriate in the circumstances. However, we suspect that our conclusions would not have been much altered if we had analysed the regenerative attributes of the Ecotron species. To take only one example, the most diverse community clearly shows a much greater variety of field emergence timing than the least diverse (Roberts 1964). In the experiment of Naeem et al. (1995), species richness varied in parallel with variation in diversity of functional types, making it impossible to isolate the effect of either. This is a difficult problem to avoid without massive replication of diversity treatments but much of the difficulty could have been avoided by some relatively slight changes to the experimental design. The range of functional types in the most diverse treatment could have been reduced and/or the range of types in the least diverse treatment could have been expanded. Including more species in the low-diversity treatment would have made this task much simpler, because the emphasis on moderate- to very low-diversity systems made functional poverty an almost insoluble problem. Naeem et al. (1995) apparently set out to examine the effect of extreme impoverishment on a system of only average diversity. Even taking the results at face value, the experiment did not (and could not) contribute to the debate about the possible beneficial effects of high diversity. A WAY FORWARD? We have so far chosen to join the debate on the role of diversity in ecosystem function on the terms set by Naeem et al. (1995). It could be argued that the debate could, and should, be widened to include other matters. For example, it is not clear that the underlying principles can be satisfactorily addressed by a community of arable weeds. Many of the more subtle interactions which may be found in communities of slower-growing perennials, for instance those involving mycorrhizas (Grime et al. 1987), are likely to be poorly developed or absent in a community of fastgrowing ephemerals. It may also be that the consequences of declining biodiversity are apparent only at spatial and temporal scales which cannot easily be reproduced in controlled environments. We therefore conclude with one suggestion of how diversity may contribute to the functioning of species-rich ecosystems. Species-rich plant communities do not have a high biomass (Al-Mufti et al. 1977; Huston & Smith 1987) and lack an aggressive dominant. Nevertheless we would expect speciesrich plant communities to exhibit a dominance hierarchy, in which a species potential place in the community is largely determined by its size (see Mitchley & Grubb 1986). In practice, the hierarchy may be poorly defined because the success of some potential dominants has been reduced by narrow niche width. Accordingly, we would normally expect the actual dominant (in the sense of the species with the highest biomass) to be a potential dominant of wide ecological amplitude. In the tail of the size distribution, we expect to find species of small stature which, although typical components of the community and often relatively abundant, never attain high biomass. In addition to this relatively fixed hierarchy, there may be a much more ecologically heterogeneous group of other scarce species. Some may be relics of a previous vegetation type. Others may persist through tolerance of infrequent extreme events (Buckland et al. 1997). Still others may be tempo-

5 847 rary migrants; seed dispersal and early establishment are to some extent chance events. Crucially, this group may include juvenile or suppressed individuals of potential dominants; grassland, for example, may contain tree and shrub seedlings. Thus we predict three broad functional groupings (Fig. 4): (1) the dominant, together with a few other species of relatively high biomass, (2) the tail of the dominance hierarchy, which in a species-rich community may contain many species but little biomass, and (3) other scarce species, whose number and identity will often vary even between different examples of the same community. The first group will control the main ecosystem functions, such as productivity, decomposition and nutrient uptake and storage, while the second will normally have very little impact on these functions. The third group, however, may have more subtle impacts; for example, they may provide a pool of additional species that could increase in the event of habitat change (see Grime (1998) for a fuller discussion of the roles played in ecosystem function by different functional species groups). These three groups of species can be recognized in diverse examples of species-rich calcareous grassland in the UK (Fig. 5), re-emphasizing that species have different functional attributes and do not play totally interchangeable roles in the ecosystem. Investigation of the role of diversity in ecosystem function must take account of this functional diversity but whether this is possible in short-term experiments in controlled environments remains to be seen (Wardle et al., 1997). Acknowledgements This work was supported by the Natural Environment Research Council. Phil Grime and Michael Huston