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The nature of the plant community: a reductionist view
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J. Bastow Wilson
Botany Department, University of Otago, Box 56, Dunedin, New Zealand.
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Andrew D.Q. Agnew
Institute of Biological Sciences, University of Wales Aberystwyth, SY23 3DA, U.K.
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Chapter 6: Construction
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Theories .......................................................................................................................................... 1
Clements and the integrated concept.............................................................................................. 3
Gleason ........................................................................................................................................... 6
Whittaker and Austin ..................................................................................................................... 7
Hubbell and chance ........................................................................................................................ 9
Grime’s C-S-R theory .................................................................................................................. 10
6.1 The triangle ...................................................................................................................... 10
6.2 Stress ................................................................................................................................ 11
6.3 Disturbance ...................................................................................................................... 13
6.4 Competition ...................................................................................................................... 14
6.5 Species/character tests ...................................................................................................... 14
6.6 Does succession provide a test of C-S-R? ....................................................................... 16
6.7 Conclusions ...................................................................................................................... 17
Tilman’s theory ............................................................................................................................ 18
7.1 The competitive process: R* ............................................................................................ 18
7.2 Succession ........................................................................................................................ 21
7.3 Conclusion ....................................................................................................................... 23
Grime versus Tilman .................................................................................................................... 23
8.1 Strategy ............................................................................................................................ 23
8.2 Species diversity............................................................................................................... 24
8.3 Competition ...................................................................................................................... 24
Synthesis ...................................................................................................................................... 31
9.1 “Too soon to tell” ............................................................................................................. 31
9.2 “Does vegetation suit our models?” ................................................................................. 31
9.3 The ‘Paradox of the plankton’.......................................................................................... 34
9.4 Heterogeneity ................................................................................................................... 35
9.5 Assembly rules ................................................................................................................. 37
9.6 Conclusions ...................................................................................................................... 40
1 Theories
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We here critically review the available general theories of plant ecological behaviour and
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relate them to our view of plant life. Our aim is to generalise over all plant communities, aquatic as
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well as terrestrial, although we mostly have embryophytes in mind. We start with the distinction
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between models that are:
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Deterministic: Environmental filters and the constraints of plant interactions wholly and
predictably control species composition. Composition does not have to be deterministic at
Wilson and Agnew, chapter 6, Theories, page 2 of 43
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the level of particular species, e.g. the determinism might be of guild representation or the
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total number of species in the community. Versus
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Stochastic: The community-determining processes are governed, or at least initiated, by
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chance. Perhaps many of the species in the species pool are ecological equivalents, so
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which arrive and establish at a site is partly “random”. Species composition is therefore
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unpredictable, just one event of a number of similar possibilities.
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The other distinction is between communities that are:
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Discrete: separated by clear boundaries. Vegetation changes suddenly along an environmental
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gradient as one discrete community gives way to another at a boundary, versus
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Continuous: gradual change, without clear boundaries. There is gradual, species-by-species
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change along an environmental gradient, a continuum.
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Well, that’s the theory of theories. These two distinctions have often been confused and are rarely
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specified explicitly. They give four logical combinations:
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(a)
y
(b)
(c)
Fig. 6.1: The distribution of species along an environmental gradient: (a) a simplistic version
of Clements, (b) a simplistic version of Gleason and (c) Whittaker (who needs no
simplification).
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Deterministic and discrete. The species composition is predictable from the environment and
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there are distinct communities (‘associations’) with sharp boundaries and no/few
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intermediates (Fig. 6.1a). This concept has been attributed, very simplistically, to Clements.
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Such structure could arise either by co-evolution or by assembly of pre-adapted species with
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only certain combinations of species being stable (Bazzaz 1987).
Wilson and Agnew, chapter 6, Theories, page 3 of 43
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2.
Deterministic, but continuous. The composition is predictable but there is continuous change
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as along an environmental gradient with no boundaries. Whittaker distinguished between
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such a model without co-evolution (6.1b) and with it (Fig. 6.1c).
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Stochastic and continuous. Gleason at times identified this with his ‘Individualistic Theory’:
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"The vegetation-unit is a temporary and fluctuating phenomenon" (Gleason 1939). The
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implication is that there is a random scatter of bell-shaped curves along the gradient (cf. Fig.
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6.1b), but a literal application of this gives considerable variation in total abundance along
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the gradient, which is surely not intended under the theory.
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4.
Stochastic and discrete. If the community structure is not deterministic, how can there be
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discrete boundaries? By a switch (J.B. Wilson and Agnew 1992). If a propagule lands and
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its offspring appear near it, it might modify the local environment in its favour, resulting in a
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sharp boundary from the surrounding vegetation. A switch of types 2-4 would be required
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for a stable mosaic (chap. 3, sect. 5.2).
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In the first part of this chapter we consider theories that have an overview of the topic of our book,
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of the patterns and their causes described above. However, theoreticians have varied in the degree
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to which they have addressed interactions (chapter 2), community processes (chapter 3),
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coexistence mechanisms (chapter 4) and pattern/assembly (chapter 5, and above).
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2 Clements and the integrated concept
Frederick E. Clements saw communities as integrated: "an organic entity exhibiting
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cooperation and division of labor" (Clements et al. 1929, 314; see also Clements 1905) and thus
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"greater than the sum of its constituent species" (Clements 1935). He produced wide-ranging ideas,
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omitting to give his theory a name because he thought it was The Truth. Phillips (1935), whom
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Clements and Shelford (1939, p. 24) cited with the greatest approval, elaborated on this: "With
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properties definitely unpredictable from a knowledge of the individual organisms", i.e., with
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emergent properties (J.B. Wilson 2002). This implies deterministic structure: "The bond of
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association is so strict ... that the same seral stage may recur around the globe ... with the same
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dominants and subdominants" (Clements et al. 1929). “An association is similar throughout its
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extent in … general floristic compositions” (Weaver and Clements 1938). These communities were
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therefore nameable. This concept has been called the "Integrated" community view (Goodall 1963),
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and the "Community-unit" view (Whittaker 1967). Clements was too good a field ecologist to take
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all this literally, writing that communities had "more or less definite limits" forming a "mosaic, in
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which the various pieces now stand out sharply, and are now obscure”, “[A formation] can rarely
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have definite limits” (Pound and Clements 1900, pp. 313 & 315), the "ecotones are rarely sharply
Wilson and Agnew, chapter 6, Theories, page 4 of 43
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defined" (Clements 1905, p. 181), “Adjacent formations of the same general nature usually shade
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gradually into each other” (Clements 1907, 216).
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Others expanded on Clements’ theme: "All the species which are members of a given
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association ... are adjusted more or less perfectly to one another" (Dice 1952). Tansley, another
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ecologist with great field experience, wrote: “the complex of interactions between plants and their
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environment does lead to a certain degree of order … The same species are constantly present in the
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same kind of place and show the same groupings”. At equilibrium, he said, the association becomes
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“the mature, integrated, self-maintaining quasi-organism” (Tansley 1920). One might think that
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Braun-Blanquet (1932), who described the association as having concrete reality, would have a
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similar view, but he could not accept the degree of integration that Clements proposed, writing: "the
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organismic character, the centralized organisation and the division of labour etc. is lacking in it". In
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spite of the strength of opinions for and against these concepts – "more than the mere sum of its
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parts", "complex organism", etc. – it is difficult to pin them down to testable features.
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Whether communities are ‘complex organisms’ or not, the naming of them implies
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recurrence: that the same community will be found in several different locations. This has rarely
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been tested, but J.B. Wilson et al. (1996b) did so for roadside communities in a range of
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environments across southern New Zealand. The problem is defining “the same” community. It
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would be unrealistic to expect exactly the same species complement, so a baseline is needed of how
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similar two remote quadrats should be in order to be regarded as the same. Wilson et al. answered
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this in two ways. The quadrats had been placed in adjacent pairs. One baseline was therefore the
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mean similarity between the two quadrats of a pair, making the question: “does one ever come
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across another patch of vegetation as similar to this one as the patch next door is?”. Some next-door
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quadrats would happen to be quite different, e.g. in disturbance, so Wilson et al. omitted the 10 %
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of least similar pairs before taking the mean. The answer was basically ‘no’; for only 19 % of sites
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was there another in the survey similar to it by this criterion (Fig. 6.2). However, another
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comparison was available, since the pairs of quadrats at a site had themselves been placed in
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subsites 50 m apart. Using those subsites as the baseline, the percentage of sites with vegetation that
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occurred elsewhere in the survey increased to 83 %. Allowing for the likelihood that vegetation
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similar to any site could have been found outwith the quadrats sampled, we have to conclude that
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communities do recur, and in this Clements was right.
Wilson and Agnew, chapter 6, Theories, page 5 of 43
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Fig. 6.2. Does the same community recur? Comparison of between-site similarities in species
composition with: (a) those between adjacent quadrats, and (b) those between subsites 50 m
apart. From Wilson et al. (1996b).
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One would imagine that Clementsian structure would arise from co-evolution. Clements
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does not seem to have used the term, but he considered that the evolution of species was part of the
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process of community evolution (Clements 1929) and later workers made it more explicit, e.g. the
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"interco-ordinated evolution" of Dice (1952). The most explicit development of such views is that
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of Dunbar (1960) who suggested that selection could operate at the level of the whole ecosystem:
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just as an individual can die and be replaced by one of genotype with higher fitness, so an
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ecosystem can be unstable, collapse to leave “empty environmental space”, and be replaced by a
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community from nearby with genetic differences in some of its species, giving it a higher stability
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(i.e. fitness). Collapse to empty space is not realistic, and the idea reeks of group selection. Darnell
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(1970) had similar ideas, writing that “the ecosystem … is … the basic selectional unit of
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evolution”. He suggested that species-level selection led to evolutionary adaptation, which led to
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stability. Co-evolution cannot lead directly to stability, for selection is for the fitness of the
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individual, not for stability or any other property of the whole community.
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Although many are ready these days to ridicule Clements' views, some contemporary
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ecologists are producing models in which the control of species composition is every bit as tight:
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mainly theoretical ecologists (e.g. Drake 1990), but also field ecologists such as Cody (1989). We
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note that Clements also made outstanding contributions to the study of ecophysiology, interference,
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pollination, evolution and sampling methods. He was the outstanding plant ecologist of his time,
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and of all time.
Wilson and Agnew, chapter 6, Theories, page 6 of 43
3 Gleason
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Gleason’s concepts are widely misunderstood. His first theoretical paper (Gleason 1917)
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was explicitly presented as an alternative to the patterns and their causes espoused by Clements
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(1916) and he later declared, provocatively, that a stand of vegetation is a “temporary and
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fluctuating phenomenon” (Gleason 1939). Clements et al. (1929, 315) in return wrote that
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Gleason’s concept “appears to involve a confusion of ideas as well as a contradiction of terms”.
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Yet behind the invective most of Gleason’s views were identical to Clements’. The
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importance of competition was emphasised by Clements et al. (1929), but also by Gleason (1936)
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who wrote that when any two plants were growing together “each interferes with the environment
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of the other” and that this interference “may act either favourably or unfavourably” so that “the
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vegetation … is the result of the interference”. The latter statement is as strong as any ecologist has
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ever made, and the very opposite of the no-interaction caricature of him often presented. In the
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process, he was among the first to suggest that subvention (‘favourable interference’) is widespread.
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On the mechanism of succession, and the rôle of reaction in it, Gleason’s (1927) views were
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identical to Clements’ (1916).
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The association was described by Gleason as having “limits … fixed by space and time”
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with “tension zones” (i.e. ecotones) between them (Gleason 1927), every community necessarily
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having boundary and uniformity (Gleason 1936). Clements could not have put this better. The
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landscape, in Clements interpretation, was a mosaic of different formations/associations (Pound and
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Clements 1900), with “the same species or formation in similar but separate situations” (Clements
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1907, 289; see also 1904), a situation he called alternation. Gleason’s (1936) concept was identical:
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“a vegetational mosaic, composed of numerous types of vegetation, each repeated numberless
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times, but all united into a harmonious and extensive whole”. Gleason (1917) did state that contra
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Clements exact repetition of the same vegetation never occurs, but Clements did not expect this:
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“No formation is uniform throughout its entire extent. … universal variation may be regarded as a
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law of formation structure” (Clements 1907, 221). It would be amazing for someone with Clements’
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depth of field experience to think otherwise.
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Clements believed that narrow transition zones (ecotones) between associations could occur
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along gradual environmental gradients because of reaction (environmental control). Gleason (1917)
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thought that at least in regions of “genial environment and dense vegetation” there is reaction (a
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term that he used interchangeably with ‘environmental control’) with the result that:
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“species of one association are then excluded from the margin of the other by environmental
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control, when the nature of the physical factors alone would permit their immigration. The
Wilson and Agnew, chapter 6, Theories, page 7 of 43
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adjacent associations meet with a narrow transition zone, even though the variation in
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physical environment from one to the other is gradual.”
