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Keywords:

  • competition;
  • herbivory;
  • resource availability;
  • tree seedling establishment

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  • 1
    We studied the establishment of tree seedlings in Mediterranean-type old fields in South Australia in different biotic environments and under different levels of resource availability. Specifically we wanted to: (a) test for a logarithmic relationship between the relative intensity of competition (RCI) and resource availability; (b) assess the potential of confounding resource competition with invertebrate herbivory; and (c) assess whether the architecture of the plant community had any qualitative or quantitative effects upon the relationship between resource availability and RCI.
  • 2
    Our glasshouse experiment showed that RCI increased with resource availability at low levels of resources, but not at higher levels, consistent with a logarithmic relationship.
  • 3
    The effects of resource competition and invertebrate herbivory were heavily confounded in the field experiment.
  • 4
    Plant architecture significantly affected the behaviour and abundance of invertebrates and we therefore conclude that it has the potential to modify the relationship between resource availability and competitive intensity.
  • 5
    Although the habitat templet/C-S-R model appears reasonably robust, modification of its general framework may be required because one of its basic underlying assumptions is most accurate when competition is defined phenomenologically.

Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

The nature of the relationship between resource availability and competitive intensity has been the subject of intense debate (Thompson 1987; Tilman 1987a, 1987b; Thompson & Grime 1988) and numerous empirical tests that yielded contradictory or inconsistent results (Wilson & Lee 2000). We propose that these inconsistencies and controversies result from methodological issues.

One argument states that competition occurs in the most productive and benign habitats (e.g. temperate rainforests), and also in habitats that are subject to high levels of abiotic stress (e.g. artic tundra and deserts), but it is argued that there are qualitative differences (Tilman 1988; also see Newman 1973). Competition for soil resources may predominate in harsh abiotic environments, whereas competition for light is more important in productive habitats. This trade-off is assumed to exist because biomass allocated to root systems cannot be simultaneously allocated to tissues used to acquire light (Tilman 1988). The alternative argument is that competitive intensity reaches a maximum in the most benign habitats with the ability to capture above- and below-ground resources linked by positive feedback (Donald 1958, cited in Grime et al. 1997): access to mineral nutrients results in the ability to build photosynthetic enzymes, which produce energy, which promotes the uptake of mineral nutrients, and so on. Intensity of competition (both root and shoot combined) is therefore expected to increase as a function of resource availability.

The comprehensive review by Aerts & Chapin (2000) on the effects of resource availability on plant structure and function supports some elements of both arguments. An alternative approach is to use removal experiments in which intensity of competition is measured as a function of resource availability, using either natural (standing crop) gradients or artificial resource gradients, but the results are equally inconsistent. One possible reason for these inconsistencies is variation in scale, or range, of resource availability investigated. Belcher et al. (1995), Bonser & Reader (1995) and Foster (1999) all found a logarithmic relationship between standing crop and the relative intensity of competition (RCI), which would not be apparent in studies using a narrow range of resource availability, or only the upper end of the resource gradient (where the log function flattens out). Disturbance and fertility can, however, be confounded on gradients of standing crop (Wilson & Tilman 1991, 1993; Peltzer et al. 1998), which questions the validity of the correlation with RCI. Glasshouse studies of the relationship between RCI and fertilization, such as we present here, avoid such confusion. With the exception of the work by Miller (1996), we are unaware of other studies that have explicitly considered this question.

Removal experiments may also confound resource competition with indirect effects (Tilman 1987b). Citing such studies in support of Grime (1977) implies the acceptance of a ‘non-mechanistic, Lokta-Volterra-based, phenomenological definition of competition’ (Tilman 1987b). According to the best such definition (Shipley et al. 1991), competition occurs when there is a ‘decrease in the fitness of a plant … due to the presence of another plant, without any necessity that the decrease in fitness be due to differential consumption of a limiting resource’. However, indirect effects, such as apparent competition (Connell 1990), can then be confused with resource competition (Tilman 1987a), as when grasses suppress the growth of cacti by attracting/housing invertebrate herbivores (Burger & Louda 1994). Strong correlations are often observed between the biomass of the plant community and the abundance of invertebrate herbivores (Southwood et al. 1988; Bonser & Reader 1995; Strong et al. 2000) and the effects of resource competition and herbivory may therefore be confounded (Reader 1992).

Experimental tests of these arguments have been conducted with a fairly limited range of habitats and life-forms. Examples include aquatic reeds along swamp margins (Wilson & Keddy 1986; Shipley et al. 1991), herb-fields (Belcher et al. 1995; Reader 1990), old-fields (Wilson & Tilman 1991, 1993; Reader et al. 1994) and grasslands (Peltzer et al. 1998). We only found a single comparative study of the relationship between resource availability and competition in prairie and forest (Wilson 1993). Plant architecture affects the invertebrate community (Lawton 1983) and the effects of ‘competition’ from trees/shrubs and grasses/herbs may be quantitatively and qualitatively different along gradients of natural productivity, where the spectrum of life-forms often changes dramatically.