made valuable comments on the manuscript. Fig. 4. A suggested classification of species in terms of potential dominance and achieved biomass within species-rich vegetation. References Al-Mufti, M.M., Sydes, C.L., Furness, S.B., Grime, J.P. & Band, S.R. (1977) A quantitative analysis of shoot phenology and dominance in herbaceous vegetation. Journal of Ecology 65, André, M., Bréchignac, F. & Thibault, P. (1994) Biodiversity in model ecosystems. Nature 371, 565. Black, J.N. (1958) Competition between plants of different initial seed sizes in swards of subterranean clover (Trifolium subterraneum L.) with particular reference to Fig. 5. Relationships between potential dominance and abundance in species-rich calcareous grasslands from (a) Cressbrook Dale, Derbyshire, 43 species m 2 (UCPE database), (b) Pulpit Hill, Buckinghamshire, 29 species 4 m 2 (Table 2, Locality 8, Pigott 1968) and (c) Knocking Hoe, Bedfordshire, 32 species m 2 (Table 2, Site 2c, Wells 1976). An attempt was made to classify species according to the scheme presented in Fig. 4 and the three groupings recognized are arbitrarily separated by broken lines. The estimate of potential dominance uses the m 2 quadrats in the UCPE field survey database and is an empirical measure of the ability of high densities of a species to exclude other species. As rooted frequency of the species increases so too does its percentage contribution to the total rooted frequency of the quadrat. Potential dominance is the gradient of this linear relationship, which is high for potential dominants (e.g. Fallopia japonica, 11 3) and low for species which are never dominant (e.g. Carex caryophyllea, 1 2). A small number of species were not in the UCPE database and were excluded from the analysis: (b) three subordinates; (c) three subordinates, one other major species. Annuals/biennials (extremely low potential dominance) and shrubs/trees (extremely high potential dominance) are outside the scope of the analysis and were also excluded: (a) one annual/biennial, two shrubs/trees; (b) 2 a/b, 1 s/t; (c) 1 a/b, 1 s/t.

6 848 leaf area and the light microclimate. Australian Journal of Agricultural Research 9, Bogaard, A., Hodgson, J.G., Wilson, P.J. & Band, S.R. (1998) An index of weed size for assessing the productivity of ancient crop fields. Vegetation History and Archaeobotany 7, Buckland, S.M., Grime, J.P., Thompson, K. & Hodgson, J.G. (1997) A comparison of plant responses to the extreme drought of 1995 in Northern England. Journal of Ecology 85, Gaudet, C.L. & Keddy, P.A. (1988) A comparative approach to predicting competitive ability from plant traits. Nature 334, Grime, J.P. (1979) Plant Strategies and Vegetation Processes. John Wiley, Chichester. Grime, J.P. (1998) Benefits of plant diversity to ecosystems: immediate, filter and founder effects. Journal of Ecology 86, in press. Grime, J.P., Mackey, J.M.L., Hillier, S.H. & Read, D.J. (1987) Floristic diversity in a model system using experimental microcosms. Nature 328, Grime, J.P., Hodgson, J.G. & Hunt, R. (1988) Comparative Plant Ecology: a Functional Approach to Common British Species. Unwin Hyman, London. Hodgson, J.G. (1986) Commonness and rarity in plants with special reference to Sheffield Flora. Part 1. The identity, distribution and habitat characteristics of the common and rare species. Biological Conservation 36, Huston, M.A. (1997) Hidden treatments in ecological experiments: re-evaluating the ecosystem function of biodiversity. Oecologia 110, Huston, M.A. & Smith, T.M. (1987) Plant succession: life history and competition. American Naturalist 130, Johnson, K.H., Vogt, K.A., Clark, H.J., Schmitz, O.J. & Vogt, D. (1996) Biodiversity and the productivity and stability of ecosystems. Trends in Ecology and Evolution 11, Lamont, B. (1995) Testing the effect of ecosystem composition/structure on its functioning. Oikos 74, Lawton, J.H., Naeem, S., Woodfin, R.M., Brown, V.K., Gange, A., Godfray, H.C.J., Heads, P.A., Lawler, S., Magda, D., Thomas, C.D., Thompson, L.J. & Young, S. (1993) The Ecotron: a controlled environment facility for the investigation of population and ecological processes. Philosophical Transactions of Royal Society of London B 341, Mitchley, J. & Grubb, P.J. (1986) Control of relative abundance of perennials in chalk grassland in southern England. I. Constancy of rank order and results of potand field-experiments on the role of interference. Journal of Ecology 74, Naeem, S., Thompson, L.J., Lawler, S.P., Lawton, J.H. & Woodfin, R.M. (1994) Declining biodiversity can alter the performance of ecosystems. Nature 368, Naeem, S., Thompson, L.J., Lawler, S.P., Lawton, J.H. & Woodfin, R.M. (1995) Empirical evidence that declining species diversity may alter the performance of terrestrial ecosystems. Philosophical Transactions of Royal Society of London B 347, Naeem, S., Håkansson, K., Lawton, J.H., Crawley, M.J. & Thompson, L.J. (1996) Biodiversity and plant productivity in a model assemblage of plant species. Oikos 76, Pigott, C.D. (1968) Biological flora of the British Isles Cirsium acaulon (L.) Scop. Journal of Ecology 56, Roberts, H.A. (1964) Emergence