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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 ........................................................................................................................ 8
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? ....................................................................... 15
6.7 Conclusions ...................................................................................................................... 17
Tilman’s theory ............................................................................................................................ 17
7.1 The competitive process: R* ............................................................................................ 18
7.2 Succession ........................................................................................................................ 21
7.3 Conclusion ....................................................................................................................... 22
Grime versus Tilman .................................................................................................................... 22
8.1 Strategy ............................................................................................................................ 23
8.2 Species diversity............................................................................................................... 23
8.3 Competition ...................................................................................................................... 24
Synthesis ...................................................................................................................................... 30
9.1 “Too soon to tell” ............................................................................................................. 30
9.2 “Does vegetation suit our models?” ................................................................................. 30
9.3 The ‘Paradox of the plankton’.......................................................................................... 33
9.4 Heterogeneity ................................................................................................................... 34
9.5 Assembly rules ................................................................................................................. 36
9.6 Conclusions ...................................................................................................................... 39
1 Theories
It is our intention here to critically review the available general theories of plant ecological
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behaviour and eventually to relate them to our view of plant life. Our aim is to generalise over all
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plant communities, aquatic as well as terrestrial, although we mostly have embryophytes in mind.
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We start with certain definitions. The first distinction is 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 41
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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)
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(b)
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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 41
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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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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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These are the overall patterns, with their causal mechanisms of community assembly. In the first
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part of this chapter we consider theories that have an overview of the topic of our book. However,
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theoreticians have varied in the degree to which they have addressed interactions (chapter 2),
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community processes (chapter 3), coexistence mechanisms (chapter 4) and pattern/assembly
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(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 41
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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: "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 41
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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 41
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 pattern/structure views of Clements (1916) and he
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later declared, provocatively, that a stand of vegetation is a “temporary and fluctuating
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phenomenon” (Gleason 1939). Clements et al. (1929, 315) in return wrote that Gleason’s concept
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“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
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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 others 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). From his 'Gradient Analysis'
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results Whittaker (1967) concluded that vegetational change along environmental gradients was a
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continuum1. This is not the concept of Gleason, who wrote: “The adjacent associations … meet
Wilson and Agnew, chapter 6, Theories, page 8 of 41
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with a narrow transition zone, even though the variation in physical environment from one to the
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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). This begs the question of
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what the environmental gradients are and how they are measured. If, as usual, the gradients are
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calculated from geographical trends in environment (e.g. Leathwick and Austin 2001) there will
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certainly be sudden change 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.
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5 Hubbell and chance
A rôle has often been proposed for stochasticity / chance / random-effects / disorderliness in
the construction of plant communities (e.g. Lippmaa 1939; Richards 1963; Fowler 1990; Sykes et
Wilson and Agnew, chapter 6, Theories, page 9 of 41
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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’ at the beginning of this chapter. However, chance does not really exist
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(cf. chapter 4). Seeds are sometimes said to disperse randomly, but in fact they disperse under the
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laws of physics, it is just that eddy diffusion is very complicated. Everything happens under the law
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of physics (except arguably the resurrection of the Our Lord Jesus Christ: J.B. Wilson 2002), and
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above the scale of the atom chance plays no part.
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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 tropic 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
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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
Wilson and Agnew, chapter 6, Theories, page 10 of 41
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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.
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).
C (competition)
Disturba
nce
(ruderal) R
(disturbance) D
C-S-R
K
r
S (stress)
Untenable
triangle
Productivit
Disturbanc
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airport, main
runway
Fig. 6.3: The C-S-R triangle of Grime (1979).
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Productivity
Wilson and Agnew, chapter 6, Theories, page 11 of 41
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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-
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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
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under stress before, when they were growing to their hearts' content, but that they are not under
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stress now that they are dead? There may be more to their death than interference: some alpine
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species grow poorly in ‘low-stress’ sea level conditions, probably because they lose carbohydrate in
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the warmer winter temperatures there (Stewart and Bannister 1973). One would think that the
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phytometer approach of Clements and Goldsmith (1924) would be ideal: planting the same species
352
into a range of communities and measuring its growth. However, Grime has chosen to define stress
353
on a whole-community basis and on the basis of the plants presently occurring, and is clear and
354
consistent in that.
Wilson and Agnew, chapter 6, Theories, page 12 of 41
355
Perhaps the most difficult habitat for C-S-R theory is forests. The dominant trees of tropical
356
rainforests might be seen as the ultimate competitors, but Hubbell (2005) described them as the
357
“competitive (stress tolerator) functional group”, with characteristics typical of S species: tolerance
358
of low light levels (as juveniles), long life spans, high resistance to pests and herbivores. This rather
359
depends on how the dominants regenerate. If they grow fast from seed or from suppressed seedlings
360
after disturbance they could be C species, almost R. Others have seen the dominants as species that
361
are shade tolerant and grow slowly up through the canopy, or sit still “conservatively” tolerating the
362
stress of shade and make bursts of growth during temporary gaps, in which case they are S species
363
as juveniles, though not as adults. Indeed, the understorey plants of evergreen forests tend to be
364
slow-growing evergreens, S species (Grime pers. comm.). Then again, trenching experiments have
365
shown that competition for nutrients is often more limiting than light to herbs and seedlings on the
366
forest floor (Coomes and Grubb 2000).
367
It is very difficult to characterise a whole site as low/high stress in terms of light, since in a
368
productive environment there will always be some species low in the canopy that have to tolerate
369
the stress of shade from taller plants (Pigott 1980). Grime had envisaged that any community would
370
comprise a mixture of species with different C-S-R status, but in this case it is not just a case of the
371
overlap of species' ecological ranges, or of micro-habitat variation, because, as Pigott notes, the
372
species "grow together in vegetation ... because they possess different strategies" [italics ours].
373
Since the r-K spectrum is widely accepted, the controversial aspect of C-S-R theory is that
374
different kinds of stress have much in common, resulting in a consistent S-species type. Such
375
species grow slowly, at least in their natural habitat. Leaves can therefore be produced only
376
infrequently, so they must function for more than a year. This results in a whole suite of leaf
377
characters, e.g. evergreen, low maximum photosynthetic rate, low percentage nitrogen, abundant
378
defence compounds, small, often stiff and tough, needle-like and with high SLW (Reich et al. 1991;
379
1992). This suite of S characters is also part of leaf costs / amortisation theory of Orians and Solbrig
380
(1977), indeed we can see the relation: C-S-R = r/K theory + Leaf Amortization theory (J.B. Wilson
381
and Lee 2000). Since the original formulation of C-S-R, Grime (1988; 2001) has concluded that the
382
common underlying stress is a deficit of major mineral nutrients either directly or as a result of
383
other stresses. This view is comparable to that of some physiologists, who have proposed a unifying
384
stress mechanism (see J.B. Wilson and Lee 2000). Craine (2005) considers this at least unproven.
385
It has sometimes been suggested that low RGRmax is directly adaptive in stress environments
386
(e.g. Hunt and Hope-Simpson 1990). However, adaptation to stress environments is by relatively
387
high RGR in those environments, not by low RGR in a hypothetical optimal environment. Low
388
RGRmax is adaptive to stress environments only via a strategic trade-off: "It is possible that genetic
Wilson and Agnew, chapter 6, Theories, page 13 of 41
389
characteristics conducive to rapid growth in productive conditions become disadvantageous when
390
the same plants are subjected to environmental extremes" (Grime and Hunt 1975).
391
A limitation to the generalisation of C-S-R is that different types of stress favour different
392
types of species (Grime 1988). Moreover, not all species are adapted to one particular stress in the
393
same way. A dramatic example of this is seen in the wide range of life forms that are found in
394
adaptation to variable water stress in deserts. Some deserts, e.g. the Namib, have predictable rain in
395
one season (summer for the Namib) and support relatively few extant life forms, whereas others
396
such as the North American deserts, with rainfall less predictable from year to year, support a very
397
wide range. Some species are adapted by being avoiders, including stem succulents such as cacti
398
and leaf succulents as in members of the Crassulaceae, but also annuals/ephemerals which avoid
399
water stress as adults by dying and surviving water stress as dormant seeds. Yet others, like the
400
shrubs, are tolerators, having very low water potentials in their tissues in dry periods and shedding
401
leaves and even branches, but tolerating this without death. Again, this emphasises C-S-R as a
402
simplification.
403
Whereas C-S-R theory sees all stresses as in some sense equivalent, the ‘Centrifugal
404
Theory’ of Wisheu and Keddy (1992) emphasises their differences, placing them on multiple axes
405
diverging from the productive sites. As Austin and Gaywood (1994) point out, this is a display, not
406
a theory because it does not make testable predictions.
407
6.3 Disturbance
408
Grime’s definition of disturbance is unambiguous: "The mechanisms which limit the plant
409
biomass by causing its partial or total destruction". This refers to the whole community, but this
410
brings the problem that what is a disturbance for one species might not be for another (paralleling
411
one of the criticisms relating to stress). For example, the mowing disturbance of Burke and Grime
412
(1996) will have disturbed the tall species, but increased the resource (light) availability to short
413
ones. Selective grazing is another example. Short or unpalatable species might be described as
414
‘disturbance avoiders’ in contrast to ‘disturbance tolerators’, but it is not clear how this distinction
415
fits into C-S-R theory. How does C-S-R theory incorporate autogenic disturbance (chap. 2, sect. 6)?
416
One answer to this is that C-S-R theory is largely about the characters of species and that species of
417
different C-S-R status can co-occur. However, productivity, stress and disturbance are all defined
418
per site, and there is also a C-S-R triangle of sites, for example Grime (2001, Fig. 40) shows
419
“habitats experiencing intermediate intensities of competition, stress, and disturbance”.