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Gleason’s statement is a precise summary of Clements’ view. Both are saying that very often
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switches cause ecotones between associations, because of reaction.
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In terms of our seven steps in community assembly (chap. 1, sect. 2 above), both Clements
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and Gleason would have accepted A-E. Assembly rules (F) are apparent when Clements (1907,
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294) writes on alternation: “owing to the accidents of migration and competition, similar areas
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within a habitat are not always occupied by the same species or group of species. A species found in
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one area may be replaced in another by a different one … Such genera and species … must be
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essentially alike in … response to the habitat, though they may be entirely unrelated
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systematically”. Here there is a niche in a community into which one species or another can fit, an
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assembly rule as strong as any. So far as we can tell, Gleason would not have accepted this.
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There were probably personalities involved, at least in their approach to science. Gleason
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could not stomach Clements’ community-as-an-organism terminology, or the classifications that
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flowed from it. Probably this was because he was a plant taxonomist and saw that communities are
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not the clear objects that most taxonomic species are. “Clements versus Gleason” is a useful straw
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man in introductions to papers, e.g. “the now well-known dispute between Clements (1916) and
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Gleason (1926) … pitting the idea of ‘discrete communities’ against that of a ‘continuum’” (Leibold
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and Mikkelson 2002). However, their concepts of the plant community were almost identical,
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reflecting deep understanding of plant communities and offering a strong springboard for future
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work if today’s ecologists would notice them.
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4 Whittaker and Austin
Whittaker clearly adhered to theory 2, continuous, but deterministic. The community is "a
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distinctive living system with its own composition, structure, ... development and function"
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Whittaker (1975a), with “emergent characteristics (Whittaker and Woodwell 1972). Exclusion-by-
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interference was the deterministic structuring process: "The unique identification of niche with
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species within a particular community ... is not a matter of chance, but as the result of competitive
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exclusion" (Whittaker and Levin 1975, p30). No one has believed more strongly in co-evolution as
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a cause of community structure, though in Whittaker’s case it was co-evolution towards mutual
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avoidance: "toward scattering of their population centers along environmental gradients" (Whittaker
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and Woodwell 1972, see also Whittaker 1967). Thus, “the community is an assemblage of
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interacting and co-evolving species" (Whittaker and Woodwell 1972). Most co-evolution ideas in
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community ecology are suspect because species occur with a number of associates, but Whittaker’s
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idea of at least the dominants co-evolving to minimise interference seems less prone to this
Wilson and Agnew, chapter 6, Theories, page 8 of 43
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problem. From his 'Gradient Analysis' results Whittaker (1967) concluded that vegetational change
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along environmental gradients was a continuum1. This is not the concept of Gleason, who wrote:
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“The adjacent associations … meet with a narrow transition zone, even though the variation in
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physical environment from one to the other is gradual: Gleason 1917, 470).
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From Whittaker’s ideas, Austin and co-workers developed a ‘Continuum Theory’, defined
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as: “the organisation of vegetation structure and composition in terms of continuous change in
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properties along environmental gradients” (Austin and Gaywood 1994). There will certainly be
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spatially sudden changes where switches locally modify the environment to produce a sharp
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boundary: rainforest/savannah, treeline, fog-catching boundaries, etc. (J.B. Wilson and Agnew
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1992). It is not clear how deterministic communities are under Continuum Theory.
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Oksanen and Minchin (2002) defined the simplest version of Continuum Theory as being
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that “species have symmetric, unimodal responses to ecological gradients”. Austin and Gaywood
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(1994) proposed that species response curves are skewed, with the longer tail being towards the
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middle of mesic position. The latter must be hard to define. Austin et al. (1994) did find that all nine
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SE Australia Eucalyptus species that they examined showed significant skewing along a gradient of
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mean annual temperature, in the expected direction if ‘mesic’ is defined as 11.5 °C. This could
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reflect fuzzy control by an interference filter in the mesic direction, but sharp control by an
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environmental filter in more extreme environments. However, the conclusion will depend on the
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type of curve fitted and how skewed is skewed (significance is not the best guide to effect size).
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Moreover, skewness can be reliably determined only when there is good evidence that the whole
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environmental range of the species has been sampled (M.P. Austin pers. comm.). A conclusion of
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skewness also depends on the way the X-axis is expressed, for example a simple gradient assumes
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that the difference between 0 mm and 300 mm rainfall is equivalent to that between 2000 and 2300
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mm, which seems unlikely. The occurrence of bimodal curves could be interesting, but not on a
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proxy gradient such as altitude where it could be due to frost above treeline and similar frost in the
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valleys due to cold air drainage. Austin (1985) commented: “The occurrence of bimodal curves …
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seems well established”. However, he cites Whittaker whose evidence for bimodality was very
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weak (J.B. Wilson et al. 2004). We have not been able to find any good example of bimodality.
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Clearly community gradients exist but we believe that switches often produce boundaries in
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underlying environmental gradients. Analysis of the shape of distributions along gradients seems to
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be a diversion from our search for the nature of the plant community. Before you move to neutral
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models, synthesize your evidence for/against these theories. What is your opinion/conclusion about
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them and what the real pattern and processes are?
Wilson and Agnew, chapter 6, Theories, page 9 of 43
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5 Hubbell and chance
A rôle has often been proposed for stochasticity / chance / random-effects / disorderliness in
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the construction of plant communities (e.g. Lippmaa 1939; Richards 1963; Fowler 1990; Sykes et
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al. 1994). The assumption is that many species are ecological equivalents2 of each other. This is
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behind concepts ‘3’ and ‘4’ (Stochastic-continuous and discreet?) at the beginning of this chapter.
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However, chance does not really exist (cf. chapter 4). Seeds are sometimes said to disperse
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randomly, but in fact they disperse under the laws of physics, it is just that eddy diffusion is very
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complicated. Everything happens under the law of physics (except arguably the resurrection of the
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Our Lord Jesus Christ: J.B. Wilson 2002), and above the scale of the atom chance plays no part.
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Although technically true (about chance), since we are never able to know a system minutely
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enough to know all that we need to to make deterministic models, apparent “chance” is going to
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play an important role in any model for the near future.
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Hubbell and Foster (1986) make the concept of chance explicit, with saying that “biotic
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interactions … are not very effective in stabilizing particular taxonomic assemblages, in causing
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competitive exclusion, or in preventing invasion of additional species” because there are
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“ecologically equivalent species”. Therefore, “chance and biological uncertainty may play a major
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role in shaping the population biology and community ecology of tropical tree communities”.
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Hubbell (2001) developed these concepts into a full ‘Neutral Model’ in which species are
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equivalent in their demography and dispersal, i.e., in which niche differences play no rôle. He
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discovered, apparently to his surprise almost as much as anyone else’s, that many of the features of
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ecological communities that ecologists have long been discussing, such as relative abundance
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distributions, species-area relations and island biogeography, can be predicted on this basis.
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Hubbell’s (2001) theory does not imply that even on one trophic level all species actually have the
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same niche: “No ecologist in the world with even a modicum of field experience would seriously
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question the existence of niche differences among competing species” (Hubbell 2005). Hubbell’s
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(2001) approach is to start with the simplest null model, which in this case comprises the functional
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(niche) equivalence of species, and then to add to the theory only when necessary to explain
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observations in the real world. Hubbell’s earlier work had described niche differences in the very
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tropical rainforest that he often takes as his example: “Some tree species are largely restricted to
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slopes, whereas others are predominant on flat ground or in the seasonal swamp”, “Shade-tolerant
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shrubs and understorey trees are also recognizable guilds. Finally, there are gap-edge regeneration
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specialists” (Hubbell and Foster 1986). These effects would tend to cause aggregation within
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species, but the same workers demonstrated “pervasive” negative effects of plants on neighbours
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that were of the same species. Such effects were confirmed when Uriarte et al. (2004) estimated the
Wilson and Agnew, chapter 6, Theories, page 10 of 43
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effect of neighbouring saplings on the diameter growth of other saplings on Barro Colorado Island,
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work in which Hubbell has been involved. For almost half of the species they could find species-
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specific effects, including more competition if the neighbours were conspecific, or confamilial, or in
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the same gap/shade-tolerant guild. All this emphasises that Hubbell’s (2001) thesis is intended as a
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null model, not a best-fit model.
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Wootton (2005) tested the theory using a 12-year record of transitions in an intertidal
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community (sessile animals and algae) to parameterise a Hubbell (2001)-type model. Model
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predictions matched the observed relative abundance distribution (RAD), but there was no
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alternative model (RAD curves tend all to look rather similar because they monotonically decrease),
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and the confidence limits for the model prediction were wide. Many observed curves could have
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fitted. However, observed species abundance in mussel-removal plots bore no relation to the
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model’s predictions. This confirms the conclusion of Chave (2004) that many ecological models
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can result in the same patterns, especially of the relative abundance distribution (which was already
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known, see J.B. Wilson 1991), but that does not prove that any one of them is correct.
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If the chance theory were correct, there would be no reason to expect community re-
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assembly except by chance and hence no predictability. However, the reverse argument cannot be
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made: a failure to predict species composition well from the measured environmental factors is no
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evidence for chance, as we discussed in chapter 4, section 9. However, Hubbell has most usefully
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reminded us that any statement in community ecology must be made against the background of an
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appropriate null model. Hubble section is redundant from Ch5
6 Grime’s C-S-R theory
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6.1 The triangle
Philip Grime’s (1974; 2001) theory is based almost entirely on the C-S-R triangle, a contrast
between types of habitat and adaptation to them (Fig. 6.3):
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─ high-productivity, low-disturbance habitats / strongly-competitive species (C),
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─ low-productivity habitats / stress-tolerant species (S) and
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─ high-disturbance habitats (D) / ruderal species (R).
Wilson and Agnew, chapter 6, Theories, page 11 of 43
C (competition)
Disturba
nce
(ruderal) R
(disturbance) D
Productivity
C-S-R
K
r
S (stress)
Untenable
triangle
Productivit
Disturbanc
e
Heathrow
airport, main
runway
Fig. 6.3: The C-S-R triangle of Grime (1979).
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This gives a C-S-R triangle of species and an equivalent C-S-D equilibrium of the sites they are in
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(Grime 1988). In the original 1974 formulation of C-S-R theory one axis was RGRmax, i.e. relative
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growth rate in the first few weeks after germination and in optimal conditions, high values defining
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the C-R side of the triangle, but Hodgson et al. (1999) developed a method for placing a species
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within the triangle by weighting several characters. Even a few simply-obtained characters such as
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canopy height, flowering period and SLW can give good prediction of C-S-R category for most
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species (Bogaard et al. 1998; Hodgson et al. 1999), but a wider, and perhaps more meaningful,
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range of characters is desirable (Caccianiga et al. 2006). These ideas were supported by the
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analytical models of Bolker and Pacala (1999), showing that three, and only three, spatial strategies
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are possible. Their ‘Exploitation’ strategy can be matched with C, the ‘Colonisation’ strategy with
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‘R’ and the ‘Tolerance’ strategy with S. We note that Grime has also considered the ecosystem-
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level processes and the rôle of within-community, within-species genetic variation.
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6.2 Stress
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Stress is clearly defined in C-S-R theory as "The external constraints which limit the rate of
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dry matter production of all or part of the vegetation". The disturbance axis (R–C) recalls the r-K
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spectrum of MacArthur and Wilson (1967), but the S (stress tolerators) axis is new to C-S-R theory.
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Grime (2001) sees sees the C-S line as being an expansion of K (Fig. 6.3). He assumes that plants
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cannot grow where disturbance and stress are both high (the grey area in Fig. 6.3), such as the
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middle of Heathrow Airport’s main runway where the soil is too dry and low in nutrients (i.e. non-
Wilson and Agnew, chapter 6, Theories, page 12 of 43
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existent) and is disturbed every two minutes (Fig. 6.3). The omission of the ‘untenable triangle’
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leaves the C-S-R triangle (Fig. 6.3).
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There remains the problem of stress to which species. Take an alpine herbfield, where
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temperatures are low (Körner 2003b). Humans would consider this a stress (except perhaps skiers),
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and so would most plants. Yet under climate warming, heat-loving plants would be able to
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establish, and probably by interference exclude the alpines. How can we say that the alpines were
352
under stress before, when they were growing to their hearts' content, but that they are not under
353
stress now that they are dead? There may be more to their death than interference: some alpine
354
species grow poorly in ‘low-stress’ sea level conditions, probably because they lose carbohydrate in
355
the warmer winter temperatures there (Stewart and Bannister 1973). One would think that the
356
phytometer approach of Clements and Goldsmith (1924) would be ideal: planting the same species
357
into a range of communities and measuring its growth. However, Grime has chosen to define stress
358
on a whole-community basis and on the basis of the plants presently occurring, and is clear and
359
consistent in that.