and longevity in cultivated soil of seeds of some annual weeds. Weed Research 4, Stanton, M.L. (1984) Seed variation in wild radish: effects of seed size on components of seedling and adult fitness. Ecology 65, Wardle, D.A., Zackrisson, O., Hörnberg, G. & Gallet, C. (1997) Biodiversity and ecosystem properties: response. Science 278, Wells, T.C.E. (1976) Biological flora of the British Isles Hypochoeris maculata L. Journal of Ecology 64, J. G. HODGSON, K. THOMPSON and P. J. WILSON Unit of Comparative Plant Ecology, Department of Animal and Plant Sciences, The University, Sheffield S10 2TN, UK A. BOGAARD Department of Archaeology and Prehistory, The University, Sheffield S1 4ET, UK Biodiversity and ecosystem function: getting the Ecotron experiment in its correct context Hodgson et al. (1998) offer a number of criticisms of experiments in the Ecotron and associated greenhouse work (Naeem et al. 1994, 1995, 1996), exploring the relationship between species richness of experimental microcosms, and ecosystem processes. We have no argument with most of the detail in Hodgson et al. s paper but note that it both fails to consider a number of fundamental issues and misunderstands the nature of the problem. We agree with Hodgson et al. (1998) that the design of the original experiment would have benefited from the insights we now have on these complex problems. Indeed, it would be remarkable if a pioneering experiment first published 4 years ago and conceived 6 years ago proved to be correct in every detail. Science does not work like that. The basic purpose of pioneering experiments is to open up new fields for detailed scrutiny. We would argue that the Ecotron experiment in Naeem et al. (1994) has done exactly that. We are not happy with some of the more exaggerated claims made by others for this experiment but are pleased that the debate, which Hodgson et al. (1998) have now joined, is happening. In this note we deal with some of the fundamental issues raised by Hodgson et al. (1998) but which we believe they either misunderstand, or fail to consider, and we take the opportunity to correct some factual errors in their paper. We also draw attention to a point that appears to be causing increasing confusion in the literature, namely the crucial difference between the impacts of changes in biodiversity on ecosystem processes within an ecosystem (intra-system effects, as in the Ecotron experiment, which sought to mimic species losses within a community) and comparisons between different ecosystems (inter-system effects) where large environmental differences between habitats and communities may totally abscure species-

7 849 richness effects on ecosystem processes. The majority of this note is concerned with intra-system effects. We return to inter-system effects at the end. There cannot be a relationship between biodiversity and ecosystem processes unless species differ in their attributes Hodgson et al. (1998) are concerned that the Ecotron experiment was not a pure manipulation of species richness. They are correct. It is impossible to manipulate species richness without also selecting species with different characteristics (growth rates, size, germination time, etc.) for the simple reason that no two species are identical. What they, and others (e.g. Huston 1997), apparently fail to see is that there cannot be any relationship between species richness and ecosystem processes without these differences between species. Or, to rephrase this key point, we know of no theoretical mechanisms whereby a set of identical species could produce a relationship between species richness and ecosystem processes. The way in which inevitable differences between species translate into diversity function relationships can be both subtle and complex. Here we wish simply to point out one obvious key process. Nichedifferences between species ensure that as species richness increases in ecological assemblages, so does the range of functional space occupied by the assemblage (Tilman, Lehman & Thomson 1997). More diverse plant communities are more spacefilling above ground (Naeem et al. 1994, 1995), have a greater variety of rooting depths (Hooper & Vitousek 1997, 1998; Hooper 1998), a wider range of requirements for below-ground resources and so on. Within any one habitat, and other things being equal (and they are not always equal), on average it is therefore almost inevitable that more species rich assemblages have greater productivity (Vandermeer 1988; Swift & Anderson 1993; Tilman, Wedin & Knops 1996; Tilman, Knops et al. 1997), retain soil nutrients more efficiently (Tilman et al. 1996; Tilman, Knops et al. 1997) and are more robust to extreme events (Tilman & Downing 1994; see also Naeem & Li 1997), because more species-rich assemblages are able to exploit a wider range and variety of resources. In fact, we now know that there are at least two ways in which positive diversity process relationships can occur in studies like the Ecotron biodiversity experiment. Both require species to differ in their biology (i.e. to show niche-differences) but make subtly different