Wilson and Agnew, chapter 6, Theories, page 14 of 41
420
421
6.4 Competition
Some have rejected the concept of competitiveness as an overall plant attribute, i.e. the
422
concept that a species that is a superior competitor for one resource is also a superior competitor for
423
all other resources (e.g. Grubb 1985). This is one prediction of C-S-R theory that can be tested quite
424
clearly. Contrasting shoot competitive ability (for light) with root competitive ability (for water and
425
the major nutrients) for the same species in the same conditions, the data assembled by J.B. Wilson
426
(1988c) indicate 13 (22 %) cases where the relative competitive abilities of two species were in a
427
different direction between shoot and root competition, and 46 (78 %) where they were in the same
428
direction, a significant difference. This supports the general idea of interference ability, but not that
429
it invariably applies to all types of interference. Non-transitivity of competitive ability (chapter 7)
430
would make a nonsense of the idea of overall competitive ability, but it seems to be rare or non-
431
existent (chap. 4, sect. 4). Another prediction of C-S-R theory is that competition intensity will be
432
lower in stress sites (Grime 2001). Grime (op. cit.) writes: “Some ecologists are extremely reluctant
433
to recognise the declining importance of competition for resources in unproductive habitats”. We
434
agree. We are amongst them, as we discuss below.
435
6.5 Species/character tests
436
The basic assumption of C-S-R theory is that there are “design constraints" (Grime 1988,
437
Grime et al. 1988) that limit viable character combinations. Reich et al. (2003) found a compelling
438
negative correlation between leaf lifespan and net photosynthetic capacity, though of course with
439
scatter, and a slightly weaker one via leaf N. Grime et al. (1987) made a more general test by using
440
a range of characters to classify species with cluster analysis and then looking for correlation
441
between the resulting groups and the three C-S-R 'strategies'. They found, in one analysis, a group
442
of low-stature, evergreen species with 'tough' foliage comparable to the S group. Grime et al. (1997)
443
used 67 characters, including experimental responses, to ordinate 43 species. They could informally
444
overlay a C-S-R triangle on the ordination diagram. There was also a good fit between this
445
ordination and that derived in Grime et al. (1988) from field distributions: e.g. the three species in
446
the C corner of the character ordination are in that corner in the distribution ordination, with
447
comparable fits for the S and R corners. This gives some support to C-S-R theory. A more direct
448
test of these trade-offs would be to find unoccupied character space, beyond the triangle.
449
Other tests can be made by determining whether species of the right type occur in the right
450
habitats. For example, Madon and Médail (1997) examined the distribution of species in a
451
Mediterranean grassland. Sites with a high cover of S species (but how they were designated as S
452
species is unclear) also contained a higher cover of annuals, but they do occur in S sites as well as R
Wilson and Agnew, chapter 6, Theories, page 15 of 41
453
ones and indeed are frequent in most such semi-arid grasslands and in some deserts. This
454
emphasises that C-S-R theory is a generalisation, not a law of the type that physicists can have.
455
Caccianiga et al. (2006) attempted to test C-S-R theory on succession on glacial moraines in
456
Italy. The concept is valid and it was a brave attempt, but unfortunately they used guessed species
457
cover. They found a succession3 from communities dominated by R species to those dominated by
458
S ones. Such a change is predicted by C-S-R theory, but there are problems. The prediction is for an
459
intermediate trend towards the C corner, and we would not expect the S corner to be reached within
460
the <200 yr of their dataset, though both of these may have been because the environment was a
461
high-stress one. Most problematic is that under C-S-R theory the R→S change that Caccianiga et al.
462
found occurs in a secondary succession; in a primary succession, which theirs certainly was, the
463
trend should be S→C-S-R→S (Grime 2001).
464
An experimental approach is perhaps better, since one can be sure what the habitat
465
differences are. Moog et al. (2005) applied four basic treatments – sheep grazing, mulching with
466
hay, burning in winter and control (‘succession’) – at 14 sites in southwest Germany. The
467
vegetation resulting 25 years later was classified in terms of C-S-R composition, using guessed
468
cover and calculating species’ C-S-R rankings by the method of Hodgson et al. (1999). There were
469
some changes in community C-S-R status that agreed with the theory. For example, grazing and
470
twice-yearly mulching, both presumably disturbances, reduced C-ness to c. 0.35 below the control.
471
Grazing and burning increased S-ness by c. 0.2 above the control. Moog et al. explained this
472
grazing effect due to the herbivory defence of S-strategists, or due to nutrient removal, though it is
473
not clear whether grazing will reduce nutrient availability or increase it through nutrient recycling.
474
They explained the increase in S-ness with burning as an indirect effect, that burning favoured
475
species with rhizomes which happened to be S-strategists, though severe burning can lower
476
nutrients (Certini 2005). Grazing and mulching increased R-ness by 0.4-0.5 above the control, as
477
predicted by C-S-R theory. However, large differences in C-S-R status were found between the
478
same treatment at different sites, up to 1.0 difference. Not clear-cut.
479
6.6 Does succession provide a test of C-S-R?
480
We shall consider here only secondary succession, because the most clear-cut tests are
481
available for them (J.B. Wilson and Lee 2000). Grime's (1979) interpretation was that for sites of
482
differing productivity there would be separate successional pathways, all starting from the R corner,
483
and all ending (eventually) in the S corner (Fig. 6.4a). At the start in the R corner, the S and C
484
succession trajectories are very close (Fig. a). Thus difference between stressful and benign
485
environments is negligible in plant characters, giving the opportunity for the same species to occur,
486
i.e. the same ruderal species in stressful as in benign habitats (Fig. 6.4b). Grime’s figures (Fig. 6.4a)
Wilson and Agnew, chapter 6, Theories, page 16 of 41
487
do not show any sites reaching up to the C corner but presumably they do, or there’s no point in
488
having a C corner.
489
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.
490
Considering the three S habitat types discussed by J.B. Wilson and Lee (2000), the main pioneer of
491
degraded land in Naiman Banner County, Inner Mongolia, is Agriophyllum squarrosum, a specialist
492
pioneer of dunes in semi-arid areas (Zhang et al. 2005). In Sonoran Desert oldfields, pioneers
493
include the very widespread weed Taraxacum officinale (dandelion), but also species such as
494
Salsola kali (tumbleweed) a ruderal annual of dry, often alkaline areas (Castellanos et al. 2005).
495
These recent examples add to the conclusion of Wilson and Lee (2000) that in arid habitats the
496
majority of secondary pioneers conform to the prediction of Fig. 6.4a in not being restricted to
497
deserts, though some are. The secondary pioneers of saltmarsh gaps are generally species of the
498
lower saltmarsh, as would be expected, since all species that occur on salt marshes, ruderal or not,
499
have to be quite salt tolerant: no agreement with prediction. Moving to alpine stress, the species
500
present in mid succession in southern New Zealand alpine grassland included the dicots Anisotome
501
aromatica, Plantago novae-zelandiae, Colobanthus strictus and Epilobium alsinoides (Lloyd et al.
502
2003), the last extends down to the lowlands, but the others are basically montane / subalpine in
503
range. J.B. Wilson and Lee (2000) gave an example from alpine Scotland where the first colonists
504
were not specialist pioneers, but species of several S habitats. However, pioneers in the Andean
505
alpine oldfields include the very widespread ruderals Erodium cicutarium (stork’s bill), Poa annua
Wilson and Agnew, chapter 6, Theories, page 17 of 41
506
and Rumex acetosella (sheep’s sorrel; Sarmiento et al. 2003). There seem to be no generalisations
507
here.
508
Grime (2002) shows primary succession in S environments as occurring within the S corner
509
of the triangle. J.B. Wilson and Lee (2000) argued that only specialised species would be able to
510
tolerate the environment of an S site. This gives the likelihood of autosuccession, with no
511
specialised secondary pioneer species. Again, C-S-R theory strictly predicts the same type of
512
species, but if there is space for fewer different niches there will tend to be fewer different species.
513
J.B. Wilson and Lee (2000) tested this prediction in relation to four types of stress. In alpine
514
environments they cited two examples, one where autosuccession was occurring and one where it
515
was not. Sarmiento et al. (2003) found that in high-Andean oldfield succession, of the eight most
516
abundant species in the undisturbed community, four were absent the first year after abandonment,
517
three others were present only in traces and the remaining one made up less than 1 % of the cover –
518
no autosuccession here. In arctic tundra, another habitat cited by Grime (1979) as high-stress, there
519
are usually pioneers, but autosuccession is occasionally seen (J.B. Wilson and Lee 2000).
520
Autosuccession is often seen on saltmarsh, especially on the more S lower saltmarsh, though it is
521
not certain that Grime would count saltmarsh as an S habitat. For desert, E.A. Allen’s (1991)
522
suggestion that autosuccession is common is not supported by the literature (J.B. Wilson and Lee
523
2000) or by Castellanos et al. (2005) in the Sonoran Desert, though the evidence of Zhang et al.
524
(2005) from China is mixed. There is some tendency for autosuccession to occur in the most
525
extreme S habitats, though it occasionally occurs in mesic habitats (J.B. Wilson and Lee 2000).
526
6.7 Conclusions
527
There have been many more criticisms of C-S-R theory, but most of them have missed its
528
point (J.B. Wilson and Lee). Several of the predictions of C-S-R theory are very difficult to test,
529
reducing the value of the theory as an explanatory model for the structure of plant communities.