360
Perhaps the most difficult habitat for C-S-R theory is forests. The dominant trees of tropical
361
rainforests might be seen as the ultimate competitors, but Hubbell (2005) described them as the
362
“competitive (stress tolerator) functional group”, with characteristics typical of S species: tolerance
363
of low light levels (as juveniles), long life spans, high resistance to pests and herbivores. This rather
364
depends on how the dominants regenerate. If they grow fast from seed or from suppressed seedlings
365
after disturbance they could be C species, almost R. Others have seen the dominants as species that
366
are shade tolerant and grow slowly up through the canopy, or sit still “conservatively” tolerating the
367
stress of shade and make bursts of growth during temporary gaps, in which case they are S species
368
as juveniles, though not as adults. Indeed, the understorey plants of evergreen forests tend to be
369
slow-growing evergreens, S species (Grime pers. comm.). Then again, trenching experiments have
370
shown that competition for nutrients is often more limiting than light to herbs and seedlings on the
371
forest floor (Coomes and Grubb 2000).
372
It is very difficult to characterise a whole site as low/high stress in terms of light, since in a
373
productive environment there will always be some species low in the canopy that have to tolerate
374
the stress of shade from taller plants (Pigott 1980). Grime had envisaged that any community would
375
comprise a mixture of species with different C-S-R status, but in this case it is not just a case of the
376
overlap of species' ecological ranges, or of micro-habitat variation, because, as Pigott notes, the
377
species "grow together in vegetation ... because they possess different strategies" [italics ours].
378
Since the r-K spectrum is widely accepted, the controversial aspect of C-S-R theory is that
379
different kinds of stress have much in common, resulting in a consistent S-species type. Such
380
species grow slowly, at least in their natural habitat. Leaves can therefore be produced only
Wilson and Agnew, chapter 6, Theories, page 13 of 43
381
infrequently, so they must function for more than a year. This results in a whole suite of leaf
382
characters, e.g. evergreen, low maximum photosynthetic rate, low percentage nitrogen, abundant
383
defence compounds, small, often stiff and tough, needle-like and with high SLW (Reich et al. 1991;
384
1992). This suite of S characters is also part of leaf costs / amortisation theory of Orians and Solbrig
385
(1977), indeed we can see the relation: C-S-R = r/K theory + Leaf Amortization theory (J.B. Wilson
386
and Lee 2000). Since the original formulation of C-S-R, Grime (1988; 2001) has concluded that the
387
common underlying stress is a deficit of major mineral nutrients either directly or as a result of
388
other stresses. This view is comparable to that of some physiologists, who have proposed a unifying
389
stress mechanism (see J.B. Wilson and Lee 2000). Craine (2005) considers this at least unproven.
390
It has sometimes been suggested that low RGRmax is directly adaptive in stress environments
391
(e.g. Hunt and Hope-Simpson 1990). However, adaptation to stress environments is by relatively
392
high RGR in those environments, not by low RGR in a hypothetical optimal environment. Low
393
RGRmax is adaptive to stress environments only via a strategic trade-off: "It is possible that genetic
394
characteristics conducive to rapid growth in productive conditions become disadvantageous when
395
the same plants are subjected to environmental extremes" (Grime and Hunt 1975).
396
A limitation to the generalisation of C-S-R is that different types of stress favour different
397
types of species (Grime 1988). Moreover, not all species are adapted to one particular stress in the
398
same way. A dramatic example of this is seen in the wide range of life forms that are found in
399
adaptation to variable water stress in deserts. Some deserts, e.g. the Namib, have predictable rain in
400
one season (summer for the Namib) and support relatively few extant life forms, whereas others
401
such as the North American deserts, with rainfall less predictable from year to year, support a very
402
wide range. Some species are adapted by being avoiders, including stem succulents such as cacti
403
and leaf succulents as in members of the Crassulaceae, but also annuals/ephemerals which avoid
404
water stress as adults by dying and surviving water stress as dormant seeds. Yet others, like the
405
shrubs, are tolerators, having very low water potentials in their tissues in dry periods and shedding
406
leaves and even branches, but tolerating this without death. Again, this emphasises C-S-R as a
407
simplification.
408
Whereas C-S-R theory sees all stresses as in some sense equivalent, the ‘Centrifugal
409
Theory’ of Wisheu and Keddy (1992) emphasises their differences, placing them on multiple axes
410
diverging from the productive sites. As Austin and Gaywood (1994) point out, this is a display, not
411
a theory because it does not make testable predictions.
412
6.3 Disturbance
413
414
Grime’s definition of disturbance is unambiguous: "The mechanisms which limit the plant
biomass by causing its partial or total destruction". This refers to the whole community, but this
Wilson and Agnew, chapter 6, Theories, page 14 of 43
415
brings the problem that what is a disturbance for one species might not be for another (paralleling
416
one of the criticisms relating to stress). For example, the mowing disturbance of Burke and Grime
417
(1996) will have disturbed the tall species, but increased the resource (light) availability to short
418
ones. Selective grazing is another example. Short or unpalatable species might be described as
419
‘disturbance avoiders’ in contrast to ‘disturbance tolerators’, but it is not clear how this distinction
420
fits into C-S-R theory. How does C-S-R theory incorporate autogenic disturbance (chap. 2, sect. 6)?
421
One answer to this is that C-S-R theory is largely about the characters of species and that species of
422
different C-S-R status can co-occur. However, productivity, stress and disturbance are all defined
423
per site, and there is also a C-S-R triangle of sites, for example Grime (2001, Fig. 40) shows
424
“habitats experiencing intermediate intensities of competition, stress, and disturbance”.
425
6.4 Competition
426
Some have rejected the concept of competitiveness as an overall plant attribute, i.e. the
427
concept that a species that is a superior competitor for one resource is also a superior competitor for
428
all other resources (e.g. Grubb 1985). This is one prediction of C-S-R theory that can be tested quite
429
clearly. Contrasting shoot competitive ability (for light) with root competitive ability (for water and
430
the major nutrients) for the same species in the same conditions, the data assembled by J.B. Wilson
431
(1988c) indicate 13 (22 %) cases where the relative competitive abilities of two species were in a
432
different direction between shoot and root competition, and 46 (78 %) where they were in the same
433
direction, a significant difference. This supports the general idea of interference ability, but not that
434
it invariably applies to all types of interference. Non-transitivity of competitive ability (chapter 7)
435
would make a nonsense of the idea of overall competitive ability, but it seems to be rare or non-
436
existent (chap. 4, sect. 4). Another prediction of C-S-R theory is that competition intensity will be
437
lower in stress sites (Grime 2001). Grime (op. cit.) writes: “Some ecologists are extremely reluctant
438
to recognise the declining importance of competition for resources in unproductive habitats”. We
439
agree. We are amongst them, as we discuss below.
440
6.5 Species/character tests
441
The basic assumption of C-S-R theory is that there are “design constraints" (Grime 1988,
442
Grime et al. 1988) that limit viable character combinations. Reich et al. (2003) found a compelling
443
negative correlation between leaf lifespan and net photosynthetic capacity, though of course with
444
scatter, and a slightly weaker one via leaf N. Grime et al. (1987) made a more general test by using
445
a range of characters to classify species with cluster analysis and then looking for correlation
446
between the resulting groups and the three C-S-R 'strategies'. They found, in one analysis, a group
447
of low-stature, evergreen species with 'tough' foliage comparable to the S group. Grime et al. (1997)
Wilson and Agnew, chapter 6, Theories, page 15 of 43
448
used 67 characters, including experimental responses, to ordinate 43 species. They could informally
449
overlay a C-S-R triangle on the ordination diagram. There was also a good fit between this
450
ordination and that derived in Grime et al. (1988) from field distributions: e.g. the three species in
451
the C corner of the character ordination are in that corner in the distribution ordination, with
452
comparable fits for the S and R corners. This gives some support to C-S-R theory. A more direct
453
test of these trade-offs would be to find unoccupied character space, beyond the triangle.
454
Other tests can be made by determining whether species of the right type occur in the right
455
habitats. For example, Madon and Médail (1997) examined the distribution of species in a
456
Mediterranean grassland. Sites with a high cover of S species (but how they were designated as S
457
species is unclear) also contained a higher cover of annuals, but they do occur in S sites as well as R
458
ones and indeed are frequent in most such semi-arid grasslands and in some deserts. This
459
emphasises that C-S-R theory is a generalisation, not a law of the type that physicists can have.
460
Caccianiga et al. (2006) attempted to test C-S-R theory on succession on glacial moraines in
461
Italy. The concept is valid and it was a brave attempt, but unfortunately they used guessed species
462
cover. They found a succession3 from communities dominated by R species to those dominated by
463
S ones. Such a change is predicted by C-S-R theory, but there are problems. The prediction is for an
464
intermediate trend towards the C corner, and we would not expect the S corner to be reached within
465
the <200 yr of their dataset, though both of these may have been because the environment was a
466
high-stress one. Most problematic is that under C-S-R theory the R→S change that Caccianiga et al.
467
found occurs in a secondary succession; in a primary succession, which theirs certainly was, the
468
trend should be S→C-S-R→S (Grime 2001).
469
An experimental approach is perhaps better, since one can be sure what the habitat
470
differences are. Moog et al. (2005) applied four basic treatments – sheep grazing, mulching with
471
hay, burning in winter and control (‘succession’) – at 14 sites in southwest Germany. The
472
vegetation resulting 25 years later was classified in terms of C-S-R composition, using guessed
473
cover and calculating species’ C-S-R rankings by the method of Hodgson et al. (1999). There were
474
some changes in community C-S-R status that agreed with the theory. For example, grazing and
475
twice-yearly mulching, both presumably disturbances, reduced C-ness to c. 0.35 below the control.
476
Grazing and burning increased S-ness by c. 0.2 above the control. Moog et al. explained this
477
grazing effect due to the herbivory defence of S-strategists, or due to nutrient removal, though it is
478
not clear whether grazing will reduce nutrient availability or increase it through nutrient recycling.
479
They explained the increase in S-ness with burning as an indirect effect, that burning favoured
480
species with rhizomes which happened to be S-strategists, though severe burning can lower
481
nutrients (Certini 2005). Grazing and mulching increased R-ness by 0.4-0.5 above the control, as
Wilson and Agnew, chapter 6, Theories, page 16 of 43
482
predicted by C-S-R theory. However, large differences in C-S-R status were found between the
483
same treatment at different sites, up to 1.0 difference. Not clear-cut.
484
6.6 Does succession provide a test of C-S-R?
485
We shall consider here only secondary succession, because the most clear-cut tests are
486
available for them (J.B. Wilson and Lee 2000). Grime's (1979) interpretation was that for sites of
487
differing productivity there would be separate successional pathways, all starting from the R corner,
488
and all ending (eventually) in the S corner (Fig. 6.4a). At the start in the R corner, the S and C
489
succession trajectories are very close (Fig. a). Thus difference between stressful and benign
490
environments is negligible in plant characters, giving the opportunity for the same species to occur,
491
i.e. the same ruderal species in stressful as in benign habitats (Fig. 6.4b). Grime’s figures (Fig. 6.4a)
492
do not show any sites reaching up to the C corner but presumably they do, or there’s no point in
493
having a C corner.
494
Fig. 6.4. C-S-R theory and specialist pioneers. Grime suggested that sites with differing degrees
of stress would follow different pathways. - - - indicates the part of the succession which will
probably be slow.
(b) The lack of difference between C and S in the R corner makes it possible for the same
species to occur along different pathways.
495
Considering the three S habitat types discussed by J.B. Wilson and Lee (2000), the main pioneer of
496
degraded land in Naiman Banner County, Inner Mongolia, is Agriophyllum squarrosum, a specialist
497
pioneer of dunes in semi-arid areas (Zhang et al. 2005). In Sonoran Desert oldfields, pioneers
498
include the very widespread weed Taraxacum officinale (dandelion), but also species such as
499
Salsola kali (tumbleweed) a ruderal annual of dry, often alkaline areas (Castellanos et al. 2005).
500
These recent examples add to the conclusion of Wilson and Lee (2000) that in arid habitats the
Wilson and Agnew, chapter 6, Theories, page 17 of 43
501
majority of secondary pioneers conform to the prediction of Fig. 6.4a in not being restricted to
502
deserts, though some are. The secondary pioneers of saltmarsh gaps are generally species of the
503
lower saltmarsh, as would be expected, since all species that occur on salt marshes, ruderal or not,
504
have to be quite salt tolerant: no agreement with prediction. Moving to alpine stress, the species
505
present in mid succession in southern New Zealand alpine grassland included the dicots Anisotome
506
aromatica, Plantago novae-zelandiae, Colobanthus strictus and Epilobium alsinoides (Lloyd et al.