assumptions. The simplest mechanism is the sampling hypothesis, which says that there is a greater probability of selecting a highly productive species in more diverse communities (Tilman, Lehman & Thompson 1997). The second mechanism will happen even if all species are identified in their productive potential but show niche-differences and complementarity in resource capture, as discussed above and in the original Ecotron paper. In either case, the correct statistical null hypothesis is that there is no relationship between biodiversity and ecosystem processes. We would only expect to support this null hypothesis if all species behaved identically with respect to the process in question. Several important issues remain unresolved. For example, where we observe increases in ecosystem function with increasing species richness, is there any more to the phenomenon than passive sampling from a species pool? Is it possible to distinguish between the sampling hypothesis and pure niche complementarity? How do we predict the effects of niche-differences between species? Is there any evidence for synergistic interactions between species, leading to overyielding (Vandermeer 1988; Swift & Anderson 1993)? Where does the species-richness effect plateau out? For plant assemblages observed under benign environmental conditions, the effects of species richness on ecosystem processes appear to asymptote at less than 20 species (Tilman et al. 1996; Tilman, Knops et al. 1997). Theory suggests, however, that substantially more species, covering a wide range of niche-space (in Hodgson et al. s (1998) terms, a variety of functional groups), may be required to maintain ecosystem processes in the face of a variety of different extreme environmental perturbations (A. Hector & BIODEPTH consortium, unpublished). One final point is in order in this section. The current debate about the relative importance of plant species richness vs plant functional types, or plant species identity, in determining ecosystem processes (Grime 1997; Hooper & Vitousek 1997; Tilman, Knops et al. 1997; Wardle et al. 1997a,b; Hodgson et al. 1998) misses the point. Because no two plant species within a functional type (however this is defined) have identical niches, species richness will influence ecosystem processes, by the arguments laid out above, although if the differences between plant species are small, then the effects will be small. By these same arguments, deliberately selecting species to be as different as possible, by selecting different functional types, is bound to have an even bigger effect on ecosystem processes. And because functional types are arbitrary divisions of continuous niche-space, deciding whether species richness or functional types has a bigger impact on ecosystem processes is to arbitrarily divide a continuum; the bigger the niche-differences between species in the experimental assemblage, the bigger the effect we expect to observe on ecosystem processes. Last, but by no means least, if only a few species are involved, and/or if there are major changes in dominants with diversity, the effects of individual species identities (the idiosyncratic hypothesis) will be paramount. These ideas, particularly that species identities mat-

8 850 ter, are discussed in Lawton (1994, 1996b) and Naeem et al. (1996) but are unfortunately ignored by Hodgson et al. (1998). Distinguishing between hypotheses Hodgson et al. (1998) reproduce (in their Fig. 3) the simple model presented by Naeem et al. (1995) showing possible theoretical relationships between species richness and ecosystem processes, including the statistical null hypothesis of no relationship. We are pleased to see that they find this simple model [described by Naeem et al. (1995) as primarily heuristic to facilitate... discourse ] useful [see also Johnson et al. (1996) and Martinez (1996)]. The reader should, however, note an important difference between Fig. 3 of Hodgson et al. (1998) and Fig. 1 of Naeem et al. (1995). The original version (Naeem et al. 1995) has no scale on the x-axis, whilst Hodgson et al. (1998) somehow manage to add a quantitative scale that positions the Ecotron experiment precisely on Fig. 1 of Naeem et al. (1995). We see no logical justification for this procedure and, even if one existed, the exact shapes of the curves in the original figure are arbitrary; equally arbitrary, but different curves would give a different answer to the one claimed by Hodgson et al. (1998). In other words, and regretfully, we have to say that Fig. 3 in Hodgson et al. (1998) is meaningless. Contrary to their more general claim (and faulty reporting of the Ecotron data), it is also possible to distinguish between these hypotheses. In the original Ecotron experiment, only primary production (aboveground biomass) increased with species richness (consistent with the rivet hypothesis over the range of species richness examined; this effect could have been driven by either of the two mechanisms discussed earlier). Other ecosystem processes were not consistent with the rivet hypothesis but appeared either to conform to the statistical null