We have three main objectives: (a) to assess whether there is a logarithmic relationship between competitive intensity and resource availability; (b) to ascertain if there is any potential for confounding the effects of competition and herbivory in a field experiment; and (c) to determine whether changing the identity (life-form) of competing vegetation (shrubs vs. grasses) could affect the relationship between experimentally manipulated resource availability and competitive intensity (phenomenologically defined).

Methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

study site

The field study was carried out in an old-field dominated by exotic annuals (mainly Avena barbata, bearded oat), within the Waite Hills Reserve (138°44′ E, 34°61′ N), in the foothills of the Mount Lofty Ranges (South Australia). The climate in this region is Mediterranean, with wet cool winters and hot dry summers. The mean annual rainfall is 690 mm, with 80% of the rain falling during April–October (autumn to spring). The average maximum temperature is 12.9 °C in winter (June to August) and 26.8 °C in the summer (December to February).

The study was conducted in the relatively rich alluvial soil found at the base of the slopes. The original community was an eucalypt savannah with 20–30 m tall trees (Kraehenbuehl 1996), including Eucalyptus camaldulensis, E. microcarpa and Allocasuarina verticillata, and an understorey dominated by native perennial bunch grasses, such as Themeda triandra (kangaroo grass), Austrodanthonia sps. (wallaby grass) and Austrostipa spp. (spear grass). Severe degradation following pastoral use has favoured exotic annuals, such as Avena barbata (bearded oat), Briza maxima (large quaking grass), Vulpia myuros (silver grass) and clovers, over the native grasses. The natural history of the region is discussed at greater length in Twidale et al. (1976).

glasshouse experiment

We collected E. camaldulensis seeds from the Waite Hills Reserve in the spring of 1998 and sprinkled 0.5 g of seed/chaff mixture onto 2-L pots (n = 60) filled with low-nutrient potting mix. These pots were watered with overhead misters for 3 minutes every day. We used a factorial design to measure the effect of density of an exotic species (A. barbata) and fertilization, as well as the interaction between these factors, on the emergence, survival and biomass of E. camaldulensis. The experiment ran between February and July 1999. We fertilized 20 pots with Native Osmocote™. (Scotts Pty. Ltd, Australia) at the recommended rate (1 kg 25 m−2, i.e. 3 g pot−1), fertilized 20 pots at half that rate and left 20 pots unfertilized. At each level of fertility, E. camaldulensis seedlings were grown with or without competition from A. barbata, resulting in 10 replicates for each treatment combination.

Density of A. barbata was similar to that observed in the field. We collected the top 3 cm of soil (containing the bulk of the soil seed bank, see Facelli 1994) from an old-field at Waite Hills Reserve and calculated that 450 g would be required to fill our experimental pots to a depth of 3 cm. We then extracted A. barbata seeds from 450-g portions of soil and added them to pots that were assigned to competition treatments. The pots were randomly placed in a glasshouse.

We counted all the E. camaldulensis seedlings that emerged in each pot. The first five were marked with wooden skewers and used to measure mortality and biomass: all subsequent emergent seedlings were removed to avoid intraspecific competition. At the end of the experiment we harvested above-ground biomass of A. barbata and the combined above- and below-ground biomass of eucalypt seedlings and oven dried the material for 3 days at 80 °C.

We used a one-way anova to determine whether the application of fertiliser affected the above-ground biomass of A. barbata and used a Tukey-Kramer HSD test for post-hoc comparisons. We used a two-way anova to analyse the effect of fertility, A. barbata density and their interaction upon emergence, biomass and survival of E. camaldulensis, and Tukey-Kramer HSD test for post-hoc comparisons. In addition, we calculated the relative intensity of competition (RCI) of E. camaldulensis and A. barbata at three levels of fertility, using biomass and survival data.