530
Even for predictions that are more easily tested, there has been little quality evidence. However, the
531
evidence so far is that predictions from C-S-R succeed more often than they fail so that it is useful
532
generalisation.
533
534
7 Tilman’s theory
Tilman (Titman 1976; Tilman 1982; 1988; etc.) has produced a number of ideas. Here we
535
emphasise those that have made a particular contribution to the topic of our book. The concepts
536
have been described as having “a hard centre but woolly edges”: that is, there is a solid core of
537
irrefutable mathematics, but it is not always clear how to apply them to the real world. Some
Wilson and Agnew, chapter 6, Theories, page 18 of 41
538
aspects – strategy, species richness and competition – are considered in comparison with Grime’s
539
theory (section 8).
540
Titman (1976) concluded from his first experiments: “long-term coexistence of competing
541
species was observed only when the growth rate of each species was limited by a different
542
nutrient”. This is standard Gaussian exclusion by interference, but he developed his R* theory of
543
how it happened. He later developed a concept of spatial niches (Tilman 1988), and then embraced
544
the fugitive model (Tilman 1994; see chapter 4 above). Craine (2005) has documented the
545
developments and retreats of Tilman’s theories. ~
546
7.1 The competitive process: R*
547
Tilman’s (1982) R* theory is that a particular species in a particular set of environmental
548
conditions has for a particular resource R a value R*, which is the lowest [R] (i.e. concentration of
549
R) at which it can grow in monoculture. Above its R* the species can grow, absorb R, and will
550
therefore lower [R] towards R*. In mixtures, where R is limiting, as [R] becomes lower each
551
species will drop out as [R] drops below its R* and it can no longer grow. Apparently no species
552
will enter during this process. The one species left will be the one that can tolerate that the lowest
553
[R], and the concentration of R at that moment will be its R*. To summarise, the species with the
554
lowest R* will be the superior competitor. The model is deceptively simple. Application to the real-
555
world terrestrial communities is another matter.
556
Major soil nutrients (NPK)
557
Tilman (1981) found that the R* model explained which species of alga won in a microcosm
558
experiment with inorganic nutrient limitation, in constant temperature, a constant daily light regime,
559
fixed lighting conditions and with the solution well mixed by flow and shaking. T.E. Miller et al.
560
(2005) surveyed the literature and found 11 similar plankton microcosms experiments and (contra
561
Miller et al.’s conclusion) all tended to support the theory (Wilson et al. submitted).
562
The situation is not so clearcut in soil where the environment is variable in time and space.
563
Tilman and Wedin (1991a; b) in field plots at Cedar Creek found the outcome of competition on
564
low N soil was predicted by R* in some cases. Comparing the grasses Agrostis scabra (bent) with
565
Schizachyrium scoparium (little bluestem) the two performed approximately equally in
566
monoculture, but in competition S. scoparium was the clear winner. By R* theory, it should have
567
reduced N in the soil (both nitrate and ammonium) to a lower level than A. scabra, and indeed
568
available N as measured by KCl extraction was lower. It should also have been able to grow at a
569
lower N level, but the experimental results do not tell us one way or the other. A. scabra suffered in
570
competition at the low N levels that S. scoparium produced, but not necessarily because of them.
571
Indeed it suffered almost as much in competition in the two higher N levels. Very similar effects
Wilson and Agnew, chapter 6, Theories, page 19 of 41
572
were seen in competition between the A. scabra and Andropogon gerardii (big bluestem) and in a
573
less clear-cut way in competition between A. scabra and Agropyron repens (quackgrass). These
574
results are ambiguous: perhaps A. scabra is more efficient at N uptake, but suffers in light
575
competition. Indeed, it grew shorter than other species, including S. scoparium in the experiments
576
of Tilman (1986).
577
Even conceptually it is difficult to apply R* to soil nutrients. Plants will lower [N/P/K] to
578
some extent. However, these elements are always being mineralised from organic matter by
579
decomposers at rates which depend on the environment, soil microflora and the fauna. Leaf leachate
580
also makes some contribution. They are added in normal and occult precipitation, and in the settling
581
of atmospheric particulates. Against this, they can be made unavailable by being immobilised from
582
solution to exchangeable form and then to unavailable forms, organic or mineral, by being taken up
583
by bacteria and other micro-organisms, or eventually by being lost by leaching and soil erosion. In the
584
case of N, the mineralisation is to ammonium, taken up thus by some plants, but for others first
585
nitrified to nitrate and taken up in that form. It can also be fixed from the air by free-living soil micro-
586
organisms and in larger quantities by the symbioses with legumes and several other species and,
587
perhaps thus added to the soil or perhaps not. It can be lost by denitrification/volatilisation. P and K
588
can be made available by hydrolysis of minerals, especially of feldspars and apatite, a process that
589
can be speeded by exudates from plant roots. Fire can increase the loss by erosion and volatilisation,
590
and animals can cause local loss of nutrients through redistribution. Vitousek (2004) describes many
591
of these processes for Hawai’i.
592
These processes are all dependent on water and some are affected by the pH of the soil, and
593
therefore depend on various environmental factors. As a result, all are patchily available in 2-D
594
space. Since most of nutrient processes start at the soil surface there is usually considerable
595
variation with depth. Availability also varies markedly in time, varying stochastically and with
596
season. Nitrogen will normally be most abundant in spring, when maximum growth occurs (Tilman
597
and Wedin, 1991a, measured soil N in summer). Plant roots will hardly lower total [P], since most is
598
insoluble. Unlike N, with its fast-diffusing NH3 and NO3 ions, available P is almost immobile so
599
plants cannot rely on diffusion to acquire the element from the soil as a whole, but have to forage
600
for it by growth. The cylinder around the root from which they take up P can be as narrow as 1 mm in
601
radius (Kraus et al. 1987). This basic difference between competition for mobile N and that for
602
immobile P was pointed out by Bray (1954), and Craine (2005) emphasised how misleading an
603
overall [R] value is with P, since there is localised depletion. How can R* theory be applied in these
604
circumstances?
Wilson and Agnew, chapter 6, Theories, page 20 of 41
605
Water
606
Water is available intermittently in time, a complication for R* theory, and often at different
607
depths. Most water lands on the surface and perhaps moves down, but water can also be available
608
from deep aquifers and by hydraulic lift plants. Thus, plants are not using the same pool of water in
609
time (ephemeral annuals versus perennials) or space (deep-rooted shrubs and perennial grasses
610
versus shallow-rooted cacti). How does R* apply then?
611
Light
612
In light competition, canopy species reduce the resource availability below them, but not
613
above them; R* theory knows nothing about directions. By R* theory, the climax canopy species
614
would reduce lower-stratum light to low levels, and be able to tolerate these low levels and hence
615
regenerate. But this depends on whether there is continuous regeneration, large-gap regeneration or
616
single-tree replacement, and in the latter two cases whether the next generation is from dispersal,
617
the seed pool, from suppressed seedlings or from advanced regeneration. All these modes occur,
618
often within the same community, different species regenerating by different modes (e.g. Lusk and
619
Ogden 1992; Thomas and Bazzaz 1999), but there seems to have been no review of the relative
620
importance of these modes.
621
Assuming continuous below-the-canopy regeneration, R* predicts that shade-tolerant plants
622
will achieve tolerance by having a lower light-compensation point. Kitajima (1994) compared 13
623
tree species of Barro Colorado Island rainforest. Shade tolerance was determined as the survival
624
rate of seedlings under a shade cloth that gave light intensity very similar to that of the forest
625
understorey, with supporting evidence by field observations of mortality in the understorey and the
626
tendency of the species to occur in light gaps. Survival in shade was uncorrelated with the light
627
compensation point (r = +0.27) and with dark respiration (r = +0.25 on a mass basis). Eschenbach
628
et al. (1998) examined tree species of North Borneo lowland dipterocarp forests in the field. Light
629
compensation points were attained mainly between 6 and 9 μ mol photons m-2 s-1 but were higher
630
for pioneering species. This supports an R* interpretation in continuous regeneration, but the
631
presence of pioneer species reminds us that gap regeneration is occurring.
632
The truth is that regeneration in forests, and probably in some other communities, is too
633
complex to fit R* theory.
634
Conclusion
635
None of these complications occur in environmentally-constant, homogenous, nutrient-
636
limited habitats such as a lab tank with planktonic algae that Tilman had in mind when he formed
637
R* theory, and it usually gives correct predictions for them (Wilson et al. in press). In real habitats,
638
R* theory is not only very complex to test, it is often impossible to see how to apply it or test it.
Wilson and Agnew, chapter 6, Theories, page 21 of 41
639
There are many, obvious simplifications in this model. It would have been very useful had R* been
640
able to predict competititve ability, for the many previous attempts to find empirical correlations
641
between competitive ability and plant characters have generally failed (e.g. Jokinen 1991). An
642
exception is the obvious correlation of height when competition for light is important (e.g. Balyan
643
et al. 1991), a correlation expected under C-S-R theory, but not under R* theory. There is a problem
644
that under R* theory competitive exclusion would lead to only one species remaining, yet
645
communities almost always comprise many species, not least in Tilman’s own site at Cedar Creek.
646
There, in a 49-yr oldfield (the second-oldest field) there were 12 species per 0.5 m2 quadrat (Inouye
647
et al. 1987). There was not even a downward trend: the 49-yr value was the highest amongst the 22
648
fields and the overall trend, although non-significant, was for richness to increase with age.
649
7.2 Succession
650
Tilman (1982) also generated a resource-ratio theory of succession, starting from the
651
observation that at his Cedar Creek experimental site soil nitrogen (N) increased during secondary
652
succession. This is often the case, though it is difficult to know what fraction of soil N is available
653
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.