507
2003), the last extends down to the lowlands, but the others are basically montane / subalpine in
508
range. J.B. Wilson and Lee (2000) gave an example from alpine Scotland where the first colonists
509
were not specialist pioneers, but species of several S habitats. However, pioneers in the Andean
510
alpine oldfields include the very widespread ruderals Erodium cicutarium (stork’s bill), Poa annua
511
and Rumex acetosella (sheep’s sorrel; Sarmiento et al. 2003). There seem to be no generalisations
512
here. The above species names don’ t mean much to me. Spend less time/space identifying the spp
513
(which are going to be unfamiliar to many readers) and more time discussing the patterns,
514
Grime (2002) shows primary succession in S environments as occurring within the S corner
515
of the triangle. J.B. Wilson and Lee (2000) argued that only specialised species would be able to
516
tolerate the environment of an S site. This gives the likelihood of autosuccession, with no
517
specialised secondary pioneer species. Again, C-S-R theory strictly predicts the same type of
518
species, but if there is space for fewer different niches there will tend to be fewer different species.
519
J.B. Wilson and Lee (2000) tested this prediction in relation to four types of stress. In alpine
520
environments they cited two examples, one where autosuccession was occurring and one where it
521
was not. Sarmiento et al. (2003) found that in high-Andean oldfield succession, of the eight most
522
abundant species in the undisturbed community, four were absent the first year after abandonment,
523
three others were present only in traces and the remaining one made up less than 1 % of the cover –
524
no autosuccession here. In arctic tundra, another habitat cited by Grime (1979) as high-stress, there
525
are usually pioneers, but autosuccession is occasionally seen (J.B. Wilson and Lee 2000).
526
Autosuccession is often seen on saltmarsh, especially on the more S lower saltmarsh, though it is
527
not certain that Grime would count saltmarsh as an S habitat. For desert, E.A. Allen’s (1991)
528
suggestion that autosuccession is common is not supported by the literature (J.B. Wilson and Lee
529
2000) or by Castellanos et al. (2005) in the Sonoran Desert, though the evidence of Zhang et al.
530
(2005) from China is mixed. There is some tendency for autosuccession to occur in the most
531
extreme S habitats, though it occasionally occurs in mesic habitats (J.B. Wilson and Lee 2000).
532
6.7 Conclusions
533
534
There have been many more criticisms of C-S-R theory, but most of them have missed its
point (J.B. Wilson and Lee). Several of the predictions of C-S-R theory are very difficult to test,
Wilson and Agnew, chapter 6, Theories, page 18 of 43
535
reducing the value of the theory as an explanatory model for the structure of plant communities.
536
Even for predictions that are more easily tested, there has been little quality evidence. However, the
537
evidence so far is that predictions from C-S-R succeed more often than they fail so that it is useful
538
generalisation.
7 Tilman’s theory
539
540
Tilman (Titman 1976; Tilman 1982; 1988; etc.) has produced a number of ideas. Here we
541
emphasise those that have made a particular contribution to the topic of our book. The concepts
542
have been described as having “a hard centre but woolly edges”: that is, there is a solid core of
543
irrefutable mathematics, but it is not always clear how to apply them to the real world. Some
544
aspects – strategy, species richness and competition – are considered in comparison with Grime’s
545
theory (section 8).
546
Titman (1976) concluded from his first experiments: “long-term coexistence of competing
547
species was observed only when the growth rate of each species was limited by a different
548
nutrient”. This is standard Gaussian exclusion by interference, but he developed his R* theory of
549
how it happened. He later developed a concept of spatial niches (Tilman 1988), and then embraced
550
the fugitive model (Tilman 1994; see chapter 4 above). Craine (2005) has documented the
551
developments and retreats of Tilman’s theories. ~You mention 2 other TIlman theories here that are
552
not discussed. You also hint that they are developments that grew out of R* theory. Discuss more
553
or drop mention of them if they don’t tie into/clarify R* theory.
554
7.1 The competitive process: R*
555
Tilman’s (1982) R* theory is that a particular species in a particular set of environmental
556
conditions has for a particular resource R a value R*, which is the lowest [R] (i.e. concentration of
557
R) at which it can grow in monoculture. Above its R* the species can grow, absorb R, and will
558
therefore lower [R] towards R*. In mixtures, where R is limiting, as [R] becomes lower each
559
species will drop out as [R] drops below its R* and it can no longer grow. Apparently no species
560
will enter during this process. The one species left will be the one that can tolerate that the lowest
561
[R], and the concentration of R at that moment will be its R*. To summarise, the species with the
562
lowest R* will be the superior competitor. The model is deceptively simple. Application to the real-
563
world terrestrial communities is another matter.
564
Major soil nutrients (NPK)
565
Tilman (1981) found that the R* model explained which species of alga won in a microcosm
566
experiment with inorganic nutrient limitation, in constant temperature, a constant daily light regime,
567
fixed lighting conditions and with the solution well mixed by flow and shaking. T.E. Miller et al.
Wilson and Agnew, chapter 6, Theories, page 19 of 43
568
(2005) surveyed the literature and found 11 similar plankton microcosms experiments and (contra
569
Miller et al.’s conclusion) all tended to support the theory (Wilson et al. submitted).
570
The situation is not so clearcut in soil where the environment is variable in time and space.
571
Tilman and Wedin (1991a; b) in field plots at Cedar Creek found the outcome of competition on
572
low N soil was predicted by R* in some cases. Comparing the grasses Agrostis scabra (bent) with
573
Schizachyrium scoparium (little bluestem) the two performed approximately equally in
574
monoculture, but in competition S. scoparium was the clear winner. By R* theory, it should have
575
reduced N in the soil (both nitrate and ammonium) to a lower level than A. scabra, and indeed
576
available N as measured by KCl extraction was lower. It should also have been able to grow at a
577
lower N level, but the experimental results do not tell us one way or the other. A. scabra suffered in
578
competition at the low N levels that S. scoparium produced, but not necessarily because of them.
579
Indeed it suffered almost as much in competition in the two higher N levels. Very similar effects
580
were seen in competition between the A. scabra and Andropogon gerardii (big bluestem) and in a
581
less clear-cut way in competition between A. scabra and Agropyron repens (quackgrass). These
582
results are ambiguous: perhaps A. scabra is more efficient at N uptake, but suffers in light
583
competition. Indeed, it grew shorter than other species, including S. scoparium in the experiments
584
of Tilman (1986).
585
Even conceptually it is difficult to apply R* to soil nutrients. Plants will lower [N/P/K] to
586
some extent. However, these elements are always being mineralised from organic matter by
587
decomposers at rates which depend on the environment, soil microflora and the fauna. Leaf leachate
588
also makes some contribution. They are added in normal and occult precipitation, and in the settling
589
of atmospheric particulates. Against this, they can be made unavailable by being immobilised from
590
solution to exchangeable form and then to unavailable forms, organic or mineral, by being taken up
591
by bacteria and other micro-organisms, or eventually by being lost by leaching and soil erosion. In the
592
case of N, the mineralisation is to ammonium, taken up thus by some plants, but for others first
593
nitrified to nitrate and taken up in that form. It can also be fixed from the air by free-living soil micro-
594
organisms and in larger quantities by the symbioses with legumes and several other species and,
595
perhaps thus added to the soil or perhaps not. It can be lost by denitrification/volatilisation. P and K
596
can be made available by hydrolysis of minerals, especially of feldspars and apatite, a process that
597
can be speeded by exudates from plant roots. Fire can increase the loss by erosion and volatilisation,
598
and animals can cause local loss of nutrients through redistribution. Vitousek (2004) describes many
599
of these processes for Hawai’i.
600
These processes are all dependent on water and some are affected by the pH of the soil, and
601
therefore depend on various environmental factors. As a result, all are patchily available in 2-D
602
space. Since most of nutrient processes start at the soil surface there is usually considerable
Wilson and Agnew, chapter 6, Theories, page 20 of 43
603
variation with depth. Availability also varies markedly in time, varying stochastically and with
604
season. Nitrogen will normally be most abundant in spring, when maximum growth occurs (Tilman
605
and Wedin, 1991a, measured soil N in summer). Plant roots will hardly lower total [P], since most is
606
insoluble. Unlike N, with its fast-diffusing NH3 and NO3 ions, available P is almost immobile so
607
plants cannot rely on diffusion to acquire the element from the soil as a whole, but have to forage
608
for it by growth. The cylinder around the root from which they take up P can be as narrow as 1 mm in
609
radius (Kraus et al. 1987). This basic difference between competition for mobile N and that for
610
immobile P was pointed out by Bray (1954), and Craine (2005) emphasised how misleading an
611
overall [R] value is with P, since there is localised depletion. How can R* theory be applied in these
612
circumstances? The preceeding 2 paragraphs give way to much detail. It is enough to say that
613
nutrients vary in space and time in response to many factors, biotic and abiotic, and the interactions
614
between them. IF our audience is at tehgrad student level or higher they will know this and don’t
615
need to be convinced by lots detailed examples.
616
Water
617
Water is available intermittently in time, a complication for R* theory, and often at different
618
depths. Most water lands on the surface and perhaps moves down, but water can also be available
619
from deep aquifers and by hydraulic lift plants. Thus, plants are not using the same pool of water in
620
time (ephemeral annuals versus perennials) or space (deep-rooted shrubs and perennial grasses
621
versus shallow-rooted cacti). How does R* apply then? Perhaps it would apply within one of these
622
rooting “guilds?”
623
Light
624
In light competition, canopy species reduce the resource availability below them, but not
625
above them; R* theory knows nothing about directions. By R* theory, the climax canopy species
626
would reduce lower-stratum light to low levels, and be able to tolerate these low levels and hence
627
regenerate. But this depends on whether there is continuous regeneration, large-gap regeneration or
628
single-tree replacement, and in the latter two cases whether the next generation is from dispersal,
629
the seed pool, from suppressed seedlings or from advanced regeneration. All these modes occur,
630
often within the same community, different species regenerating by different modes (e.g. Lusk and
631
Ogden 1992; Thomas and Bazzaz 1999), but there seems to have been no review of the relative
632
importance of these modes.
633
Assuming continuous below-the-canopy regeneration, R* predicts that shade-tolerant plants
634
will achieve tolerance by having a lower light-compensation point. Kitajima (1994) compared 13
635
tree species of Barro Colorado Island rainforest. Shade tolerance was determined as the survival
636
rate of seedlings under a shade cloth that gave light intensity very similar to that of the forest
Wilson and Agnew, chapter 6, Theories, page 21 of 43
637
understorey, with supporting evidence by field observations of mortality in the understorey and the
638
tendency of the species to occur in light gaps. Survival in shade was uncorrelated with the light
639
compensation point (r = +0.27) and with dark respiration (r = +0.25 on a mass basis). Eschenbach
640
et al. (1998) examined tree species of North Borneo lowland dipterocarp forests in the field. Light
641
compensation points were attained mainly between 6 and 9 μ mol photons m-2 s-1 but were higher
642
for pioneering species. This supports an R* interpretation in continuous regeneration, but the
643
presence of pioneer species reminds us that gap regeneration is occurring.
644
The truth is that regeneration in forests, and probably in some other communities, is too
645
complex to fit R* theory.
646
Conclusion
647
None of these complications occur in environmentally-constant, homogenous, nutrient-
648
limited habitats such as a lab tank with planktonic algae that Tilman had in mind when he formed
649
R* theory, and it usually gives correct predictions for them (Wilson et al. in press). In real habitats,
650
R* theory is not only very complex to test, it is often impossible to see how to apply it or test it.
651
There are many, obvious simplifications in this model. It would have been very useful had R* been
652
able to predict competititve ability, for the many previous attempts to find empirical correlations
653
between competitive ability and plant characters have generally failed (e.g. Jokinen 1991). An
654
exception is the obvious correlation of height when competition for light is important (e.g. Balyan
655
et al. 1991), a correlation expected under C-S-R theory, but not under R* theory. There is a problem
656
that under R* theory competitive exclusion would lead to only one species remaining, yet
657
communities almost always comprise many species, not least in Tilman’s own site at Cedar Creek.
658
There, in a 49-yr oldfield (the second-oldest field) there were 12 species per 0.5 m2 quadrat (Inouye
659
et al. 1987). There was not even a downward trend: the 49-yr value was the highest amongst the 22
660
fields and the overall trend, although non-significant, was for richness to increase with age.
661
7.2 Succession
Wilson and Agnew, chapter 6, Theories, page 22 of 43
662
Tilman (1982) also generated a resource-ratio theory of succession, starting from the
663
observation that at his Cedar Creek experimental site soil nitrogen (N) increased during secondary
664
succession. This is often the case, though it is difficult to know what fraction of soil N is available
665
to plants. This led him to theorise that the early-successional species would have low R* for N
RGR response to X10 nitrogen increase
1.35
Poa
pratensis
1.3
Schizachyrium
scoparium
1.25
1.2
`
1.15
Agrostis
scabra
1.1
0
2
4
6
8
10
N status in field: rank
Fig. 6.6: The experimental response to N compared to the rank of species in a
successional/N field gradient.
