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1 A field experiment was designed to investigate the relationship between environmental heterogeneity and species diversity in a group of sedges (Cyperaceae: Carex) growing in old-growth forest.
2 A measure of environmental quality, as perceived by the sedges, was obtained from the survival of clonal ramets of 11 species of Carex planted at 10-m intervals along each of three 1-km transect lines.
3 The resident assemblage of sedges was censused along the same three transect lines and along a further 24 km of survey lines in the same forest.
4 The general state of a site was represented by the overall survival of the experimental implants at that site. The general environmental variance between sites provided a measure of environmental heterogeneity. This could be partitioned into a specific variance (mean environmental variance of species) and an environmental covariance. The rate of increase of the general and specific variances with distance between sites reflected environmental structure.
5 The three transects differed in scale. The species diversity of the resident Carex assemblage was correlated with general environmental quality both among and within transects.
6 The three transects differed in structure. The number of resident species, relative to the number expected from the number of individuals sampled, was greatest on the most coarse-grained transect (steepest increase in general environmental variance with distance).
7 Within each transect, species diversity increased with general environmental variance because the specific correlation of performance (correlation among species of survival in pair-wise combinations of sites) decreased as the general environmental variance increased.
8 The effect of specific environmental variance was weaker. Overall survival of a species on the transects was not correlated with its abundance in the forest. Neither the transects nor a targeted implant experiment provided evidence for a close relationship between the distribution of species and the state of the environment.
9 As a general explanation of our results, we propose a ‘marginal-specialist’ model in which the species that dominate the most productive sites also have the broadest ranges, whereas other species are superior in a more restricted range of less productive sites.
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- Materials and methods
The diversity of ecologically similar organisms that live together has for long been a central issue in community ecology. The best adapted species should long ago have replaced all the others, unless the process of replacement through competition is continually obstructed or interrupted. In a heterogeneous environment where patches offer different conditions for growth, or have been disturbed at different times in the past, competitive exclusion is likely to be very slow, and might never reach completion (Palmer 1994). More heterogeneous environments would then be expected to support a greater number of species (Williams 1964), as many studies have reported (see general reviews by Shmida & Wilson 1985; Auerbach & Shmida 1987; Hart & Horwitz 1991; Cornell & Lawton 1992; Shorrocks & Sevenster 1995).
Species diversity seems to be related to the structural complexity of the environment in many different kinds of system. Early work by MacArthur showed that bird species diversity is related to the vertical heterogeneity of the canopy (MacArthur 1958, 1964; Recher 1969). In a rather similar way, the number of species of soil mites increases with the complexity of the soil profile (Anderson 1978). Insect diversity is related to the structural or architectural diversity of their plant hosts (Murdoch et al. 1972; Strong & Levin 1979; Moran 1980), and fish diversity to the structural complexity of aquatic vegetation (Tonn & Magnuson 1982). The number of species of lizard is related to the complexity of the physical environment in desert communities (Pianka 1967). The diversity of the macrobiota, although not the microbiota, of the rocky intertidal is greater at structurally complex sites provided by seaweed holdfasts or clumps of barnacles than on bare rock (Thompson et al. 1996). Structural diversity provided by physical or biotic features is associated with greater diversity of several groups of benthic marine organisms, including microbiota (Pringle 1990), invertebrates (Hewatt 1935) and snails (Kohn 1967). The number of species of freshwater snails also increases with the variety of substrates available (Harman 1972). The number of bird species increases with number of distinct habitats independently of area in islands of a Finnish archipelago (Haila 1983; Haila et al. 1983). The number of species of mammals is greater in western districts of North America, which are topographically more heterogeneous than central and eastern districts (Kerr & Packer 1997). Plant species diversity in the Appalachians increases with the number of distinct communities and the number of mountain peaks in the survey area, suggesting a similar link with topographic and ecological heterogeneity (White & Miller 1988). There is also a certain amount of experimental evidence for the theory. For example, Vivian-Smith (1997) manipulated microtopography in experimental plots and found that hummock–hollow sites supported more diverse plant assemblages than flat surfaces (Silvertown & Wilkin 1983). The relationship between diversity and the heterogeneity created by disturbance has been reviewed at length by Huston (1994).
Not all results are consistent with this view. For example, Nilsson et al. (1988) found no relationship between species diversity and the number of types of habitat for woody plants, carabid beetles and land snails on islands in a Swedish lake. Moreover, there is a pervasive difficulty concerning the spatial scale at which surveys are conducted. Böhning-Gaese (1997) found that bird species diversity around Lake Constance was correlated with habitat diversity only at sampling scales of between 4 and 36 km2, perhaps because such moderate spatial scales correspond with the distances over which the activity or dispersal of the organisms occurs. Less effect of habitat diversity will be seen either at larger scales or at smaller scales where immigration may overwhelm competition. This may be why, in a very careful study of plant communities of 0.1-ha plots in North Carolina forests, Palmer (1991) found that species diversity was related to the mean value of soil nutrients such as magnesium but not to their variance within plots. The appropriate scale for testing the theory must therefore be chosen carefully to be appropriate for the group of organisms being studied.