654
therefore be better competitors at low N; late-successional species would require high N, but be
655
better competitors, probably for light, in those conditions. He performed experiments with co-
656
workers and concluded that later successional species at Cedar Creek do not necessarily have a
657
higher N requirement or response (Tilman 1986; Tilman 1987b; Tilman and Cowan 1989). The
658
former statement is true: the modal nitrogen content of the soil in which various species grow at
659
Cedar Creek (Tilman and Wedin 1991a) is not significantly related4 to their RGR at low N (Tilman
660
and Cowan 1989) nor5 to their growth at high N. However, their response to N (RGR at high N /
Wilson and Agnew, chapter 6, Theories, page 22 of 41
661
RGR at low N, data as above) is clearly related6 to their modal soil N (Fig. 6.6). What is not so well
662
related is their successional position. The low-responding Agrostis scabra does indeed appear early
663
on and peak at c. 5 five years (Tilman and Wedin 1991a), but the high-requiring and high-
664
responding Poa pratensis (meadow grass) peaks at c. 15 years, whereas Schizachyrium scoparium
665
is hardly present then, and peaks at c. 45 years. Harpole and Tilman (2006) and Fargione and
666
Tilman (2006) produced similar partial support by correlating previously-determined nitrogen R*
667
values with relative abundance in three semi-natural or experimental areas at Cedar Creek. This
668
assumes that competitive ability and abundance in a mixture will be correlated and this is not
669
necessarily so (chap. 3, sect. 7.3). The correlations were highly significant but reflect only that the
670
three abundant species have low R*, whilst that for other species covers the range from low to high.
671
There was considerable respect for Tilman that he had published many results with frank
672
admission of their conflict with his theory. However, this leaves R* theory hanging (Craine 2005).
673
It is also difficult to generalise the ideas. Tilman emphasises the increase in soil nutrient status,
674
especially of nitrogen, during both primary and secondary succession (Tilman 1988). It is true that
675
only a few successions do not have a monotonic N increase (e.g. Crews et al. 1995, examining a
676
4100000 yr chronosequence in Hawai’i), but often phosphate limitation is a major determinant of
677
plant growth during succession and it decreases (Chapin et al. 1994; Richardson et al. 2004). We do
678
not consider these theories useful for the real world.
679
7.3 Conclusion
680
Tilman followed the example of MacArthur in producing formal models of how
681
communities might work. He and many others have been able to test his models (Miller et al. 2005).
682
R* theory has proved highly robust for micro-organisms in experimental conditions, though it is
683
hard to see how it will extend to embryophytes. Moreover, when Tilman attempted to put
684
successional processes on a more formal basis, reality proved to be more complicated. We discuss
685
other ideas of his below, notably agreeing with his ideas on the intensity of competition along
686
gradients of productivity. Tilman tried to find neat patterns in ecology. It was brave of him.
687
688
8 Grime versus Tilman
The ideas of Tilman have often been compared with Grime’s. However, C-S-R theory is a
689
coherent body of ideas, including the characters of the species, the characteristics of the habitats,
690
succession, whole-community attributes such as stability and the relation of species richness to
691
productivity (the humped-back theory). All these are interconnected. It has remained essentially
692
unchanged since 1979, the only major addition being that all stresses are basically unavailability of
693
mineral nutrients. Love it or lump it, it is the only comprehensive, coherent theory we community
Wilson and Agnew, chapter 6, Theories, page 23 of 41
694
ecologists have. Tilman’s theory, in contrast, includes a number of ideas that are rather separate,
695
covering the mechanism of competition, where competition will be most intense, how resources
696
will change during succession, whether and how species will co-exist, species diversity, etc. Some
697
of these theories have been effectively disproved, even by Tilman himself, but others remain alive.
698
To some extent this reflects that the theories are put in a more testable form than Grime’s. Grime
699
does have one undisputed advantage over Titman/Tilman: he did not change his name part way
700
through.
701
8.1 Strategy
702
The concept of strategy is old, and intuitive to every child, that the effort a plant or animal
703
puts into one organ or activity is at the expense of another. Plant ecologists generally think of
704
biomass, though calorific content might be more appropriate. Cody (1966) stated the concept
705
eloquently: “It is possible to think of organisms as having a limited amount of … energy available
706
for expenditure, and of natural selection as that force which operates in the allocation of this …
707
energy in the way that maximises the contribution of the genotype to following generations” (the
708
“…” omissions were “time and”; it is easier to see time as a resource for animals than for plants).
709
Harper and Ogden (1970) applied this concept to plants by examining the proportion of energy
710
allocated to reproductive structures. Much consideration has been given to the selective advantages
711
of particular reproductive strategies, formalised in terms of optimal strategy and later more correctly
712
as evolutionarily stable strategy (Smith 1982). The concept applies to a whole species, to ecotypes
713
and to plastic responses. It applies to vegetative allocation too, for example, shoot versus root
714
allocation: "the plant makes every endeavour to supply itself with adequate nutriment, and as if,
715
when the food supply is low, it strives to make as much root growth as possible” (Brenchley 1916).
716
This principle is implicit in C-S-R theory; it explains why no species can be a perfect competitor, a
717
perfect stress-tolerator and also a perfect ruderal. Indeed, Grime commonly refers to C-S-R as
718
‘Strategy Theory’, as though it were the only one. Tilman has also moved to an emphasis on
719
strategy with his ALLOCATE model of plant growth and competition (Tilman 1988), emphasising
720
shoot versus root strategy, a field with a long history of theory and observation (J.B. Wilson 1988a),
721
but usefully put into the context of the community.
722
8.2 Species diversity
723
Tilman (1982) reached a similar conclusion to Grime (1974), that there would be a humped-
724
back relation between productivity and species richness. Like Grime, Tilman’s argument for low
725
richness under low productivity included the idea that there are few species capable of growing in
726
conditions of high stress, but he also suggested that environmental heterogeneity would be low
Wilson and Agnew, chapter 6, Theories, page 24 of 41
727
there, with all microsites equally stressful. He also agreed with Grime in seeing a decrease in
728
richness at high productivity as being due to greater competitive exclusion. He later, finding that
729
nitrogen application led to a reduction in species richness in the Cedar Creek oldfields, converged
730
with Grime’s conclusion that this effect was due to shading suppression by live plant material and
731
litter (Tilman 1993).
732
8.3 Competition
733
Grime’s and Tilman’s hypotheses
734
Grime’s (1974; 2001) theory is that in the S corner of the C-S-R Triangle there is no
735
competition because neighbours are too limited by the physical environment to interact. Near the S
736
corner, competition is low. This conflicts with ecological common sense and close-to universal
737
observation. Almost everywhere plants fill the area. Having grown, how do they stop when they
738
reach this state, unless through competition? As elsewhere, ‘competition’ has been used when other
739
kinds of interference will be involved too, but we shall consider competition for the moment.
740
Tilman’s (1988) contrary view is that competition will be equally important in unproductive (high
741
stress) and productive (low-stress) environments. The logic seems to be that if resource availability
742
is too high for there to be competition, the plants will grow until availability has been reduced so
743
that there is competition for it, or until another resource becomes limiting. For Grime the issue is
744
connected to his humped-back model of species richness: at low productivity / standing-crop R and
745
C species will be absent. D.A. Wardle (2002) uses this argument to comment that Tilman’s R* model
746
is “difficult to reconcile with the frequently observed humped-back relationship between diversity and
747
productivity”, because according to Tilman competition, and hence competitive exclusion, will be no
748
greater at high biomass. Wardle’s statement is misleading for several reasons: (a) the humpedback
749
relation is far from universal, especially considering significance by an appropriate test of the
750
downturn at high richness, (b) the usual relation has been with richness, not diversity, (c) productivity
751
has hardly ever been measured, only above-ground standing crop, and (d) the logic is based on the
752
downturn in richness at high standing-crop being due to exclusion by interference, which even Wardle
753
admits is only “a likely reason”.
754
An explanation for population maintenance without competition in high-stress
755
environments, such as deserts, has been a low probability of ecesis and/or high mortality. An ecesis
756
rate that happens to exactly balance mortality is infinitely unlikely. Yet, even a slight deficit of
757
ecesis over mortality would give RGR (population growth rate) less than 0.0 and a population that
758
declined to zero, and even a slight excess of ecesis would give RGR greater than 0.0 and a
759
population that climbed towards infinity. Neither are ever seen in existing populations. The logical
760
conclusion is that in all persistent populations of a species, ecesis and/or mortality must be density-
Wilson and Agnew, chapter 6, Theories, page 25 of 41
761
dependent, and the most likely explanation is competition. We conclude that in all environments
762
plants will increase in abundance until they are limited by interference, usually because competition
763
is 100 %, even if we ecologists, as outsiders, cannot easily see what the critical resource is. There
764
are two riders to this. Firstly, competition will be absent in the very earliest stages of succession
765
(Clements et al. 1929). Another possible explanation of sparse populations could be that they are
766
present because of subsidy from elsewhere: the spatial mass effect (chap. 4, sect. 12), but it seems
767
unlikely this is the main explanation of large areas of desert vegetation. Thirdly, it would be
768
possible for density-dependent herbivory to hold abundance too low for competition to occur. It is
769
not clear this could happen, because with such low levels of plant productivity herbivore
770
populations might not be able to exist.