hypothesis (no effect of richness on the process) or to the idiosyncratic hypothesis (there were significant differences between treatments but not simply related to species richness). We can now intrepret the Ecotron data in a way that we were unable to 4 years ago. Taking the basic theory outlined above, we expect to see results consistent with the statistical null hypothesis when niche-differences between plant species have a trivially small influence on the process in question; essentially, all species behave identically with respect to a particular process. And we expect to observe data consistent with the idiosyncratic hypothesis when species differ markedly in the niche-attributes impacting on the process (i.e. they have very different functional characteristics for the attributes in question) and the experimental gradient of species richness is not a large, well replicated set of random draws from the species pool (Naeem et al. 1996; Tilman, Lehman & Thompson 1997). The Ecotron experiment used one nested set of species and replicate diversity treatments used the same species combinations (rather than creating genuine replicates using different species combinations at each level of diversity; see also Huston 1997). With the benefit of hindsight, these are exactly the conditions in which we would expect idiosyncratic species effects to dominate. Only biomass production increased systematically with species richness (and as Hodgson et al. (1998) point out, with increasing functional diversity). Worries about weeds Hodgson et al. (1998) ask whether the underlying principles [of the relationship between species richness and ecosystem processes] can be satisfactorily addressed by a community of arable weeds? We know of no fundamental reasons why they cannot. Different species of weeds show pronounced nichedifferences and hence ought to be suitable experimental organisms. Vague criticisms of this kind are much more constructively expressed as questions or, better still, as hypotheses (Lawton 1996a). If weeds are poor model organisms, or if there are concerns about mycorrhizas or the spatial scale of the experimental system [both of which Hodgson et al. (1998) are also concerned about], we should pose these concerns in terms of a specific mechanism or mechanisms: an absence of mycorrhizas will change the relationship between species richness and ecosystem processes because.... Vague worries do nothing to sharpen the science. Additionally, just for the record, Ecotron plants do have mycorrhizas. The way forward Flattered as we are by the repeated attention which the Ecotron experiment receives [Naeem et al. (1994) was the fifth most cited paper in environmental research in 1996 (MPD 1996)], we believe that progress will be faster in this field if we look forwards rather than backwards. Relationships between species richness and the variety of plant functional types and ecosystem processes have now been demonstrated experimentally by a number of independent researchers (Tilman, Wedin & Knops 1996; Hooper & Vitousek 1997; Tilman, Knops et al. 1997; for related, pioneering work with organisms other than higher plants see McGrady-Steed, Harris & Morin 1997). The need now is to better understand the underpinning mechanisms and to explore situations and ecosystem processes where we might not expect to find support for a simple decline in ecosystem processes with declining species richness. We entirely agree with Hodgson et al. (1998) that as part of these explorations it will be important to consider the role of dominant vs scarce species, particularly the role of normally scarce or

9 851 suppressed species in maintaining ecosystem processes in the face of extreme events. However, we take issue with the experimental design suggested by these authors. Hodgson et al. (1998) suggest that it would have been better if in the Ecotron experiment (and presumably other experiments?) the range of functional types in the most diverse treatment could have been reduced and/or the range of types in the least diverse treatments could have been expanded. This is a fundamentally poor experimental design. Good experimental design involves manipulating only one factor at a time; by manipulating both aspects of diversity simultaneously it will be impossible to interpret their relative importance. To overcome these and other problems (betweenand within-site effects, for example, see below) we have recently established a European-wide experiment known as BIODEPTH (BIODiversity and Ecological Processes in Terrestrial Herbaceous ecosystems) (A. Hector & BIODEPTH consortium, unpublished). BIODEPTH is conducting the same biodiversity ecosystem function experiment at eight European field sites. Five levels of species richness have been experimentally established at each site, ranging from monocultures to the average maximum found in neighbouring undisturbed plots. To compare the effects of species richness (and hence potentially small niche-differences between species) with differences in plant functional diversity (potentially larger niche-differences) we have also manipulated community