We aimed to determine the most appropriate measure of environmental heterogeneity, and to evaluate its relationship to species diversity. The simple approach of measuring physical variables such as pH or nitrate concentration (Lechowicz & Bell 1991) has the drawback that patterns of variation in physical factors cannot be translated readily into terms of plant response. Sowing soil cores taken from the forest with genetically uniform material of barley and Arabidopsis (Bell & Lechowicz 1991) allows environmental variation to be described in terms of plant response with great precision, but many of the sources of difference among sites are lost by transferring the soil to the glasshouse bench. A third technique is to take seedlings of native plants from forest sites, raise them in exclosures, cross them to create seed families of known provenance, and then plant the seeds back into the parental site (Schoen et al. 1994). This is satisfactory in principle, although in practice the complications of sexual inheritance and the rapid loss of a large proportion of the seeds or seedlings make it difficult to estimate the state of the environment with great precision. Despite their drawbacks, all three techniques have demonstrated that the forest floor is heterogeneous at a scale of several metres, i.e. that there are appreciable differences between sites 1–50 m apart. Moreover, the first two techniques have demonstrated that the forest floor is structured, i.e. that the variance among sites increases with separation from 1 to about 50 m. The object of this study was to use a bioassay approach to extend our description of the structure of the forest floor to a scale of 1 km, using the results to address the relationship between environmental heterogeneity and species diversity.
A given region supports a set of ecologically equivalent species (in the sense of Bell 1996; species of the same functional kind, in the sense of Huston 1994), the local species pool. We wished to know what determines the total number of species recorded when samples are taken from several sites within this region, and what causes variation in the number of species among sites. Consider any two sites, from which S1 and S2 species, respectively, have been recorded. The number of species occurring in the two sites combined (S12) will be:
- S12 = S1 + S2 - S1S2/N - (N - 1) Cov (Xij, Xik)
where N is the number of species in the local pool. The number of species in each site separately, S1 and S2, is an effect of scale. It depends on the number of individuals collected, and it cannot be analysed further unless the sites can be further subdivided. The final term on the right-hand side is the covariance of occurrence at the two sites among species: Xij is the occurrence of the ith species at site j, and Xik its occurrence at the other site, k. We shall call this the specific covariance; it would be equivalent to a genetic covariance if the species were treated as genotypes within a population. A low, or negative, covariance indicates that the composition of the assemblage at one site is poorly correlated, or negatively correlated, with its composition at another. One interpretation of a low specific covariance of occurrence is that conditions of growth differ at the two sites, some species being well-adapted to the first site and colleagues to the second. The covariance can then be used as a measure of environmental heterogeneity in terms of overall plant response. It can be thought of as quantifying the concept of among-site or beta diversity (Whittaker 1970), so that the decay of the covariance with distance measures the ‘turnover’ of assemblage composition.
There are at least two competing interpretations of how species diversity is maintained in spatially heterogeneous environments, illustrated in the two upper panels of Fig. 1. The x-axis of each diagram represents an environmental gradient of some kind, in this case productivity, so that separation along this axis represents environmental variance. The y-axis represents the performance of a given species. Performance, as used here, is best defined as the rate at which this species increases in frequency in a mixture, but in practice it will usually be defined in terms of the survival, growth or reproduction of isolated plants or pure stands. Although this is often the only practicable approach, it may be inadequate when populations are so dense that individuals of different species compete directly. In the classical ‘niche-separation’ model (Fig. 1a), each species is specialized for thriving in a restricted range of conditions, so that species differ in their mean location along the environmental axis. The height of its distribution at any given point represents the performance of a species at a given state of the environment, and the state to which the species is best adapted is marked by its peak performance. The variance of each distribution is proportional to the ecological range occupied by the species; species do not differ consistently in range, or at least range is not correlated with peak performance. Environmental heterogeneity thus sustains species diversity through local adaptation to qualitatively different conditions of growth at different sites. In contrast, in the ‘rare-generalist’ model all species have their peak performance at the same environmental state (high productivity), but differ in variance; peak performance is negatively correlated with variance, so the species that dominate the most productive sites have narrow ranges. The most productive sites are dominated by the most responsive species, which are best able to exploit favourable conditions of growth, whereas other species are more stable, being able to maintain themselves even in unproductive sites. A third hypothesis, the ‘marginal-specialist’ model, will be discussed later. Recent accounts of ecological specialization and variation in plant assemblages include Sultan et al. (1998) and Svenning (1999).
Figure 1. Three theories of how species are arranged on landscapes. Each curve represents the variation of performance over sites of a given species. (a) Niche-separation model. Each species is specialized to a given range of sites. Mean (or maximal) local abundance of species is uncorrelated with their range (variance). Diversity of sites is uncorrelated with their productivity. (b) Rare-generalist model. Abundance is negatively correlated with range; diversity is positively correlated with productivity. (c) Marginal-specialist model. Abundance is positively correlated with range; diversity is negatively correlated with productivity.
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In both cases, the species–sites interaction of performance is supposed to lead to a process of selection that sorts species into the sites to which they are best adapted, and this causes the observed species–sites interaction of occurrence. Both theories predict that species diversity will increase with the area sampled. This will be in part an effect of scale, because the number of individuals encountered will increase with area, and in part an effect of structure, because environmental variance will increase with area. It is possible to distinguish the two; the ingenious analysis of forest plant communities by Palmer & White (1994), for example, showed that about two-thirds of the overall increase in species diversity with area was a pure scale effect, the remainder being attributable to function. Both theories predict a pure effect of structure independently of scale: the combined species diversity of two sites will increase with their distance apart.
Given an objective measure of environmental heterogeneity, we would be able to evaluate its relationship with species diversity. The niche-separation theory requires a high degree of local adaptation, and therefore predicts that the performance of experimental plants at a site will be correlated with the composition of the local assemblage: a species should occur predominantly at sites where its performance is high, and, conversely, its performance should be exceptionally high in the sites where it occurs. Furthermore, the specific covariance should fall with distance, becoming negative at moderate distances. The rare-generalist theory requires only that species respond differently to the general quality of the environment, and local adaptation may be undetectable because many species have broad ranges and are able to survive almost anywhere. The specific covariance will fall with distance, but will remain positive even at large distances.