771
Grace (1991) made another important point: “both Grime and Tilman discuss gradients in
772
habitat productivity as if it makes no difference whether they are gradients in [resources] or non-
773
resource factors”. However, there is more complication. Many studies in the literature examine the
774
effect of a mineral nutrient such as N in a system where competition is probably for light, or even
775
necessarily for light by the experimental design. For example, Stern and Donald (1962) added N to
776
a grass and a clover growing with their roots separated. In this example the gradient is a resource,
777
N, but the competition is not for N, but for light. The true distinction is between a gradient in a
778
factor for which there is competition and in a factor for which there is no competition. But the
779
factor for which there is competition will change. If soil nutrients or water are limiting initially, and
780
they are added, the limitation will be removed and competition will shift to being for light (Tilman
781
1988). Moreover, the environmental conditions will then be so different that it will be difficult to
782
say whether competition is less, the same or greater (see The growth-rate artefact below). Perhaps
783
an even greater problem is that once competition is for light it will probably be cumulative (chap. 2,
784
sect. 2.3). Other complications are the change in species composition that will occur along gradients
785
and the lack of a generally-agreed index of competition. Most of the confusion that has grown about
786
this topic seems to come from ignoring what resource competition is for.
787
The growth-rate artefact
788
A huge complication in experiments testing the Grime versus Tilman ideas on competition
789
is that if plants are put in a pot in a high-productivity environment the plants will by definition grow
790
faster, and thus come into competition sooner. Therefore, if competition is measured at a fixed time
791
after planting, it will appear to be greater in more productive conditions. The same situation occurs
792
after natural disturbance in a favourable environment. Eventually, competition will be 100 % right
793
along the gradient because the plants will grow until carrying capacity is reached and competition is
794
complete in the community-matrix sense: if x grams of plant material are removed growth will
Wilson and Agnew, chapter 6, Theories, page 26 of 41
795
resume until there are x grams more. Therefore competitive intensity cannot be measured as the
796
final outcome either. Competition is like death: it’s not a question of if, but of when. This problem
797
of the growth-rate artefact is removed when the experiment indicates lower competition at higher-
798
productivity conditions, but it is difficult to accept only results in one direction. Another
799
complication is that resources will be exhausted sooner when they are in shorter supply; resource
800
availability is not a fixed variate, but as always in communities is subject to reaction.
801
Our own hypothesis
802
Our own view, from first principles, is that along a beta-niche gradient (i.e. a gradient of
803
conditions, of non-resources, or of resources for which competition is not occurring), competition
804
will be of constant intensity, but will appear to be greater in more productive conditions because of
805
the growth-rate artefact.
806
Along an alpha-niche gradient (i.e. of a resource for which there is competition) competition
807
will be strongest when the resource is in shortest supply. There can be exceptions, e.g. the mobility
808
of some soil nutrients can be higher when they are present at higher concentrations and this can
809
result in greater below-ground competition (e.g. Vaidyanathan et al. 1968; J.B. Wilson and
810
Newman 1987). The same could apply to water. An additional complication is that as the
811
availability of resource X increases along a gradient, the plants may change from competing for X
812
to competing for resource Y.
813
Deserts
814
Ecologists often see what they think are exceptions to the universality of competition in
815
deserts, where the plants are spaced above-ground. The desert habitat is indeed stressful and if there
816
is competition it is likely to be for the same factor that causes the stress: water supply. Many, from
817
Shreve (1942) through Went (1955) to Mirkin (1994), have denied that desert plants compete. This
818
idea was fuelled by studies that failed to find a regular spatial pattern of individual plants in deserts,
819
and sometimes found clumping instead (e.g. Gulmon et al. 1979). The idea was often that plant
820
populations in deserts were kept below 100 % occupancy by unfavourable probabilities of
821
colonisation and death. We demolished this argument above, showing that there must be 100 %
822
competition, and if it is manifestly not above-ground it must be below-ground. The existence of
823
intense competition for water has been demonstrated by finding negative correlations between plant
824
sizes and distance apart (Yeaton and Cody 1976) and by relief of plant water stress and increase in
825
plant growth upon removing neighbours (Fonteyn and Mahal 1978; Robberecht, et al. 1983; Fowler
826
1986a; Kadmon and Shmida 1990). In fact, the effect of competition on plant spatial pattern has
827
been best demonstrated in desert communities. Ecologists have often underestimated the intensity
828
of competition where there seem to be unvegetated gaps between plants; in fact the cacti and shrubs
Wilson and Agnew, chapter 6, Theories, page 27 of 41
829
may be spaced out, but their root systems are not (Woodell et al. 1969). Clements knew this, of
830
course: “The open spacing of desert shrubs in particular suggests some indirect influence in
831
explanation, but studies of the root systems demonstrate that this is a result of competition for water
832
where the deficit is great” (Clements et al. 1929, p. 317). Remember our rider above on the spatial
833
mass effect. Remember our rider on herbivory, but it is a tenet of C-S-R theory that plants of
834
unproductive sites have more defences (Grime 2001). Disturbance would also override competition,
835
but is disturbance really so frequent in deserts that they are in a continually seral state? Anyway, it
836
is the basis of the C-S-R triangle that stress sites cannot have much disturbance, or no plants can
837
grow. We conclude that the intensity of competition is likely to be approximately 100 % in all
838
communities, supporting Tilman’s conclusion, perhaps for different reasons.
839
Tests
840
The complete absence of competition would be testable. However, we argue above that this
841
is not tenable, and moreover no habitat can fall exactly in the S corner so the question does not
842
arise. We have to test degrees of competition along an S–C gradient, which is possible but difficult.
843
The literature is unclear on how to measure the intensity of competition; we shall use a species’
844
percentage reduction from monoculture, ideally in RGR but sometimes in biomass.
845
Considering a gradient of environment conditions, La Peyre et al. (2001) grew three species
846
of salt/freshwater marshes in monoculture and competition along a salinity gradient. A measure of
847
the overall importance of competition was almost constant along the gradient, and once allowance
848
is made for dead material the competitive response of the individual species varied remarkably
849
little. Similarly, Cahill (1999) found no consistent change in aboveground competition in his
850
oldfield experiment between the two NPK levels. Although N, P and K are resources, in the latter
851
comparison there was competition only for light, so they are conditions. These two pieces of work
852
support our thesis that along a gradient of conditions, competition will be of constant intensity.
Wilson and Agnew, chapter 6, Theories, page 28 of 41
853
For a gradient in a resource for which competition is occurring, a relevant experiment is that
854
of Campbell and Grime (1992), growing seven species in outdoor plots with a range of nutrient
855
levels and disturbance regimes. Nutrients promoted growth considerably (Fig. 6.7a). Campbell and
856
Grime declare that Arrhenatherum elatius (oat grass) is a plant of fertile soils, and Festuca ovina,
857
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.
858
nutrient response does not differ between species (p = 0.989 7). The species differ in the effect of
859
interference on them (Fig. 6.7b; p < 0.0018), but there is no overall effect of nutrient supply on the
860
intensity of interference (p = 0.072 9), disproving Grime’s assumption. Goldberg et al. (1999) found
861
in a meta-analysis that there was a tendency for competitive intensity to decrease more often than
862
increase with productivity, in general conformity with our theory and Peltzer and Wilson (2001)
863
found no significant trend with standing crop, used as an inverse proxy for stress. However, the
Wilson and Agnew, chapter 6, Theories, page 29 of 41
864
experiment of Campbell and Grime, as many of those surveyed by Goldberg, has the restriction that
865
it is not possible to tell whether competition was for the resource (NPK) that varied along the
866
gradient. This restricts very considerably the range of investigations available for critical tests.
867
The experiments of Peltzer et al. (1998) in Saskatchewan, Canada, and Cahill (1999) in
868
Pennsylvania, USA, were both in oldfields, planting seeds or seedlings into plots where shoot
869
competition was prevented by tying back the vegetation, root competition was either prevented or
870
allowed by using plastic tubes, and fertiliser was added or nor (N in the case of Pelzer et al. and
871
NPK in the case of Cahill). Both studies showed somewhat greater belowground competitive effects
872
when soil resources were in shorter supply. This confirms the conclusion of J.B. Wilson (1988c),
873
surveying experiments on root competition, that the limited evidence available indicates that
874
competitive intensity is highest when soil resources are in shortest supply. In those experiments the
875
the gradient is one of soil nutrients and competition must be for either soil nutrients or water, but
876
generally it is not possible to see which. However, Cahill recorded soil moisture with gypsum
877
blocks, and found no significant difference between treatments, implying so far as one can from
878
non-significance that the competition was not for water. The study that comes closest to answering
879
the question is that of S.D. Wilson and Tilman (1991) at Cedar Creek, an experiment similar in
880
most respects to those of Peltzer et al. and Cahill. It is known from other work that nitrogen is the
881
limiting mineral nutrient in the oldfield at Cedar Creek and other nutrients were applied to all
882
treatments to make absolutely certain of this (right down to Cu, Co, Mn and Mo). Only N
883
(ammonium nitrate) differed between treatments. It therefore seems likely that we are looking at
884
competition for N along a gradient of N supply. Moreover, RGR is available to judge the result. In
885
all three species used the belowground competitive effect was greater at low soil N supply. An
886
experiment with one of the same species confirmed this (S.D. Wilson and Tilman 1993). The
887
overall evidence overwhelmingly supports our contention that competition for resource X will
888
generally be most severe when X is in shorter supply. It is surprising that anyone thought otherwise.
889
However, we must remember that in the real world soil nutrients are patchy (chap. 4, sect. 1.3).
890
We conclude that both Grime and Tilman were wrong. Along a gradient of an
891
environmental factor, or of a resource for which competition is not occurring, competition will be
892
equally intense right along the gradient. Along a gradient of a factor for which there is competition
893
the most severe competition will be at low levels of it. If the resource for which competition is
894
occurring changes, the question is too difficult to answer.