666
therefore be better competitors at low N; late-successional species would require high N, but be
667
better competitors, probably for light, in those conditions. He performed experiments with co-
668
workers and concluded that later successional species at Cedar Creek do not necessarily have a
669
higher N requirement or response (Tilman 1986; Tilman 1987b; Tilman and Cowan 1989). The
670
former statement is true: the modal nitrogen content of the soil in which various species grow at
671
Cedar Creek (Tilman and Wedin 1991a) is not significantly related4 to their RGR at low N (Tilman
672
and Cowan 1989) nor5 to their growth at high N. However, their response to N (RGR at high N /
673
RGR at low N, data as above) is clearly related6 to their modal soil N (Fig. 6.6). What is not so well
674
related is their successional position. The low-responding Agrostis scabra does indeed appear early
675
on and peak at c. 5 five years (Tilman and Wedin 1991a), but the high-requiring and high-
676
responding Poa pratensis (meadow grass) peaks at c. 15 years, whereas Schizachyrium scoparium
677
is hardly present then, and peaks at c. 45 years. Harpole and Tilman (2006) and Fargione and
678
Tilman (2006) produced similar partial support by correlating previously-determined nitrogen R*
679
values with relative abundance in three semi-natural or experimental areas at Cedar Creek. This
680
assumes that competitive ability and abundance in a mixture will be correlated and this is not
681
necessarily so (chap. 3, sect. 7.3). The correlations were highly significant but reflect only that the
682
three abundant species have low R*, whilst that for other species covers the range from low to high.
683
684
There was considerable respect for Tilman that he had published many results with frank
admission of their conflict with his theory. However, this leaves R* theory hanging (Craine 2005).
Wilson and Agnew, chapter 6, Theories, page 23 of 43
685
It is also difficult to generalise the ideas. Tilman emphasises the increase in soil nutrient status,
686
especially of nitrogen, during both primary and secondary succession (Tilman 1988). Soil nitrogen
687
indeed normally increases through succession, though there is evidence that after some hundreds to
688
thousands of years there is a decrease (Richardson et al. 2004; Crews et al. 19957, examining a
689
4100000 yr chronosequence in Hawai’i), but often phosphate limitation is a major determinant of
690
plant growth during succession and it decreases (Chapin et al. 1994; Richardson et al. 2004). We do
691
not consider these theories useful for the real world.
692
7.3 Conclusion
693
Tilman followed the example of MacArthur in producing formal models of how
694
communities might work. He and many others have been able to test his models (Miller et al. 2005).
695
R* theory has proved highly robust for micro-organisms in experimental conditions, though it is
696
hard to see how it will extend to embryophytes. Moreover, when Tilman attempted to put
697
successional processes on a more formal basis, reality proved to be more complicated. We discuss
698
other ideas of his below, notably agreeing with his ideas on the intensity of competition along
699
gradients of productivity. Tilman tried to find neat patterns in ecology. It was brave of him.
8 Grime versus Tilman
700
701
The ideas of Tilman have often been compared with Grime’s. However, C-S-R theory is a
702
coherent body of ideas, including the characters of the species, the characteristics of the habitats,
703
succession, whole-community attributes such as stability and the relation of species richness to
704
productivity (the humped-back theory). All these are interconnected. It has remained essentially
705
unchanged since 1979, the only major addition being that all stresses are basically unavailability of
706
mineral nutrients. Love it or lump it, it is the only comprehensive, coherent theory we community
707
ecologists have. Tilman’s theory, in contrast, includes a number of ideas that are rather separate,
708
covering the mechanism of competition, where competition will be most intense, how resources
709
will change during succession, whether and how species will co-exist, species diversity, etc. Some
710
of these theories have been effectively disproved, even by Tilman himself, but others remain alive.
711
To some extent this reflects that the theories are put in a more testable form than Grime’s. Grime
712
does have one undisputed advantage over Titman/Tilman: he did not change his name part way
713
through.
714
8.1 Strategy
715
716
The concept of strategy is old, and intuitive to every child, that the effort a plant or animal
puts into one organ or activity is at the expense of another. Plant ecologists generally think of
Wilson and Agnew, chapter 6, Theories, page 24 of 43
717
biomass, though calorific content might be more appropriate. Cody (1966) stated the concept
718
eloquently: “It is possible to think of organisms as having a limited amount of … energy available
719
for expenditure, and of natural selection as that force which operates in the allocation of this …
720
energy in the way that maximises the contribution of the genotype to following generations” (the
721
“…” omissions were “time and”; it is easier to see time as a resource for animals than for plants).
722
Harper and Ogden (1970) applied this concept to plants by examining the proportion of energy
723
allocated to reproductive structures. Much consideration has been given to the selective advantages
724
of particular reproductive strategies, formalised in terms of optimal strategy and later more correctly
725
as evolutionarily stable strategy (Smith 1982). The concept applies to a whole species, to ecotypes
726
and to plastic responses. It applies to vegetative allocation too, for example, shoot versus root
727
allocation: "the plant makes every endeavour to supply itself with adequate nutriment, and as if,
728
when the food supply is low, it strives to make as much root growth as possible” (Brenchley 1916).
729
This principle is implicit in C-S-R theory; it explains why no species can be a perfect competitor, a
730
perfect stress-tolerator and also a perfect ruderal. Indeed, Grime commonly refers to C-S-R as
731
‘Strategy Theory’, as though it were the only one. Tilman has also moved to an emphasis on
732
strategy with his ALLOCATE model of plant growth and competition (Tilman 1988), emphasising
733
shoot versus root strategy, a field with a long history of theory and observation (J.B. Wilson 1988a),
734
but usefully put into the context of the community.
735
8.2 Species diversity
736
Tilman (1982) reached a similar conclusion to Grime (1974), that there would be a humped-
737
back relation between productivity and species richness. Like Grime, Tilman’s argument for low
738
richness under low productivity included the idea that there are few species capable of growing in
739
conditions of high stress, but he also suggested that environmental heterogeneity would be low
740
there, with all microsites equally stressful. He also agreed with Grime in seeing a decrease in
741
richness at high productivity as being due to greater competitive exclusion. He later, finding that
742
nitrogen application led to a reduction in species richness in the Cedar Creek oldfields, converged
743
with Grime’s conclusion that this effect was due to shading suppression by live plant material and
744
litter (Tilman 1993).
745
8.3 Competition
746
Grime’s and Tilman’s hypotheses
747
Grime’s (1974; 2001) theory is that in the S corner of the C-S-R Triangle there is no
748
competition because neighbours are too limited by the physical environment to interact. Near the S
749
corner, competition is low. This conflicts with ecological common sense and close-to universal
Wilson and Agnew, chapter 6, Theories, page 25 of 43
750
observation. Almost everywhere plants fill the area. Having grown, how do they stop when they
751
reach this state, unless through competition? As elsewhere, ‘competition’ has been used when other
752
kinds of interference will be involved too, but we shall consider competition for the moment.
753
Tilman’s (1988) contrary view is that competition will be equally important in unproductive (high
754
stress) and productive (low-stress) environments. The logic seems to be that if resource availability
755
is too high for there to be competition, the plants will grow until availability has been reduced so
756
that there is competition for it, or until another resource becomes limiting. For Grime the issue is
757
connected to his humped-back model of species richness: at low productivity / standing-crop R and
758
C species will be absent. D.A. Wardle (2002) uses this argument to comment that Tilman’s R* model
759
is “difficult to reconcile with the frequently observed humped-back relationship between diversity and
760
productivity”, because according to Tilman competition, and hence competitive exclusion, will be no
761
greater at high biomass. Wardle’s statement is misleading for several reasons: (a) the humpedback
762
relation is far from universal, especially considering significance by an appropriate test of the
763
downturn at high richness, (b) the usual relation has been with richness, not diversity, (c) productivity
764
has hardly ever been measured, only above-ground standing crop, and (d) the logic is based on the
765
downturn in richness at high standing-crop being due to exclusion by interference, which even Wardle
766
admits is only “a likely reason”.
767
An explanation for population maintenance without competition in high-stress
768
environments, such as deserts, has been a low probability of ecesis and/or high mortality. An ecesis
769
rate that happens to exactly balance mortality is infinitely unlikely. Yet, even a slight deficit of
770
ecesis over mortality would give RGR (population growth rate) less than 0.0 and a population that
771
declined to zero, and even a slight excess of ecesis would give RGR greater than 0.0 and a
772
population that climbed towards infinity. Neither are ever seen in existing populations. THemean
773
could be 0 with variation on wither side. Thereby creating stability albeit a tenuous one. The
774
logical conclusion is that in all persistent populations of a species, ecesis and/or mortality must be
775
density-dependent, and the most likely explanation is competition. We conclude that in all
776
environments plants will increase in abundance until they are limited by interference, usually
777
because competition is 100 %, even if we ecologists, as outsiders, cannot easily see what the critical
778
resource is. There are two riders to this. Firstly, competition will be absent in the very earliest stages
779
of succession (Clements et al. 1929). Another possible explanation of sparse populations could be
780
that they are present because of subsidy from elsewhere: the spatial mass effect (chap. 4, sect. 10),
781
but it seems unlikely this is the main explanation of large areas of desert vegetation. Thirdly, it
782
would be possible for density-dependent herbivory to hold abundance too low for competition to
783
occur. It is not clear this could happen, because with such low levels of plant productivity herbivore
784
populations might not be able to exist.
Wilson and Agnew, chapter 6, Theories, page 26 of 43
785
Grace (1991) made another important point: “both Grime and Tilman discuss gradients in
786
habitat productivity as if it makes no difference whether they are gradients in [resources] or non-
787
resource factors”. However, there is more complication. Many studies in the literature examine the
788
effect of a mineral nutrient such as N in a system where competition is probably for light, or even
789
necessarily for light by the experimental design. For example, Stern and Donald (1962) added N to
790
a grass and a clover growing with their roots separated. In this example the gradient is a resource,
791
N, but the competition is not for N, but for light (also a resource). The true distinction is between a
792
gradient in a factor for which there is competition and in a factor for which there is no competition.
793
But the factor for which there is competition will change. If soil nutrients or water are limiting
794
initially, and they are added, the limitation will be removed and competition will shift to being for
795
light (Tilman 1988). Moreover, the environmental conditions will then be so different that it will be
796
difficult to say whether competition is less, the same or greater (see The growth-rate artefact
797
below). Perhaps an even greater problem is that once competition is for light it will probably be
798
cumulative (chap. 2, sect. 2.3). Other complications are the change in species composition that will
799
occur along gradients and the lack of a generally-agreed index of competition. Most of the
800
confusion that has grown about this topic seems to come from ignoring what resource competition
801
is for.
802
The growth-rate artefact
803
A huge complication in experiments testing the Grime versus Tilman ideas on competition
804
is that if plants are put in a pot in a high-productivity environment the plants will by definition grow
805
faster, and thus come into competition sooner. Therefore, if competition is measured at a fixed time
806
after planting, it will appear to be greater in more productive conditions. The same situation occurs
807
after natural disturbance in a favourable environment. Eventually, competition will be 100 % right
808
along the gradient because the plants will grow until carrying capacity is reached and competition is
809
complete in the community-matrix sense: if x grams of plant material are removed growth will
810
resume until there are x grams more. Therefore competitive intensity cannot be measured as the
811
final outcome either. Competition is like death: it’s not a question of if, but of when. This problem
812
of the growth-rate artefact is removed when the experiment indicates lower competition at higher-
813
productivity conditions, but it is difficult to accept only results in one direction. Another
814
complication is that resources will be exhausted sooner when they are in shorter supply; resource
815
availability is not a fixed variate, but as always in communities is subject to reaction.
816
Our own hypothesis
817
818
Our own view, from first principles, is that along a beta-niche gradient (i.e. a gradient of
conditions, of non-resources, or of resources for which competition is not occurring), competition
Wilson and Agnew, chapter 6, Theories, page 27 of 43
819
will be of constant intensity, but will appear to be greater in more productive conditions because of
820
the growth-rate artefact.
821
Along an alpha-niche gradient (i.e. of a resource for which there is competition) competition
822
will be strongest when the resource is in shortest supply. There can be exceptions, e.g. the mobility
823
of some soil nutrients can be higher when they are present at higher concentrations and this can
824
result in greater below-ground competition (e.g. Vaidyanathan et al. 1968; J.B. Wilson and
825
Newman 1987). The same could apply to water. An additional complication is that as the
826
availability of resource X increases along a gradient, the plants may change from competing for X
827
to competing for resource Y.