composition in terms of three simple plant functional groups: legumes, non-nitrogen fixing forbs and grasses. These two factors cannot be fully crossed (obviously there cannot be more functional groups than species) but diversity varies widely (contrary to the views expressed by Hodgson et al. (1998) massive replication of diversity treatments is not a problem). For example, at Silwood Park there are plots containing only grasses that vary in richness from one to 11 species. In plots with more than three species, functional diversity varies from grasses only, to grasses and legumes, grasses and non-nitrogen fixing forbs, to all three functional groups. To separate the effects of diversity from the effects of the identity of particular species or combinations of species, each replicate community utilizes a different randomly selected set of species chosen from the pool of suitable local species at each site. Initial results from BIODEPTH support some positive diversity productivity relationships but suggest that a single model of the relationship between biodiversity and ecosystem functioning may be inadequate to describe the patterns across the range of European grasslands. In brief, with both hindsight and the rapid growth in knowledge that followed the initial Ecotron experiment, it is now relatively easy to design quite powerful experiments to address relationships between biodiversity and ecosystem function, both within one site, and across localities. Confusion about within habitat and between habitat effects of biodiversity on ecosystem processes We have one final comment. It is easy to criticise manipulative experiments that seek to change species richness and measure ecosystem processes either in controlled environment facilities (Naeem et al. 1994, 1995, 1996; McGrady-Steed et al. 1997; Naeem and Li 1997) or in the field (Tilman et al. 1996; Hooper & Vitousek 1997; Tilman, Knops et al. 1997; A. Hector & BIODEPTH consortium, unpublished), because such experiments are always, to a greater or lesser degree, artificial. The temptation is therefore to resort to correlative field studies on natural vegetation (Wardle et al. 1997a,b). Such a criticism, and suggested means of dealing with it, seem to be implicit (if not explicit) in Hodgson et al. s A Way Forward (Hodgson et al. 1998). We warn that in this particular field, purely correlative studies can be extremely misleading (Tilman, Naeem et al. 1997). Simple models (Loreau 1998) and empirical data (McNaughton 1993; Bulla 1996) show that unless conditions are extremely similar, across-habitat or across-locality comparisons of the relationship between species richness and ecosystem processes are unlikely to be illuminating because between-site differences totally obscure within-habitat effects of species richness on ecosystem processes. For example, the fact that several ecosystem processes increased as species richness declined across a set of island habitats (Wardle et al. 1997a) is entirely due to large associated changes in environmental characteristics across these islands and hence in the types of plants growing there. Such observations tell us nothing about how ecosystem processes respond to changes in species richness within a habitat. It is certainly important to know the relative magnitude of within-habitat species-richness effects, and across-habitat environmental effects on ecosystem processes, but it is not helpful to confuse the two (Grime 1997; Wardle et al. 1997b). References Bulla, L. (1996) Relationship between biotic diversity and primary productivity in savanna grasslands. Biodiversity and Savanna Ecosystem Processes (eds O. T. Solbrig, E. Medina & J. F. Silva), pp Springer-Verlag, Berlin. Grime, J.P. (1997) Biodiversity and ecosystem function: the debate deepens. Science 277, Hodgson, J.G., Thompson, K., Bogaard, A. & Wilson, P.J. (1998) Does biodiversity determine ecosystem function? The Ecotron experiment reconsidered. Functional Ecology 12, Hooper, D.U. (1998) The role of complementarity and competition in ecosystem response to variation in plant diversity. Ecology 79, Hooper, D.U. & Vitousek, P.M. (1997) The effects of plant composition and diversity on ecosystem processes. Science 277,

10 852 Hooper, D.U. & Vitousek, P.M. (1998) Effects of plant composition and diversity on nutrient cycling. Ecological Monographs 68, Huston, M.A. (1997) Hidden treatments in ecological experiments: re-evaluating the ecosystem function of biodiversity. Oecologia 110, Johnson, K.H., Vogt, K.A., Clark, H.J., Schmitz, O.J. & Vogt, D.J. (1996) Biodiversity and the productivity and stability of ecosystems. Trends in Ecology and Evolution 11, Lawton, J.H. (1994) What do species do in ecosystems? Oikos 71, Lawton, J.H. (1996a) The Ecotron facility at Silwood Park: the value of big bottle experiments. Ecology 77, Lawton J.H. (1996b) The role of species in ecosystems: aspects of ecological complexity and biological diversity. Biodiversity. An Ecological Perspective (eds T. Abe, S. A. Lein & M. Higashi), pp Springer, New York. Loreau, M. (1998) Biodiversity and ecosystem functioning: a mechanistic model. Proceedings of the National Academy of Sciences 95, McGrady-Steed, J., Harris, P.M. & Morin, P.J. (1997) Biodiversity regulates ecosystem predictability. Nature 390, McNaughton, S.J. (1993) Biodiversity and function of grazing ecosystems. Biodiversity and Ecosystem Function (eds E.