Wilson and Agnew, chapter 6, Theories, page 30 of 41
895
9 Synthesis
896
9.1 “Too soon to tell”
897
Plants are simple to physiological ecologists, operating not so far above the level of physics.
898
Even so, they have found it hard to produce general theories, except that of adaptation which is
899
dangerous if applied uncritically (Gould and Lewontin 1979). Population ecologists, working at the
900
level below community ecology, can see clear patterns such as a logarithmic decline when death
901
rates are constant (Harper 1967), but their main principle seems to be density-dependence, which
902
we argued above is logically an almost necessary feature of a persisting population. In ecosystem
903
ecology, at the level above community ecology, it is possible to see some patterns imposed by the
904
laws of conservation of matter and of energy. We community ecologists are in the worst situation.
905
Theories fail. Generalising from first principles and seeking hard evidence the best evidence we
906
have is for the Botany Lawn, and though it seems clear that assembly rules are operating we do not
907
know how, or even whether they are based on aboveground or belowground plant interactions. As
908
Mao Zee Tzung is claimed to have said when asked what the effect of the French Revolution had
909
been on subsequent history: “It is too soon to tell”. Theories of communities are certainly at too
910
early a phase to be applied to practical problems. The dangers of doing this are exemplified by
911
attempts to apply ‘Island Biogeography’ theory to reserve design.
912
9.2 “Does vegetation suit our models?”
913
None of the models of plant communities yet produced have high synthetic or predictive
914
value. We deeply respect Frederick E. Clements’ field knowledge of vegetation, his powers of
915
observation and generalisation and his pioneering experimental work. All of his concepts contain a
916
good deal of truth. Since the same community rarely recurs (J.B. Wilson et al. 1996b) his
917
formations and associations are simplifications, but similar classification continues today. It does
918
little harm when it is admitted that the main purpose of the ‘associations’ is to identify conservation
919
targets to the public and to government. We dedicate this book to Clements’ for his insights.
920
Variation along environmental gradients is sometimes continuous, but at other times
921
discontinuous due to the operation of a switch, as both Clements and Gleason believed. This is true
922
even of many boundaries that ecologists categorise as ‘environmental’ such as between a
923
saltmeadow and a saltpan, or a riverbank. The rôle of switches in generating the spatial patterns
924
around us has been considerably underestimated. The methods of Mike Austin and co-workers
925
(section 4) indicate continuous variation along environmental gradients, but this is partly because
926
they have worked at a larger spatial extent than that on which most switches occur. Nevertheless,
927
there is increasing interest in geographic-scale switches, especially those involved with climatic
928
change (chap. 3, sect. 5.4.A).
Wilson and Agnew, chapter 6, Theories, page 31 of 41
929
Philip Grime’s C-S-R is the only modern, overall theory of plant communities. It matches
930
the current interest in guilds, often under the name ‘plant functional types’ (chap. 1, sect. 4.2), and
931
usefully it does so using continuous axes, not discrete types. Both C-S-R theory and intrinsic guilds
932
avoid the ad-hoc guilds commonly used, but in opposite ways. Intrinsic guilds are defined in each
933
study with no pre-conceptions, discovering the structure from the community itself. C-S-R, in
934
contrast, has an a-priori triangle derived from field and experimental experience and with
935
theoretical underpinnings from r-K theory and from leaf ammortisation theory; this is used as a
936
template for understanding all vegetation. C-S-R is a useful and stimulating generalisation and it
937
has spurred the collection of an excellent database of plant ecological characters. Other datasets
938
should aspire to this quality. Tilman’s concept that competition will be equal along a productivity
939
gradient is close to the truth, but his R* approach seems to be too simplistic for embryophytes.
940
Plant ecologists tend to produce models and then try to make the facts fit. Anna Bio (2000)
941
neatly criticised this as, “Does vegetation suit our models?”. The nature of the community depends
942
on the nature of its parts and the starting point must be the peculiar characteristics of plants (chap. 1,
943
sect. 1.1): they do not consistently have ‘individuals’, they are colonies of modules moving through
944
space (“Plants move, animals don’t”). Litter forms an extended phenotype around plants that moves
945
with them. Its effects persists after them, and can have lasting effects if there is a switch operating.
946
The effect of plants does not die when they die. The species therefore plays the part of an individual
947
in the community. Its rôle depends on its shape and secondarily on its physiology and chemistry. Its
948
reaction on the environment and on associated biota flows from these. These characteristics of
949
plants produce a range of interactions within and between species (Box 6.1), many of which are
950
rarely considered in a community context. All this will make it difficult for vegetation to suit our
951
simple models.
Wilson and Agnew, chapter 6, Theories, page 32 of 41
952
953
Box 6.1: Types of interaction between plants.
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
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
973
974
975
976
977
978
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
979
A few of the interactions between plants are direct. Parasites and strangling lianes are
980
examples, as are the fascinating and understudied effects of shaking and physical abrasion (chap. 2,
981
sect. 6.1). Interactions via herbivores, fungi and microbes are more important. Parasitism is well
982
known, and we are afraid we have tended to ignore it as a special case, and shall do below.
983
However, the most important types of interaction are via the environment, i.e. reaction. In the short
984
term this effects most types of interference and subvention. Competition is often spoken of as if it
985
were the only negative interaction between plants, but in fact it is one of many, modified by
986
subvention. Longer-term and often stronger reaction results in either community change, most
987
likely via relay floristics or reinforcement of the current state via a switch (Box 6.1). The “or” is a
988
simplification since an accelerating or delaying switch can operate during relay floristics. Cyclic
989
succession is really a third type (Fig. 3.1); there is very rarely good evidence for it (chap. 3, sect. 4),
990
but there is only marginally more for relay floristics or switches. It seemed necessary to divide
991
subvention by whether the effects were reciprocal. However, we could also divide subvention by its
992
cause, notably reaction versus interactions via heterotrophs.
993
994
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 33 of 41
995
plants. The combination of these processes does not give a neat pattern (Fig. 3.10) nor does it make
996
it easy to use neat labels. However, one clear conclusion is that whenever ecologists see a sharp
997
boundary in nature without an obvious environmental or historical cause, they should suspect that a
998
switch is operating.
999
Three things are clear about plant communities: (1) almost all comprise many species,
1000
(2) they are heterogeneous and (3) ecologists must hope there are some rules governing the
1001
assembly of species in them – assembly rules – or there is no science in plant community science.
1002
9.3 The ‘Paradox of the plankton’
1003
The 12 mechanisms that could be permitting species to coexist are now clear (chapter 4), but
1004
evidence of their relative importance is sparse. The lack of evidence on Initial Patch Composition
1005
(7) and Co-Evolution of Similar Interference Ability (11) probably reflects their lack of realism.
1006
However, experiments on each would be possible. The existence of Equal Chance (9) is very
1007
unlikely, and chance is impossible to prove, but evidence for plants as good as that Munday (2004)
1008
was able to obtain for fish would be fascinating. The evidence (chap. 4, sect. 4) on Circular
1009
Interference Networks (4) suggests that the mechanism is likely to be unimportant, or non-existent.
1010
However, better-quality evidence is needed, examining how RGR changes as exclusion by
1011
interference is approached and using the species of a natural community. Evidence for Cyclic
1012
Succession (8) is currently absent. Since Egler’s (1977) diatribe there have been many more
1013
permanent plots set up and these may eventually give evidence for or against it. Temporal and
1014
Spatial Inertia (10) and Interference/Dispersal Tradeoffs (6) are probably all around us, but there is
1015
miniscule evidence for either. Temporal inertia (10.1) is hard to measure, but evidence may come
1016
when a change of environment affects a permanent plot, or that change could be imposed
1017
experimentally. Stoll and Prati (2001) gave neat evidence of spatial inertia (10.2) from a very
1018
artificial system, and evidence from more realistic systems would be useful. However, this is only
1019
an equalising mechanism. Ecologists rarely have any idea how much of the small-scale patchiness
1020
that they see around them is due to Allogenic Disturbance (5), but the research would not be too
1021
hard, with permanent plots in herbaceous communities and using dendrochronology as well as
1022
permanent plots in forests. The main problem in measuring the Spatial Mass Effect (12) is that the
1023
tail of leptokurtic dispersal is hard to quantify. The answer may lie in experiments with adjacent
1024
mesocosms, or mesocosms transplanted into the field as phytometers, but for measuring dispersal
1025
and ecesis, not the environment. We can put together a story on Pest Pressure (3) from separate
1026
pieces of work (chap. 4, sect. 3), at least for pathogens, but more work on applying pesticides to
1027
natural communities would be valuable, with examination of all the processes in a single system to
1028
aid interpretation through the nexus of interactions involved. Allogenic changes imply that
Wilson and Agnew, chapter 6, Theories, page 34 of 41
1029
Environmental Fluctuation (2) has huge impacts on plant communities (chap. 3, sect. 2), but it will
1030
not always meet the strict criteria for permitting coexistence. When data are to hand to parameterise
1031
the models of Chesson (2006) it should be possible to understand this better. How much of the
1032
Alpha-niche Differentiation (1) that can be seen around us is actually causing coexistence is hard to
1033
know. Experiments with treatments preventing niche differentiation would be useful, e.g. using
1034
shallow boxes to prevent differences in rooting depth or long-term growth-cabinet work with and
1035
without seasonal differences.
1036
All these effects have been demonstrated, if at all, in separate studies. The next step is for
1037
them all to be evaluated for one community.