828
Deserts
829
Ecologists often see what they think are exceptions to the universality of competition in
830
deserts, where the plants are spaced above-ground. The desert habitat is indeed stressful and if there
831
is competition it is likely to be for the same factor that causes the stress: water supply. Many, from
832
Shreve (1942) through Went (1955) to Mirkin (1994), have denied that desert plants compete. This
833
idea was fuelled by studies that failed to find a regular spatial pattern of individual plants in deserts,
834
and sometimes found clumping instead (e.g. Gulmon et al. 1979). The idea was often that plant
835
populations in deserts were kept below 100 % occupancy by unfavourable probabilities of
836
colonisation and death. We demolished this argument above, showing that there must be 100 %
837
competition, and if it is manifestly not above-ground it must be below-ground. The existence of
838
intense competition for water has been demonstrated by finding negative correlations between plant
839
sizes and distance apart (Yeaton and Cody 1976) and by relief of plant water stress and increase in
840
plant growth upon removing neighbours (Fonteyn and Mahal 1978; Robberecht, et al. 1983; Fowler
841
1986a; Kadmon and Shmida 1990). In fact, the effect of competition on plant spatial pattern has
842
been best demonstrated in desert communities. Ecologists have often underestimated the intensity
843
of competition where there seem to be unvegetated gaps between plants; in fact the cacti and shrubs
844
may be spaced out, but their root systems are not (Woodell et al. 1969). Clements knew this, of
845
course: “The open spacing of desert shrubs in particular suggests some indirect influence in
846
explanation, but studies of the root systems demonstrate that this is a result of competition for water
847
where the deficit is great” (Clements et al. 1929, p. 317). Remember our rider above on the spatial
848
mass effect. Remember our rider on herbivory, but it is a tenet of C-S-R theory that plants of
849
unproductive sites have more defences (Grime 2001). Disturbance would also override competition,
850
but is disturbance really so frequent in deserts that they are in a continually seral state? Anyway, it
851
is the basis of the C-S-R triangle that stress sites cannot have much disturbance, or no plants can
Wilson and Agnew, chapter 6, Theories, page 28 of 43
852
grow. We conclude that the intensity of competition is likely to be approximately 100 % in all
853
communities, supporting Tilman’s conclusion, perhaps for different reasons.
854
Tests
855
The complete absence of competition would be testable. However, we argue above that this
856
is not tenable, and moreover no habitat can fall exactly in the S corner so the question does not
857
arise. We have to test degrees of competition along an S–C gradient, which is possible but difficult.
858
The literature is unclear on how to measure the intensity of competition; we shall use a species’
859
percentage reduction from monoculture, ideally in RGR but sometimes in biomass.
860
Considering a gradient of environment conditions, La Peyre et al. (2001) grew three species
861
of salt/freshwater marshes in monoculture and competition along a salinity gradient. A measure of
862
the overall importance of competition was almost constant along the gradient, and once allowance
863
is made for dead material the competitive response of the individual species varied remarkably
864
little. Similarly, Cahill (1999) found no consistent change in aboveground competition in his
865
oldfield experiment between the two NPK levels. Although N, P and K are resources, in the latter
866
comparison there was competition only for light, so they are conditions. These two pieces of work
867
support our thesis that along a gradient of conditions, competition will be of constant intensity.
Wilson and Agnew, chapter 6, Theories, page 29 of 43
868
For a gradient in a resource for which competition is occurring, a relevant experiment is that
869
of Campbell and Grime (1992), growing seven species in outdoor plots with a range of nutrient
870
levels and disturbance regimes. Nutrients promoted growth considerably (Fig. 6.7a). Campbell and
871
Grime declare that Arrhenatherum elatius (oat grass) is a plant of fertile soils, and Festuca ovina,
872
Bromus erectus and Desmazeria rigida (fern grass) are plants of infertile soils, but actually the
10000
(a)
1000
Biomass (g m-2)
Arrhenatherum
Bromus
Dactylis
100
Desmazeria
Festuca
Lolium
Poa
10
1
0.001
0.01
0.1
1
10
Relative nutrient concentration
120
(b)
% reduction
by interference
Competive
suppression
100
Arrhenatherum
80
Bromus
Dactylis
60
Desmazeria
Festuca
Lolium
40
Poa
20
0
0.001
0.01
0.1
1
10
Relative nutrient concentration
Fig. 6.7: The effect of nutrient concentration on competitive ability.
873
nutrient response does not differ between species (p = 0.989 8). The species differ in the effect of
874
interference on them (Fig. 6.7b; p < 0.0019), but there is no overall effect of nutrient supply on the
875
intensity of interference (p = 0.072 10), disproving Grime’s assumption. Goldberg et al. (1999)
876
found in a meta-analysis that there was a tendency for competitive intensity to decrease more often
877
than increase with productivity, in general conformity with our theory and Peltzer and Wilson
878
(2001) found no significant trend with standing crop, used as an inverse proxy for stress. However,
Wilson and Agnew, chapter 6, Theories, page 30 of 43
879
the experiment of Campbell and Grime, as many of those surveyed by Goldberg, has the restriction
880
that it is not possible to tell whether competition was for the resource (NPK) that varied along the
881
gradient. This restricts very considerably the range of investigations available for critical tests.
882
The experiments of Peltzer et al. (1998) in Saskatchewan, Canada, and Cahill (1999) in
883
Pennsylvania, USA, were both in oldfields, planting seeds or seedlings into plots where shoot
884
competition was prevented by tying back the vegetation, root competition was either prevented or
885
allowed by using plastic tubes, and fertiliser was added or not (N in the case of Pelzer et al. and
886
NPK in the case of Cahill). Both studies showed somewhat greater belowground competitive effects
887
when soil resources were in shorter supply. This confirms the conclusion of J.B. Wilson (1988c),
888
surveying experiments on root competition, that the limited evidence available indicates that
889
competitive intensity is highest when soil resources are in shortest supply. In those experiments the
890
the gradient is one of soil nutrients and competition must be for either soil nutrients or water, but
891
generally it is not possible to see which. However, Cahill recorded soil moisture with gypsum
892
blocks, and found no significant difference between treatments, implying so far as one can from
893
non-significance that the competition was not for water. The study that comes closest to answering
894
the question is that of S.D. Wilson and Tilman (1991) at Cedar Creek, an experiment similar in
895
most respects to those of Peltzer et al. and Cahill. It is known from other work that nitrogen is the
896
limiting mineral nutrient in the oldfield at Cedar Creek and other nutrients were applied to all
897
treatments to make absolutely certain of this (right down to Cu, Co, Mn and Mo). Only N
898
(ammonium nitrate) differed between treatments. It therefore seems likely that we are looking at
899
competition for N along a gradient of N supply. Moreover, RGR is available to judge the result. In
900
all three species used the belowground competitive effect was greater at low soil N supply. An
901
experiment with one of the same species confirmed this (S.D. Wilson and Tilman 1993). The
902
overall evidence overwhelmingly supports our contention that competition for resource X will
903
generally be most severe when X is in shorter supply. It is surprising that anyone thought otherwise.
904
However, we must remember that in the real world soil nutrients are patchy (chap. 4, sect. 1.3).
905
We conclude that both Grime and Tilman were wrong. Along a gradient of an
906
environmental factor, or of a resource for which competition is not occurring, competition will be
907
equally intense right along the gradient. Along a gradient of a factor for which there is competition
908
the most severe competition will be at low levels of it. If the resource for which competition is
909
occurring changes, the question is too difficult to answer.
Wilson and Agnew, chapter 6, Theories, page 31 of 43
910
9 Synthesis
911
9.1 “Too soon to tell”
912
Plants are simple to physiological ecologists, operating not so far above the level of physics.
913
Even so, they have found it hard to produce general theories, except that of adaptation which is
914
dangerous if applied uncritically (Gould and Lewontin 1979). Population ecologists, working at the
915
level below community ecology, can see clear patterns such as a logarithmic decline when death
916
rates are constant (Harper 1967), but their main principle seems to be density-dependence, which
917
we argued above is logically an almost necessary feature of a persisting population. In ecosystem
918
ecology, at the level above community ecology, it is possible to see some patterns imposed by the
919
laws of conservation of matter and of energy. We community ecologists are in the worst situation.
920
Theories fail. Generalising from first principles and seeking hard evidence the best evidence we
921
have is for the Botany Lawn, and though it seems clear that assembly rules are operating we do not
922
know how, or even whether they are based on aboveground or belowground plant interactions. As
923
Mao Zee Tzung is claimed to have said when asked what the effect of the French Revolution had
924
been on subsequent history: “It is too soon to tell”. Theories of communities are certainly at too
925
early a phase to be applied to practical problems. The dangers of doing this are exemplified by
926
attempts to apply ‘Island Biogeography’ theory to reserve design.
927
9.2 “Does vegetation suit our models?”
928
None of the models of plant communities yet produced have high synthetic or predictive
929
value. We deeply respect Frederick E. Clements’ field knowledge of vegetation, his powers of
930
observation and generalisation and his pioneering experimental work. All of his concepts contain a
931
good deal of truth. Since the same community rarely recurs (J.B. Wilson et al. 1996b) his
932
formations and associations are simplifications, but similar classification continues today. It does
933
little harm when it is admitted that the main purpose of the ‘associations’ is to identify conservation
934
targets to the public and to government. We dedicate this book to Clements’ for his insights.
935
Variation along environmental gradients is sometimes continuous, but at other times
936
discontinuous due to the operation of a switch, as both Clements and Gleason believed. This is true
937
even of many boundaries that ecologists categorise as ‘environmental’ such as between a
938
saltmeadow and a saltpan, or a riverbank. The rôle of switches in generating the spatial patterns
939
around us has been considerably underestimated. The methods of Mike Austin and co-workers
940
(section 4) indicate continuous variation along environmental gradients, but this is partly because
941
they have worked at a larger spatial extent than that on which most switches occur. Nevertheless,
942
there is increasing interest in geographic-scale switches, especially those involved with climatic
943
change (chap. 3, sect. 5.4.A).
Wilson and Agnew, chapter 6, Theories, page 32 of 43
944
Philip Grime’s C-S-R is the only modern, overall theory of plant communities. It matches
945
the current interest in guilds, often under the name ‘plant functional types’ (chap. 1, sect. 4.2), and
946
usefully it does so using continuous axes, not discrete types. Both C-S-R theory and intrinsic guilds
947
avoid the ad-hoc guilds commonly used, but in opposite ways. Intrinsic guilds are defined in each
948
study with no pre-conceptions, discovering the structure from the community itself. C-S-R, in
949
contrast, has an a-priori triangle derived from field and experimental experience and with
950
theoretical underpinnings from r-K theory and from leaf ammortisation theory; this is used as a
951
template for understanding all vegetation. C-S-R is a useful and stimulating generalisation and it
952
has spurred the collection of an excellent database of plant ecological characters. Other datasets
953
should aspire to this quality. Tilman’s concept that competition will be equal along a productivity
954
gradient is close to the truth, but his R* approach seems to be too simplistic for embryophytes.
955
Plant ecologists tend to produce models and then try to make the facts fit. Anna Bio (2000)
956
neatly criticised this as, “Does vegetation suit our models?”. The nature of the community depends
957
on the nature of its parts and the starting point must be the peculiar characteristics of plants (chap. 1,
958
sect. 1.1): they do not consistently have ‘individuals’, they are colonies of modules moving through
959
space (“Plants move, animals don’t”). Litter forms an extended phenotype around plants that moves
960
with them. Its effects persists after them, and can have lasting effects if there is a switch operating.
961
The effect of plants does not die when they die. The species therefore plays the part of an individual
962
in the community. Its rôle depends on its shape and secondarily on its physiology and chemistry. Its
963
reaction on the environment and on associated biota flows from these. These characteristics of
964
plants produce a range of interactions within and between species (Box 6.1), many of which are
965
rarely considered in a community context. All this will make it difficult for vegetation to suit our
966
simple models.
Wilson and Agnew, chapter 6, Theories, page 33 of 43
967
968
Box 6.1: Types of interaction between plants.
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
At the species (or within-species) level
negative effects
interference (negative effects via reaction)
competition: species X removes resources from the environment, which are then
unavailable to species Y
allelopathy: X produces a substance toxic to Y
spectral interference: X changes the red/far-red balance, disadvantaging Y
switch: X causes reaction in an environmental factor, disadvantaging Y
negative litter effects: X produces litter of a type that disadvantages Y (positive
effects are a type of subvention)
parasitism: X removes resources directly from Y
autogenic disturbance: X disturbs, disadvantaging Y
negative effects via heterotrophs: X changes the heterotroph population, disadvantaging
Y
Subvention (positive effects)
mutualism = X and Y both benefit relative to their being at the same density on their
own
benefaction = X benefits Y as above, with no known advantage/disadvantage to itself
facilitation = X benefits Y, to its disadvantage
988
989
990
991
992
993
At the community level
guild/community X gives a relative disadvantage to itself:
the effect is density-independent: facilitation and/or autointerference = relay floristics
the effect disappears at low density of X (negative feedback) = stability
guild/community X gives a relative advantage to itself = switch
994
A few of the interactions between plants are direct. Parasites and strangling lianes are
995
examples, as are the fascinating and understudied effects of shaking and physical abrasion (chap. 2,
996
sect. 6.1). Interactions via herbivores, fungi and microbes are more important. Parasitism is well
997
known, and we are afraid we have tended to ignore it as a special case, and shall do below.