-D. Schulze & H. A. Mooney), pp Springer-Verlag, Berlin. MPD (1996) Biodiversity and climate change dominate environmental research. The Scientist 10, 14. Naeem, S. & Li, S. (1997) Biodiversity enhances ecosystem reliability. Nature 390, Naeem, S., Thompson, L.J., Lawler, S.P., Lawton, J.H. & Woodfin, R.M. (1994) Declining biodiversity can alter the performance of ecosystems. Nature 368, Naeem, S., Thompson, L.J., Lawler, S.P., Lawton, J.H. & Woodfin, R.M. (1995) Empirical evidence that declining biodiversity may alter the performance of terrestrial ecosystems. Philosophical Transactions of the Royal Society of London B 347, Naeem, S., Håkansson, K., Lawton, J.H., Crawley, M.J. & Thompson, L.J. (1996) Biodiversity and plant productivity in a model assemblage of plant species. Oikos 76, Swift, M.J. & Anderson, J.M. (1993) Biodiversity and ecosystem function in agricultural systems. Biodiversity and Ecosystem Function (eds E.-D. Schulze & H. A. Mooney), pp Springer-Verlag, Berlin. Tilman, D. & Downing, J.A. (1994) Biodiversity and stability in grasslands. Nature 367, Tilman, D., Wedin, D. & Knops, J. (1996) Productivity and sustainability influenced by biodiversity in grassland ecosystems. Nature 379, Tilman, D., Knops, J., Wedin, D., Reich, P., Ritchie, M. & Siemann, E. (1997) The influence of functional diversity and composition on ecosystem processes. Science 277, Tilman, D., Lehman, C.L. & Thompson, K.T. (1997) Plant diversity and ecosystem productivity: theoretical considerations. Proceedings of the National Academy of Sciences 94, Tilman, D., Naeem, S., Knops, J., Reich, P., Siemann, E., Wedin, D., Ritchie, M. & Lawton, J.H. (1997) Biodiversity and ecosystem properties. Science 278, Vandermeer, J. (1989) The Ecology of Intercropping. Cambridge University Press, Cambridge. Wardle, D.A., Zackrisson, O., Hörnberg, G. & Gallet, C. (1997a) The influence of island area on ecosystem properties. Science 277, Wardle, D.A., Zackrisson, O., Hörnberg, G. & Gallet, C. (1997b) Response. Science 278, J.H. LAWTON, S. NAEEM, 1 L.J. THOMPSON, A. HECTOR and M.J. CRAWLEY NERC Centre for Population Biology, Imperial College, Silwood Park, Ascot, SL5 7PY, UK 1 Department of Ecology, Evolution and Behavior, University of Minnesota, 100 Ecology Building, 1987 Upper Burford Circle, St Paul, MN55108, USA Response to Lawton et al. We are pleased to hear from Lawton et al. (1998) that there appears to be an increasing convergence on the view (which we have always held) that functional differences between species are the key to understanding the ecosystem function of biodiversity. However, we were less happy to have our two principal arguments (Hodgson et al. 1998) dismissed as meaningless or poor experimental design. Neither criticism is justified. First, it is disingenuous to suggest that the x-axis of Fig. 1 of Naeem et al. (1995) lacked a scale. The scale was explicitly defined by Naeem et al. as the current level of species richness. We merely took this definition at face value and gave it numerical meaning by reference to very extensive survey data from real weed communities. The exact shapes of the curves in the original figure are of course arbitrary but this does not alter the fact that the original Ecotron experiment examined the effects of biodiversity over the lower one quarter to one third of the range found in real weed communities. Nor is this a trivial point. Maybe Lawton et al. (1998) now know that all the important effects of biodiversity are to be found at less than 20 species (although we note that where does the species-richness effect plateau out? remains an unanswered question) but many of us would like to know if genuinely high diversity has any functional implications. Second, we note that our suggestion that the range of several plant size variables could have been kept constant across the Ecotron diversity treatments is fundamentally poor experimental design. On the contrary, the approach of Naeem et al. (1995) involving simultaneously increasing species number and allowing the range of canopy height and diameter, seed size and leaf size to increase in tandem was fundamentally poor experimental design. Finally, we dispute the artificial distinction Lawton et al. (1998) attempt to draw between within-habitat effects, of which the Ecotron is an extreme example, and between-habitat studies on natural vegetation. It is illusory to suggest that one can create ecosystems,