1038
9.4 Heterogeneity
1039
Environments are (almost?) always heterogeneous in space and time, even in apparently
1040
uniform natural communities (e.g. Robertson et al. 1988; Farley and Fitter 1999). The base for
1041
modelling this can be either environmental heterogeneity or environmental homogeneity.
1042
The usual starting point has been underlying spatial heterogeneity, and indeed it is very hard
1043
to escape from such variation. Deserts appear uniform, but have damper depressions and even
1044
dunes. Alluvial flood plains are deceptively homogenous because they receive non-uniform deposits
1045
as rivers meander and even split/rejoin. The deposits are reworked by the original river and then, as
1046
the river cuts lower, by smaller streams. The same is true on saltmarshes. This can be combined
1047
with the certainty that there are differences between species in their environmental tolerances,
1048
which can be determined by experiments and/or inferred from plant/environment distributions (the
1049
“easy task” of Warming 1909). This gives a base model in which environmental heterogeneity
1050
combined with different species tolerances causes community heterogeneity. This is allogenic
1051
heterogeneity. All further investigation of community processes has to sample where allogenic
1052
heterogeneity is minimal and/or allow for it (e.g. in patch models: chap. 5, sect. 2.3).
1053
Alternatively, heterogeneity in vegetation can be explained with a null model of a uniform
1054
underlying environment. ‘Random’ dispersal of species then has to be assumed to give some
1055
pattern. Too little inward dispersal would leave unvegetated gaps and too much would give cover
1056
too uniform to explain the observed heterogeneity, so infiltration invasion must be assumed (chap.
1057
1, sect. 2.3), which conveniently seems to be the norm. The next assumption must be that those
1058
colonists react on their environment, and we gave plenty evidence for this when discussing switches
1059
(chap. 3, sect. 5). Next, species must differ in their reaction. If that reaction is in a direction that
1060
disfavours the present species, the result would be relay floristics with a single homogenous
1061
endpoint (Clements 1916), or just possibly cyclic succession. However, often the reaction of the
1062
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 35 of 41
1063
Types 2-4 the result can be a stable mosaic of different communities. The assumptions under this
1064
model are that community heterogeneity is generated by infiltration invasion and switches, i.e.
1065
autogenic heterogeneity. The creation of autogenic heterogeneity reaches its full development when
1066
a switch produces a mosaic of alternative stable states (chap. 3, sect. 5.6), situations that we believe
1067
are more common than has been realised, although the evidence for them is much more uncommon
1068
than has been realised. Care is needed, though, because most of the switches seem to be one-sided
1069
(Type 1) which cannot give rise to a permanent mosaic (chap. 3, sect. 5.3).
1070
The greatest knowledge gap is the degree to which the species of one pool differ in their
1071
reaction. Effects can readily be seen in the light regime beneath different species, though still much
1072
more is known of species differences in total light transmittance than of changes in spectral
1073
composition. Soil reactions occur much more slowly. It is clear that a few species, such as Calluna
1074
vulgaris (heather) and Sphagnum spp. mosses, differ strongly from their neighbours in their
1075
reactions on pH. Whether differences in reaction are general and especially whether there are
1076
changes in other soil variates is remarkably unknown. Local soil/species correlations can easily be
1077
seen, but distinguishing cause from effect is difficult (but see Pelletier et al. 1999; Ehrenfeld et al.
1078
2001; chap. 4, sect. 1.3 above). Experiments with soil litter bags normally last 2-5 years, rather than
1079
the 50 years that would usually be needed to see the effects, and they usually examine the litter, not
1080
the nearby soil. However, we believe that reaction of plants and litter on the soil environment has
1081
been underestimated as the cause of heterogeneity and we call for people to investigate it. The
1082
urgent need is for documentation of all the steps of a switch from a single system. We commented
1083
(J.B. Wilson and Agnew 1992) that there was then no case where this had been done. Although
1084
further work has been done on switches as those involving goose-grazing / saltmarsh (chap. 3, sect.
1085
5.6), microscopic algae / sediment stability (chap. 3, sect. 5.4.C) and lake turbidity one (chap. 3,
1086
sect. 5.4.E), this remains essentially the situation.
1087
Almost certainly the processes assumed in both the heterogeneity and the homogeneity
1088
starting-point models occur, and do so simultaneously. Yet spatial analysis tends to be rather
1089
uninformative. The reader will have noticed that we have largely ignored species-area curves. This
1090
was not because we forgot about them, but because they seem to shed little light on the structure of
1091
communities, tending to be indirect ways of describing geography. Goodall (1954) argued that if a
1092
community has real existence it should show homogeneity of composition within its boundaries.
1093
This is an interesting, even provocative, challenge. Similar is Whittaker’s idea that his ‘gradient
1094
analysis’ (Fig. 6.1) could identify ‘integrated’ communities. These approaches fail. The existence of
1095
small-scale heterogeneity does not disprove integrated structure, for there is certainly underlying
1096
environmental variation which any community structure, however strong, could surely not
1097
extinguish. F.E. Clements who wrote “the community is a complex organism … greater than the
Wilson and Agnew, chapter 6, Theories, page 36 of 41
1098
sum of its constituent species” (Clements 1935) but also “Practically all vegetation shows more or
1099
less striking differences every few feet” (Weaver and Clements 1929, 6). Neither do sharp
1100
boundaries prove co-evolution; they could well be caused by switches, as supposed by both
1101
Clements and Gleason (section 3 above). On the other hand, continuous variation could represent
1102
strong structure, derived from co-evolution towards coevolution, as it did in Whittaker’s fairy
1103
stories (section 4 above).
1104
9.5 Assembly rules
1105
At one point within this heterogeneity there can be either a stable community (but of course
1106
with continual allogenic change), an alternative stable state, or a seral stage of directional or cyclic
1107
succession (chapter 3). However, our discussion would be little more than natural history were there
1108
not some regularities, or rules, that could be seen in how the states are assembled. Assembly rules
1109
are similar to alternative stable states in that from a pool of species only some combinations are
1110
stable. Alternative stable states are necessarily produced by switches. A switch generally depends
1111
on a considerable degree of reaction, sufficient to make a state stable in the face of all but the more
1112
extreme environmental variation, but it could depend on interactions via heterotrophs or, in theory,
1113
autogenic disturbance (chapter 2). Assembly rules are also caused by reaction, though they can be
1114
much more subtle ones, and small-scale interactions via heterotrophs or autogenic disturbance
1115
cannot be ruled out as the mechanism. Alternative stable states are usually envisaged to exist either
1116
at different times or in different places over scales of hundreds of metres or more. Assembly rules
1117
are envisaged at a small, within-community scale, but this difference cannot be absolute:
1118
Diamond’s (1975) original assembly rules operated between islands up to 1000 km apart. Because
1119
of the difference in scale, instantaneous interactions, such as via light, are quite likely to be causes
1120
of assembly rules, whereas gross changes in soil composition are likely effectors for alternative
1121
stable states. The scope for assembly rules is wider, for example, specifying a relative abundance
1122
distribution (RAD) without specifying the species involved, or specifying guild proportions whilst
1123
leaving open which species of a guild are represented, whereas there will be a limited number of
1124
specified alternative stable states, often only two, each with its own set of environmental conditions
1125
and species.
1126
We ecologists have to be very careful in examining apparent evidence for assembly rules;
1127
there are many traps for the unwary null modeller. Nevertheless, there is overwhelming evidence
1128
that assembly rules do exist (chap. 5), refuting claims to the contrary by Hubbell (2005) and Grime
1129
(2006). The best evidence for assembly rules is from character-based rules. There is a trend in plant
1130
community ecology towards analysing plant communities not by the names of their species but by
1131
the characters of the plants. The beginnings of this awareness of characters at the community level
Wilson and Agnew, chapter 6, Theories, page 37 of 41
1132
are in Jan Barkman’s (1979) concept of vegetation texture. Amongst character-based assembly
1133
rules, some distributional evidence supports guild proportionality, as does the successional study of
1134
Fukami et al. (2005). There is little support from removal experiments, probably because of high
1135
experimental error. The use of a priori guilds has severe limitations and we strongly advocate
1136
seeking intrinsic guilds. The use of texture instead of discrete guilds avoids classification, but does
1137
not avoid the problem of character choice. Methods for the determination of intrinsic texture, i.e.
1138
determining the characters of the species to use by the properties of the communities, remain to be
1139
developed.
1140
The evidence for assembly rules so far comes mainly from herbaceous communities, and the
1141
only comprehensive body of evidence is from the University of Otago Botany Lawn. We would be
1142
cautious about the demonstration of an assembly rule in any single study, but the coherent
1143
conclusions from this site are compelling. The evidence from this and other sites suggests that
1144
canopy relations are important, even in the shortest communities such as lawns, saltmarshes and
1145
sand dunes. This may be partly because of the types of communities that have been examined so
1146
far. It may also reflect a bias towards easily-measured characters, since when Stubbs and Wilson
1147
(2004) utilised wider range of characters in a sand dune community the results implied community
1148
structuring by mode of foraging for water and soil nutrients. The evidence on even-spacing of
1149
flowering implies that phenological niche differentiation is important in restricting species assembly
1150
too, though great care is needed in examining that evidence. However, the failure of roadside
1151
communities to re-assemble in New Zealand (J.B. Wilson et al. 2000b) indicates that the restrictions
1152
on community assembly rules are often weak, and probably that alternative stable states exist (chap.
1153
3, sect. 5.6).