998
However, the most important types of interaction are via the environment, i.e. reaction. In the short
999
term this effects most types of interference and subvention. Competition is often spoken of as if it
1000
were the only negative interaction between plants, but in fact it is one of many, modified by
1001
subvention. Longer-term and often stronger reaction results in either community change, most
1002
likely via relay floristics or reinforcement of the current state via a switch (Box 6.1). The “or” is a
1003
simplification since an accelerating or delaying switch can operate during relay floristics. Cyclic
1004
succession is really a third type (Fig. 3.1); there is very rarely good evidence for it (chap. 3, sect. 4),
1005
but there is only marginally more for relay floristics or switches. It seemed necessary to divide
1006
subvention by whether the effects were reciprocal. However, we could also divide subvention by its
1007
cause, notably reaction versus interactions via heterotrophs.
1008
1009
Reaction is the plant community, in that almost alone it causes the community processes:
relay floristics, cyclic succession and switches. Without reaction there will be only a collection of
Wilson and Agnew, chapter 6, Theories, page 34 of 43
1010
plants. The combination of these processes does not give a neat pattern (Fig. 3.10) nor does it make
1011
it easy to use neat labels. However, one clear conclusion is that whenever ecologists see a sharp
1012
boundary in nature without an obvious environmental or historical cause, they should suspect that a
1013
switch is operating.
1014
Three things are clear about plant communities: (1) almost all comprise many species,
1015
(2) they are heterogeneous and (3) ecologists must hope there are some rules governing the
1016
assembly of species in them – assembly rules – or there is no science in plant community science.
1017
9.3 The ‘Paradox of the plankton’
1018
The 12 mechanisms that could be permitting species to coexist are now clear (chapter 4), but
1019
evidence of their relative importance is sparse. The lack of evidence on Initial Patch Composition
1020
(7) and Co-Evolution of Similar Interference Ability (12) probably reflects their lack of realism.
1021
However, experiments on each would be possible. The existence of Equal Chance (9) is very
1022
unlikely, and chance is impossible to prove, but evidence for plants as good as that Munday (2004)
1023
was able to obtain for fish would be fascinating. The evidence (chap. 4, sect. 4) on Circular
1024
Interference Networks (4) suggests that the mechanism is likely to be unimportant, or non-existent.
1025
However, better-quality evidence is needed, examining how RGR changes as exclusion by
1026
interference is approached and using the species of a natural community. Evidence for Cyclic
1027
Succession (8) is currently absent. Since Egler’s (1977) diatribe there have been many more
1028
permanent plots set up and these may eventually give evidence for or against it. Temporal and
1029
Spatial Inertia (10) and Interference/Dispersal Tradeoffs (6) are probably all around us, but there is
1030
miniscule evidence for either. Temporal inertia (11.1) is hard to measure, but evidence may come
1031
when a change of environment affects a permanent plot, or that change could be imposed
1032
experimentally. Stoll and Prati (2001) gave neat evidence of spatial inertia (11.2) from a very
1033
artificial system, and evidence from more realistic systems would be useful. However, this is only
1034
an equalising mechanism. Ecologists rarely have any idea how much of the small-scale patchiness
1035
that they see around them is due to Allogenic Disturbance (5), but the research would not be too
1036
hard, with permanent plots in herbaceous communities and using dendrochronology as well as
1037
permanent plots in forests. The main problem in measuring the Spatial Mass Effect (10) is that the
1038
tail of leptokurtic dispersal is hard to quantify. The answer may lie in experiments with adjacent
1039
mesocosms, or mesocosms transplanted into the field as phytometers, but for measuring dispersal
1040
and ecesis, not the environment. We can put together a story on Pest Pressure (3) from separate
1041
pieces of work (chap. 4, sect. 3), at least for pathogens, but more work on applying pesticides to
1042
natural communities would be valuable, with examination of all the processes in a single system to
1043
aid interpretation through the nexus of interactions involved. Allogenic changes imply that
Wilson and Agnew, chapter 6, Theories, page 35 of 43
1044
Environmental Fluctuation (2) has huge impacts on plant communities (chap. 3, sect. 2), but it will
1045
not always meet the strict criteria for permitting coexistence. When data are to hand to parameterise
1046
the models of Chesson (2006) it should be possible to understand this better. How much of the
1047
Alpha-niche Differentiation (1) that can be seen around us is actually causing coexistence is hard to
1048
know. Experiments with treatments preventing niche differentiation would be useful, e.g. using
1049
shallow boxes to prevent differences in rooting depth or long-term growth-cabinet work with and
1050
without seasonal differences.
1051
All these effects have been demonstrated, if at all, in separate studies. The next step is for
1052
them all to be evaluated for one community.
1053
9.4 Heterogeneity
1054
Environments are (almost?) always heterogeneous in space and time, even in apparently
1055
uniform natural communities (e.g. Robertson et al. 1988; Farley and Fitter 1999). The base for
1056
modelling this can be either environmental heterogeneity or environmental homogeneity.
1057
The usual starting point has been underlying spatial heterogeneity, and indeed it is very hard
1058
to escape from such variation. Deserts appear uniform, but have damper depressions and even
1059
dunes. Alluvial flood plains are deceptively homogenous because they receive non-uniform deposits
1060
as rivers meander and even split/rejoin. The deposits are reworked by the original river and then, as
1061
the river cuts lower, by smaller streams. The same is true on saltmarshes. This can be combined
1062
with the certainty that there are differences between species in their environmental tolerances,
1063
which can be determined by experiments and/or inferred from plant/environment distributions (the
1064
“easy task” of Warming 1909). This gives a base model in which environmental heterogeneity
1065
combined with different species tolerances causes community heterogeneity. This is allogenic
1066
heterogeneity. All further investigation of community processes has to sample where allogenic
1067
heterogeneity is minimal and/or allow for it (e.g. in patch models: chap. 5, sect. 2.3).
1068
Alternatively, heterogeneity in vegetation can be explained with a null model of a uniform
1069
underlying environment. ‘Random’ dispersal of species then has to be assumed to give some
1070
pattern. Too little inward dispersal would leave unvegetated gaps and too much would give cover
1071
too uniform to explain the observed heterogeneity, so infiltration invasion must be assumed (chap.
1072
1, sect. 2.3), which conveniently seems to be the norm. The next assumption must be that those
1073
colonists react on their environment, and we gave plenty evidence for this when discussing switches
1074
(chap. 3, sect. 5). Next, species must differ in their reaction. If that reaction is in a direction that
1075
disfavours the present species, the result would be relay floristics with a single homogenous
1076
endpoint (Clements 1916), or just possibly cyclic succession. However, often the reaction of the
1077
species will be in the direction that favours their good selves, giving a switch. If the switch is of
Wilson and Agnew, chapter 6, Theories, page 36 of 43
1078
Types 2-4 the result can be a stable mosaic of different communities. Tree islands in the low alpine
1079
are a very visible example, though the mosaic there is often permanent but shifting (J.B. Wilson and
1080
Agnew 1992). The assumptions under this model are that community heterogeneity is generated by
1081
infiltration invasion and switches, i.e. autogenic heterogeneity. The creation of autogenic
1082
heterogeneity reaches its full development when a switch produces a mosaic of alternative stable
1083
states (chap. 3, sect. 5.6), situations that we believe are more common than has been realised,
1084
although the evidence for them is much more uncommon than has been realised. Care is needed,
1085
though, because most of the switches seem to be one-sided (Type 1) which cannot give rise to a
1086
permanent mosaic (chap. 3, sect. 5.3).
1087
The greatest knowledge gap is the degree to which the species of one pool differ in their
1088
reaction. Effects can readily be seen in the light regime beneath different species, though still much
1089
more is known of species differences in total light transmittance than of changes in spectral
1090
composition. Soil reactions occur much more slowly. It is clear that a few species, such as Calluna
1091
vulgaris (heather) and Sphagnum spp. mosses, differ strongly from their neighbours in their
1092
reactions on pH. Whether differences in reaction are general and especially whether there are
1093
changes in other soil variates is remarkably unknown. Local soil/species correlations can easily be
1094
seen, but distinguishing cause from effect is difficult (but see Pelletier et al. 1999; Ehrenfeld et al.
1095
2001; chap. 4, sect. 1.3 above). Experiments with soil litter bags normally last 2-5 years, rather than
1096
the 50 years that would usually be needed to see the effects, and they usually examine the litter, not
1097
the nearby soil. However, we believe that reaction of plants and litter on the soil environment has
1098
been underestimated as the cause of heterogeneity and we call for people to investigate it. The
1099
urgent need is for documentation of all the steps of a switch from a single system. We commented
1100
(J.B. Wilson and Agnew 1992) that there was then no case where this had been done. Although
1101
further work has been done on switches as those involving goose-grazing / saltmarsh (chap. 3, sect.
1102
5.6), microscopic algae / sediment stability (chap. 3, sect. 5.4.C) and lake turbidity one (chap. 3,
1103
sect. 5.4.E), this remains essentially the situation.
1104
Almost certainly the processes assumed in both the heterogeneity and the homogeneity
1105
starting-point models occur, and do so simultaneously. Yet spatial analysis tends to be rather
1106
uninformative. The reader will have noticed that we have largely ignored species-area curves. This
1107
was not because we forgot about them, but because they seem to shed little light on the structure of
1108
communities, tending to be indirect ways of describing geography. Goodall (1954) argued that if a
1109
community has real existence it should show homogeneity of composition within its boundaries.
1110
This is an interesting, even provocative, challenge. Similar is Whittaker’s idea that his ‘gradient
1111
analysis’ (Fig. 6.1) could identify ‘integrated’ communities. These approaches fail. The existence of
1112
small-scale heterogeneity does not disprove integrated structure, for there is certainly underlying
Wilson and Agnew, chapter 6, Theories, page 37 of 43
1113
environmental variation which any community structure, however strong, could surely not
1114
extinguish. F.E. Clements who wrote “the community is a complex organism … greater than the
1115
sum of its constituent species” (Clements 1935) but also “Practically all vegetation shows more or
1116
less striking differences every few feet” (Weaver and Clements 1929, 6). Neither do sharp
1117
boundaries prove co-evolution; they could well be caused by switches, as supposed by both
1118
Clements and Gleason (section 3 above). On the other hand, continuous variation could represent
1119
strong structure, derived from co-evolution towards coevolution, as it did in Whittaker’s fairy
1120
stories (section 4 above).
1121
9.5 Assembly rules
1122
At one point within this heterogeneity there can be either a stable community (but of course
1123
with continual allogenic change), an alternative stable state, or a seral stage of directional or cyclic
1124
succession (chapter 3). However, our discussion would be little more than natural history were there
1125
not some regularities, or rules, that could be seen in how the states are assembled. Assembly rules
1126
are similar to alternative stable states in that from a pool of species only some combinations are
1127
stable. Alternative stable states are necessarily produced by switches. A switch generally depends
1128
on a considerable degree of reaction, sufficient to make a state stable in the face of all but the more
1129
extreme environmental variation, but it could depend on interactions via heterotrophs or, in theory,
1130
autogenic disturbance (chapter 2). Assembly rules are also caused by reaction, though they can be
1131
much more subtle ones, and small-scale interactions via heterotrophs or autogenic disturbance
1132
cannot be ruled out as the mechanism. Alternative stable states are usually envisaged to exist either
1133
at different times or in different places over scales of hundreds of metres or more. Assembly rules
1134
are envisaged at a small, within-community scale, but this difference cannot be absolute:
1135
Diamond’s (1975) original assembly rules operated between islands up to 1000 km apart. Because
1136
of the difference in scale, instantaneous interactions, such as via light, are quite likely to be causes
1137
of assembly rules, whereas gross changes in soil composition are likely effectors for alternative
1138
stable states. The scope for assembly rules is wider, for example, specifying a relative abundance
1139
distribution (RAD) without specifying the species involved, or specifying guild proportions whilst
1140
leaving open which species of a guild are represented, whereas there will be a limited number of
1141
specified alternative stable states, often only two, each with its own set of environmental conditions
1142
and species.