11 853 even wholly artificial ones, which differ only in species richness. Species differences rapidly translate into differences in rates of litter decomposition (and hence nutrient suppy) and in densities and identities of herbivores, predators and soil micro-organisms. Differences between and within ecosystems are quantitative, not qualitative. Note how convenient it becomes if every failure to find significant effects of biodiversity can be attributed to large associated changes in environmental characteristics. References Hodgson, J.G., Thompson, K., Bogaard, A. & Wilson, P. (1998) Does biodiversity determine ecosystem function? The Ecotron experiment reconsidered. Functional Ecology 12, Lawton, J.H., Naeem, S., Thompson, L.J., Hector, A. & Crawley, M.J. (1998) Biodiversity and ecosystem function: getting the Ecotron experiment in its correct context. Functional Ecology 12, Naeem, S., Thompson, L.J., Lawler, S.P., Lawton, J.H. & Woodfin, R.M. (1995) Empirical evidence that declining biodiversity may alter the performance of terrestrial ecosystems. Philosophical Transactions of the Royal Society of London B 347, K. THOMPSON & J.G. HODGSON Unit of Comparative Plant Ecology, Department of Animal and Plant Sciences, The University, Sheffield S10 2TN, UK On the utility of path modelling for ecological and evolutionary studies In a recent article, Petraitis, Dunham & Niewiarowski (1996) discuss potential limitations regarding the application of some statistical methodologies, in particular path analysis, to ecological and evolutionary problems. Their cautions regarding collinearity, sample size and proper implementation of methods should be seriously studied by those who wish to develop and test multivariate hypotheses of complex ecological systems. At the end of their paper, the authors go on to criticize what they refer to as path analysis with LISREL, or at times simply LISREL, which they contend will have little value for ecological and evolutionary studies. In this paper, we argue that Petraitis et al. (1996) have not adequately represented the utility of what is properly referred to as structural equation modelling (SEM), the statistical methodology implemented by LISREL (as well as a large number of other programs). SEM is a generalized covariance analysis methodology that is used for a wide variety of applications in the analysis of data, including the analysis of path models. Developed in the early 1970s (Keesling 1972; Jöreskog 1973), SEM long ago replaced Wrightian path analysis (e.g. Wright 1918) in the statistical literature, which is one reason that literature on path analysis is so sparce. Some authors refer to SEM as LISREL modelling and traditional path analysis can be performed with LISREL, thereby producing further confusion. Since its initial development in the social sciences and econometrics, SEM is now used in a wide range of additional fields including chemistry, medicine, genetics and biology. Unfortunately, the abandonment of traditional path analysis in favour of the more generalized methodology SEM has not been widely recognized by ecologists and, as a result, the vast literature on how to analyse path models properly has been missed by many, including Petraitis et al. (1996). At present, an extensive literature exists dealing with the theory and application of SEM. More recent books on the subject include Hayduk (1987, 1996), Bollen (1989), Finkel (1995), Hair et al. (1995), Hoyle (1995), Jaccard & Wan (1996), Marcoulides & Schumacker (1996), Mueller (1996) and Schumacker & Lomax (1996). A substantial number of software programs also exist for performing SEM, including LISREL (Jöreskog & Sörbom 1996), CALIS in SAS (Hatcher 1994), EQS (Bentler & Wu 1996) and AMOS (Arbuckle 1995), just to mention four of the more popular ones. Further, a large body of literature exists that shows a wide range of applications of SEM (for a bibliography see Austin & Calderon 1996; also the journal Structural Equation Modeling). In this paper, we discuss a number of the points raised by Petraitis et al. (1996) which we feel require clarification. Their dismissal of path analysis with LISREL belies the potential utility of SEM for ecological and evolutionary studies. Because of the complexity of many of the statistical issues, our approach in this paper is largely one where we support our contentions with published literature, rather than through a complete exposition of the statistical theory (which would require far more space than available here). In their article, Petraitis et al. (1996) present several reasons why they doubt that this procedure (LISREL) will be of much help to evolutionary ecology. With the exception of the requirement of no missing data*, we feel that their criticisms are overstated or have been addressed to the contrary in the SEM literature. 1. The test assumes a large sample. Actually, a large sample size is an inherent requirement for all multivariate procedures. This includes multiple regression, MANOVA, and path analysis. The appropriate sample size for an SEM study depends on a number of factors including the number and types of variables, and normality of the data (Bentler & Dugeon 1996; Yuan & Bentler 1997). In general, SEM allows for the use of smaller samples than other multivariate methods owing to its effective handling of measurement error (Boomsma 1982; Raykov & Widman 1995). One form of SEM, using partial least squares (Lohmöller 1989), can provide stable solutions with quite small sample sizes (Fornell & Cha 1994).