1154
It is difficult to search for assembly rules without knowing what the rules are and when it is
1155
so easy to get negative or invalid results, for example by not using a patch model. But how can
1156
ecologists claim to understand plant communities when they do not know what restrictions there are
1157
on species coexistence, when they occur and where? The future probably lies with character-based
1158
assembly rules, but they must be characters that are carefully selected, not those that happen to be to
1159
hand or are easy to measure, and the selection should towards characters likely to reflect the alpha
1160
niche. The other urgent need in plant assembly rules research is to understand for any particular rule
1161
how it operates, i.e. what reaction in what environmental factor or resource is caused by each
1162
species that limits the ways others associate with it. Alternatively, the assembly rules may be caused
1163
by autogenic disturbance, interactions via heterotrophs, etc. Many types of autogenic disturbance
1164
have been demonstrated, but for few is there evidence as to how frequent they are within and among
1165
plant communities. Interactions via heterotrophs are very likely to cause limitations to community
1166
assembly – assembly rules – but the evidence is frustratingly sparse. There are a few experiments
Wilson and Agnew, chapter 6, Theories, page 38 of 41
1167
on the effects of applying insecticide or fungicide at the community level. More are needed. Many
1168
simply report the effect on species diversity. Careful examination is needed of the cascade of effects
1169
that are caused and their rôle in assembly rules. This mechanism of plant-plant interaction has been
1170
widely mentioned for companion planting, but we found searches of the scientific literature for
1171
evidence almost fruitless.
1172
These assembly rules are based on mechanisms, but the net result is efficiently summarised
1173
in the Community Matrix. Introduced to ecology by May (1972), it was not until c. years later that
1174
anyone bothered obtaining values for a real plant community and comparing that community with
1175
the predictions of the Matrix (Roxburgh and Wilson (2000a, b). A Community Matrix is necessarily
1176
a true description of a community, but only one at an equilibrium and perturbed a very small
1177
amount. More realistic models are needed, parameterised from real communities.
1178
Any assembly rules could be based on either co-evolution or pre-adaptation. Dice (1952)
1179
and Whittaker (1975b) were convinced about co-evolution. One of the strongest advocates of this
1180
was Goodall (1963), who argued that a group of species that grew together in common types of site
1181
would adapt to those site conditions and to each other by “… positive feedback. In this sense the
1182
plant community may sometimes be said with justice to have evolved as a whole”. We believe that
1183
co-evolution between plant species is unlikely, even at the ecotypic level.
1184
One problem is temporal change. The environment and the species pool both change and
1185
equilibrium in a plant community is rare. This would not matter if groups of species moved around
1186
the landscape together, but the pollen record tells us clearly that they have associated in different
1187
ways during this interglacial, and probably in earlier ones (chap. 5, sect. 9). Neither do species
1188
associations stay together on much finer timescales. For example, in Watt’s (1981) records from
1189
Breckland, Erigeron acer (fleabane) first increased with Thymus polytrichus, (= T. drucei, thyme)
1190
then stayed essentially constant as T. polytrichus increased, then decreased as T. polytrichus stayed
1191
constant. Much more analysis of local time/space relations like this is needed.
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).
1192
Wilson and Agnew, chapter 6, Theories, page 39 of 41
1193
Another problem for a co-evolution explanation is spatial change. Since environmental
1194
heterogeneity exists right down to the smallest scales, it is not predictable even within a community
1195
which species a plant will have as a neighbour. Part of this heterogeneity is caused by the reaction
1196
of one plant affecting another: effects between different species, between ramets of the same
1197
species and between modules of the same ramet. The species cannot co-evolve to match all these
1198
different assemblages. An even greater spatial problem is that species normally occur in several
1199
communities and the characters of a whole species cannot co-evolve to be optimal in each (Gleason
1200
1926; Goodall 1966).
1201
Furthermore, we argued in chapter 1 that evolutionary change in plants is often slow. All
1202
this makes co-evolution of species traits impossible in heterogeneous communities, and hardly
1203
likely even within homogenous ones if they existed. Therefore, when assembly rules are found, they
1204
are likely to be due to the assembly of preadapted species, that happen from their evolutionary
1205
history in a variety of contexts to have the right characters for the job. Preadaptation is the key to
1206
community ecology.
1207
9.6 Conclusions
1208
We have emphasised the wide variety of plant-plant interactions that occur. The majority
1209
operate through reaction, including interactions via litter, though others operate via autogenic
1210
disturbance, heterotrophs, or occasionally parasitism. There are many gaps in our knowledge of
1211
these interactions, but the most pressing need is for integrated knowledge of them for even one
1212
community. Reaction must always be present and if it be towards favouring the plants that caused it,
1213
a switch will operate. We see the switch as the supreme process in plant communities. Switches are
1214
not ubiquitous, but they are the necessary cause of persistent autogenic heterogeneity, i.e. of
1215
alternative stable states (ASS). They are also the cause of the more interesting aspects of relay-
1216
floristics succession, viz., delay and acceleration, as well as the alternative pathways that lead to
1217
ASS.
1218
As plant ecology moves beyond Warming’s “easy task” of describing those plant
1219
distributions caused by allogenic heterogeneity, beyond indirect analysis of those descriptions by
1220
tools such as species-area curves and beyond describing succession as a gradient in time, switches
1221
are the key. They are at the heart of both spatial and temporal heterogeneity, which are the primary
1222
objects of plant community study. Erwin Adema, working in Dutch slacks, produced evidence that
1223
a switch was causing ASS, perhaps the best of all terrestrial examples (chap. 3, sect. 5.6), but he has
1224
remained modest about it. Many workers have seen ASS as being common. They may be, but
1225
unless we are credulous the hard evidence for them is vanishingly small (chap. 3, sect. 5.6; Wilson
1226
et al. in press). Elsewhere in the literature there has been hand-waving about alternative stable states
Wilson and Agnew, chapter 6, Theories, page 40 of 41
1227
and diagrams of hysteresis, with minimal consideration of mechanism. Sometimes it has not even
1228
been realised that ASS must be caused by a switch (e.g. Lortie et al. 2004). Often the switch process
1229
envisaged to cause ASS/hysteresis has not been specified, still less has evidence for its operation
1230
been produced. This is especially important because superficially observed ASS and hysteresis
1231
could be due simply to temporal inertia, to plants taking their time about dying. Thus, whilst we
1232
suggest that the importance of switches has been considerably under-estimated, we must also point
1233
out that for almost every example of a possible switch more data are needed before it can be
1234
demonstrated to be operating.
1235
Essentially the same processes, dominated by reaction, operate on a smaller scale with pre-
1236
adapted species as their pawns to give assembly rules. ‘Assembly rules’ was coined by Diamond
1237
(1975), but the concept was implicit in the theoretical work of MacArthur (e.g. MacArthur and
1238
Levins 1967). MacArthur’s assembly-rule concept of limiting similarity appears in every textbook,
1239
yet theory and reality existed in parallel, not touching each other, for c. 20 years before the first
1240
rigorous demonstrations. There have been interesting tests of the limiting similarity concept using
1241
flowering phenology (chap. 5, sect. 6.2), though these studies have many problems. The first
1242
rigorous test with plant functional characters was that of Stubbs and Wilson (2004). Again, the need
1243
is to bring theory and reality together, and to test for several aspects of the structure of one
1244
community, as we have for the Botany Lawn. However, great care is needed with the methods used.
1245
Too often, workers have performed some randomisation, found a difference between the observed
1246
pattern and the randomised one, and declared an assembly rule. Fox’s assembly rule for desert
1247
rodents is a notorious example (Wilson 1995; Simberloff et al. 1999). In order to test for an
1248
assembly rule, one also has to know for which rule one is testing (i.e. the test statistic) and the rule
1249
should be one based on the ways plants function and interact (chaps. 1, 2). It is becoming clear that
1250
the rule should probably be based on plant characters and ideally on abundance too. However,
1251
which characters are critical in causing assembly rules is hardly ever known. We have pioneered
1252
determination of intrinsic guilds from distributional and experimental data as a route to more
1253
appropriate assembly rules, but the characters and thus the processes behind the intrinsic guilds are
1254
yet to be discovered. Methods for determining intrinsic texture have yet to be found, for weighting
1255
the characters of the species by information obtained from the structure of the community itself.
1256
Thus, we emphasise reaction, alternative stable states, switches and assembly-rules, and the
1257
need to obtain hard evidence for them all, bridging the gap that has existed in community ecology
1258
between theory and reality.
Wilson and Agnew, chapter 6, Theories, page 41 of 41
1259
ILLUSTRATIONS
1260
Fig. 6.1: The distribution of species along an environmental gradient: (a) a simplistic version of
1261
Clements, (b) a simplistic version of Gleason, and (c) Whittaker (who needs no
1262
simplification).
1263
Fig. 6.2. Does the same community recur? Comparison of between-site similarities in species
1264
composition with: (a) those between adjacent quadrats, and (b) those between subsites 50 m
1265
apart. From Wilson et al. (1996b).
1266
Fig. 6.3: The C-S-R triangle of Grime (1979).
1267
Fig. 6.5. Fig. 6.4. C-S-R theory and specialist pioneers. Grime suggested that sites with differing
1268
degrees of stress would follow different pathways. - - - indicates the part of the succession
1269
which will probably be slow.
1270
Fig. 6.6: The experimental response to N compared to the rank of species in a successional/N field
1271
gradient.
1272
Fig. 6.7: The effect of nutrient concentration on competitive ability.
1273
Fig. 6.8: Trends in the shoot frequency of Erigeron acer and Thymus polytrichus (= T. drucei,
1274
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
7
test for heterogeneity of slopes on a log-log basis
8
by analysis of covariance, with log of nutrient concentration as the independent variate
9
for a joint residual regressio006E