1143
We ecologists have to be very careful in examining apparent evidence for assembly rules;
1144
there are many traps for the unwary null modeller. Nevertheless, there is overwhelming evidence
1145
that assembly rules do exist (chap. 5), refuting claims to the contrary by Hubbell (2005) and Grime
1146
(2006). The best evidence for assembly rules is from character-based rules. There is a trend in plant
Wilson and Agnew, chapter 6, Theories, page 38 of 43
1147
community ecology towards analysing plant communities not by the names of their species but by
1148
the characters of the plants. The beginnings of this awareness of characters at the community level
1149
are in Jan Barkman’s (1979) concept of vegetation texture. Amongst character-based assembly
1150
rules, some distributional evidence supports guild proportionality, as does the successional study of
1151
Fukami et al. (2005). There is little support from removal experiments, probably because of high
1152
experimental error. The use of a priori guilds has severe limitations and we strongly advocate
1153
seeking intrinsic guilds. The use of texture instead of discrete guilds avoids classification, but does
1154
not avoid the problem of character choice. Methods for the determination of intrinsic texture, i.e.
1155
determining the characters of the species to use by the properties of the communities, remain to be
1156
developed.
1157
The evidence for assembly rules so far comes mainly from herbaceous communities, and the
1158
only comprehensive body of evidence is from the University of Otago Botany Lawn. We would be
1159
cautious about the demonstration of an assembly rule in any single study, but the coherent
1160
conclusions from this site are compelling. The evidence from this and other sites suggests that
1161
canopy relations are important, even in the shortest communities such as lawns, saltmarshes and
1162
sand dunes. This may be partly because of the types of communities that have been examined so
1163
far. It may also reflect a bias towards easily-measured characters, since when Stubbs and Wilson
1164
(2004) utilised wider range of characters in a sand dune community the results implied community
1165
structuring by mode of foraging for water and soil nutrients. The evidence on even-spacing of
1166
flowering implies that phenological niche differentiation is important in restricting species assembly
1167
too, though great care is needed in examining that evidence. However, the failure of roadside
1168
communities to re-assemble in New Zealand (J.B. Wilson et al. 2000b) indicates that the restrictions
1169
on community assembly rules are often weak, and probably that alternative stable states exist (chap.
1170
3, sect. 5.6).
1171
It is difficult to search for assembly rules without knowing what the rules are especially
1172
when it is so easy to get negative or invalid results, for example by not using a patch model. But
1173
how can ecologists claim to understand plant communities when they do not know what restrictions
1174
there are on species coexistence, when they occur and where? The future probably lies with
1175
character-based assembly rules, but they must be characters that are carefully selected, not those
1176
that happen to be to hand or are easy to measure, and the selection should be towards characters
1177
likely to reflect the alpha niche. The other urgent need in plant assembly rules research is to
1178
understand how any particular rule operates, i.e. what reaction in what environmental factor or
1179
resource is caused by each species that limits the ways others associate with it. Alternatively, the
1180
assembly rules may be caused by autogenic disturbance, interactions via heterotrophs, etc. Many
1181
types of autogenic disturbance have been demonstrated, but for few is there evidence as to how
Wilson and Agnew, chapter 6, Theories, page 39 of 43
1182
frequent they are within and among plant communities. Interactions via heterotrophs are very likely
1183
to cause limitations to community assembly – assembly rules – but the evidence is frustratingly
1184
sparse. There are a few experiments on the effects of applying insecticide or fungicide at the
1185
community level. More are needed. Many simply report the effect on species diversity. Careful
1186
examination is needed of the cascade of effects that are caused and their rôle in assembly rules. This
1187
mechanism of plant-plant interaction has been widely mentioned for companion planting, but we
1188
found searches of the scientific literature for evidence almost fruitless.
1189
These assembly rules are based on mechanisms, but the net result is efficiently summarised
1190
in the Community Matrix. Introduced to ecology by May (1972), it was not until c. years later that
1191
anyone bothered obtaining values for a real plant community and comparing that community with
1192
the predictions of the Matrix (Roxburgh and Wilson (2000a, b). A Community Matrix is necessarily
1193
a true description of a community, but only one at an equilibrium and perturbed a very small
1194
amount. More realistic models are needed, parameterised from real communities.
1195
Any assembly rules could be based on either co-evolution or pre-adaptation. Dice (1952)
1196
and Whittaker (1975b) were convinced about co-evolution. One of the strongest advocates of this
1197
was Goodall (1963), who argued that a group of species that grew together in common types of site
1198
would adapt to those site conditions and to each other by “… positive feedback. In this sense the
1199
plant community may sometimes be said with justice to have evolved as a whole”. We believe that
1200
co-evolution between plant species is unlikely, even at the ecotypic level.
1201
One problem is temporal change. The environment and the species pool both change and
1202
equilibrium in a plant community is rare. This would not matter if groups of species moved around
1203
the landscape together, but the pollen record tells us clearly that they have associated in different
1204
ways during this interglacial, and probably in earlier ones (chap. 5, sect. 9). Neither do species
1205
associations stay together on much finer timescales. For example, in Watt’s (1981) records from
1206
Breckland, Erigeron acer (fleabane) first increased with Thymus polytrichus, (= T. drucei, thyme)
1207
then stayed essentially constant as T. polytrichus increased, then decreased as T. polytrichus stayed
1208
constant. Much more analysis of local time/space relations like this is needed.
Wilson and Agnew, chapter 6, Theories, page 40 of 43
Fig. 6.8: Trends in the shoot frequency of Erigeron acer and Thymus polytrichus (= T. drucei, thyme)
in a 10 × 160 cm plot in the Breckland, eastern England. From Watt (1981).
1209
1210
Another problem for a co-evolution explanation is spatial change. Since environmental
1211
heterogeneity exists right down to the smallest scales, it is not predictable even within a community
1212
which species a plant will have as a neighbour. Part of this heterogeneity is caused by the reaction
1213
of one plant affecting another: effects between different species, between ramets of the same
1214
species and between modules of the same ramet. The species cannot co-evolve to match all these
1215
different assemblages. An even greater spatial problem is that species normally occur in several
1216
communities and the characters of a whole species cannot co-evolve to be optimal in each (Gleason
1217
1926; Goodall 1966).
1218
Furthermore, we argued in chapter 1 that evolutionary change in plants is often slow. All
1219
this makes co-evolution of species traits impossible in heterogeneous communities, and hardly
1220
likely even within homogenous ones if they existed. Therefore, when assembly rules are found, they
1221
are likely to be due to the assembly of preadapted species, that happen from their evolutionary
1222
history in a variety of contexts to have the right characters for the job. Preadaptation is the key to
1223
community ecology.
1224
9.6 Conclusions
1225
We have emphasised the wide variety of plant-plant interactions that occur. The majority
1226
operate through reaction, including interactions via litter, though others operate via autogenic
1227
disturbance, heterotrophs, or occasionally parasitism. There are many gaps in our knowledge of
1228
these interactions, but the most pressing need is for integrated knowledge of them for even one
1229
community. Reaction must always be present and if it be towards favouring the plants that caused it,
1230
a switch will operate. We see the switch as the supreme process in plant communities. Switches are
1231
not ubiquitous, but they are the necessary cause of persistent autogenic heterogeneity, i.e. of
1232
alternative stable states (ASS). They are also the cause of the more interesting aspects of relay-
Wilson and Agnew, chapter 6, Theories, page 41 of 43
1233
floristics succession, viz., delay and acceleration, as well as the alternative pathways that lead to
1234
ASS.
1235
As plant ecology moves beyond Warming’s “easy task” of describing those plant
1236
distributions caused by allogenic heterogeneity, beyond indirect analysis of those descriptions by
1237
tools such as species-area curves and beyond describing succession as a gradient in time, switches
1238
are the key. They are at the heart of both spatial and temporal heterogeneity, which are the primary
1239
objects of plant community study. Erwin Adema, working in Dutch slacks, produced evidence that
1240
a switch was causing ASS, perhaps the best of all terrestrial examples (chap. 3, sect. 5.6), but he has
1241
remained modest about it. Many workers have seen ASS as being common. They may be, but
1242
unless we are credulous the hard evidence for them is vanishingly small (chap. 3, sect. 5.6; Wilson
1243
et al. in press). Elsewhere in the literature there has been hand-waving about alternative stable states
1244
and diagrams of hysteresis, with minimal consideration of mechanism. Sometimes it has not even
1245
been realised that ASS must be caused by a switch (e.g. Lortie et al. 2004). Often the switch process
1246
envisaged to cause ASS/hysteresis has not been specified, still less has evidence for its operation
1247
been produced. This is especially important because superficially observed ASS and hysteresis
1248
could be due simply to temporal inertia, to plants taking their time about dying. Thus, whilst we
1249
suggest that the importance of switches has been considerably under-estimated, we must also point
1250
out that for almost every example of a possible switch more data are needed before it can be
1251
demonstrated to be operating.
1252
Essentially the same processes, dominated by reaction, operate on a smaller scale with pre-
1253
adapted species as their pawns to give assembly rules. ‘Assembly rules’ was coined by Diamond
1254
(1975), but the concept was implicit in the theoretical work of MacArthur (e.g. MacArthur and
1255
Levins 1967). MacArthur’s assembly-rule concept of limiting similarity appears in every textbook,
1256
yet theory and reality existed in parallel, not touching each other, for c. 20 years before the first
1257
rigorous demonstrations. There have been interesting tests of the limiting similarity concept using
1258
flowering phenology (chap. 5, sect. 6.2), though these studies have many problems. The first
1259
rigorous test with plant functional characters was that of Stubbs and Wilson (2004). Again, the need
1260
is to bring theory and reality together, and to test for several aspects of the structure of one
1261
community, as we have for the Botany Lawn. However, great care is needed with the methods used.
1262
Too often, workers have performed some randomisation, found a difference between the observed
1263
pattern and the randomised one, and declared an assembly rule. Fox’s assembly rule for desert
1264
rodents is a notorious example (Wilson 1995; Simberloff et al. 1999). In order to test for an
1265
assembly rule, one also has to know for which rule one is testing (i.e. the test statistic) and the rule
1266
should be one based on the ways plants function and interact (chaps. 1, 2). It is becoming clear that
1267
the rule should probably be based on plant characters and ideally on abundance too. However,
Wilson and Agnew, chapter 6, Theories, page 42 of 43
1268
which characters are critical in causing assembly rules is hardly ever known. We have pioneered
1269
determination of intrinsic guilds from distributional and experimental data as a route to more
1270
appropriate assembly rules, but the characters and thus the processes behind the intrinsic guilds are
1271
yet to be discovered. Methods for determining intrinsic texture have yet to be found, for weighting
1272
the characters of the species by information obtained from the structure of the community itself.
1273
Thus, we emphasise reaction, alternative stable states, switches and assembly-rules, and the
1274
need to obtain hard evidence for them all, bridging the gap that has existed in community ecology
1275
between theory and reality.
1276
ILLUSTRATIONS
1277
Fig. 6.1: The distribution of species along an environmental gradient: (a) a simplistic version of
1278
Clements, (b) a simplistic version of Gleason, and (c) Whittaker (who needs no
1279
simplification).
1280
Fig. 6.2. Does the same community recur? Comparison of between-site similarities in species
1281
composition with: (a) those between adjacent quadrats, and (b) those between subsites 50 m
1282
apart. From Wilson et al. (1996b).
1283
Fig. 6.3: The C-S-R triangle of Grime (1979).
1284
Fig. 6.5. Fig. 6.4. C-S-R theory and specialist pioneers. Grime suggested that sites with differing
1285
degrees of stress would follow different pathways. - - - indicates the part of the succession
1286
which will probably be slow.
1287
Fig. 6.6: The experimental response to N compared to the rank of species in a successional/N field
1288
gradient.
1289
Fig. 6.7: The effect of nutrient concentration on competitive ability.
1290
Fig. 6.8: Trends in the shoot frequency of Erigeron acer and Thymus polytrichus (= T. drucei,
1291
thyme) in a 10 × 160 cm plot in the Breckland, eastern England. From Watt (1981).
1
It has to be said that flaws in Whittaker’s methods leave those results in doubt (J.B. Wilson et al.
2004)
2
This can be distinguished from the redundancy concept, where the species are equivalent in alpha
niche but not in beta niche.
3
by space-for-time substitution
4
Spearman’s rank correlation rs = -0.45, with RGR taken from the graphs of Tilman and Cowan
(1989) at 150 mg N / kg of soil
5
rs = -0.24, RGR at 1500 mg N
6
rs = +0.84, p < 0.05
Wilson and Agnew, chapter 6, Theories, page 43 of 43
7
The timing is difficult to establish since the evidence is naturally from sites of different
successional age that differ also in factors such as initial substrate and altitude.
8
test for heterogeneity of slopes on a log-log basis
9
by analysis of covariance, with log of nutrient concentration as the independent variate
10
for a joint residual regressio006E