RCI was calculated as

  • RCI = (BNC − BC)/BNC

where BNC and BC, respectively, are the biomass (the mean weight of the surviving seedlings in each pot) or survival (the percentage of the five seedlings that survived in each pot) of the target species in pots without and with competition (see Sammul et al. 2000). Replicate values were obtained by random pairing of each competition pot with one where there was no competition. We analysed these ratios with anova and Tukey-Kramer HSD tests.

field experiment

We investigated the effect of ‘biological neighbourhoods’ (microhabitats represented by the identity of the competitor, four treatments), nutrient addition (two levels) and their interaction on establishment of Allocasuarina verticillata and Eucalyptus camaldulensis. Plots (1 m2) contained either exotic grasses (W, weeds), Acacia pycnantha (AP, a tall, relatively short lived shrub that commonly establishes after fires), Themeda triandra (TT, a native bunch grass that used to dominate these grassy woodlands), or no vegetation (NW, no weeds). Before planting A. pycnantha and T. triandra, we treated the plots with glyphosate (roundup©) to facilitate establishment. Seedlings of A. pycnantha were purchased from Provenance Seeds (Semaphore, South Australia) and planted in the field in May 1998. Themeda triandra seed, donated by Andrew Crompton (Burnside City Council, South Australia) and germinated in a constant environment cabinet in June 1998, was grown in commercial seedling tubes, in a shade house, until transplanted into the field at the end of winter 1999. Throughout the experiment we used glyphosate each spring and autumn to control exotic grasses in the 1-m buffer strips that surrounded each plot and hand weeded plots with A. pycnantha, T. triandra and no vegetation three times a year: plots with exotic grasses were left un-weeded. During the summer of 1999/2000 we watered plots with A. pycnantha and T. triandra once a month to ensure good establishment, prior to starting the experiment in May 2000.

We used a randomised, complete block experimental design. There were 10 blocks, each containing one replicate of the four biological neighbourhoods, with five receiving additional resources (water at 10 L m−2, once a month from October to March, and Native Osmocote fertiliser twice a year at the recommended horticultural rate of 40 g m−2) and five untreated controls. Each block was orientated on a north–south axis, and the order of the biological neighbourhoods was randomised within each block. We planted three A. verticillata and two E. camaldulensis seedlings in each plot on 23 May 2000.

We measured the performance of the tree seedlings on 13 September (spring). Allocasuarina verticillata seedlings have photosynthetic organs analogous to pine needles, and we had intended to measure the number and length of these. However, seedlings were still very small at the first census and, as it was apparent that invertebrate herbivores would have a major influence upon the results of this study, we assessed only survival at this stage, to avoid disturbing the experimental plots. We counted survival of E. camaldulensis seedlings, the number of leaves, and the number of leaves that had been damaged by herbivores. We also deployed a pitfall trap (a 300-mL plastic cup buried to the rim and filled with 30% ethanol) in the centre of each plot between 10 and 13 September At the second census (23 March 2001, end of summer) we assessed survival of E. camaldulensis and A. verticillata seedlings and measured the above-ground biomass of those surviving following harvest and oven drying at 80 °C for 48 hours.

statistical analyses

Survival at the first census was only analysed for A. verticillata as all E. camaldulensis seedlings survived. Two-way anova was used with fertility and biological neighbourhood as factors. We also used two-way anova to determine whether fertility, biological neighbourhood or their interaction affected the number of leaves on E. camaldulensis seedlings or the number damaged by herbivores. Because biological neighbourhood significantly affected leaf number (see below), percentage of damaged leaves (on each seedling) was used to analyse leaf damage. This measure is extremely conservative because leaves that have been completely destroyed by herbivores do not contribute to the total. We analysed the effect of fertility and biological neighbourhood upon the abundance of each type of invertebrate in the pitfall traps with a two-way anova; statistical comparisons were not made between different invertebrates. If an anova was significant, a Tukey-Kramer HSD test was used for the post-hoc comparison. Data were not always normally distributed, and some of the frequency distributions were slightly skewed. However, we did not use transformations because anova is reasonably robust to such marginal departure from its assumptions (Underwood 1997).

Survival and above-ground biomass of E. camaldulensis and A. verticillata seedlings at the second census was analysed using two-way anova, with fertility and biological neighbourhood as factors and Tukey-Kramer HSD tests for post-hoc comparison. Statistical comparisons were not made between E. camaldulensis and A. verticillata.

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

glasshouse experiment

The application of fertiliser increased the biomass of A. barbata (Table 1, Fig. 1a). Increasing the density of Avena barbata resulted in lower levels of emergence and survival for E. camaldulensis (Fig. 1b,c, Table 1). Fertility, and the interaction of A. barbata density and fertility, had no effect upon eucalypt emergence or survival but both significantly affected the growth (final biomass) of E. camaldulensis seedlings (Table 1). Density of A. barbata affected final biomass in pots with fertiliser, where it caused a significant reduction in the growth of E. camaldulensis seedlings (Table 1, Fig. 1d). When biomass data were used to calculate RCI, increased fertility resulted in more intense competition (Fig. 1e), but no effect was detected when survival data were used (Table 1).

Table 1.  Summary statistics for anovas performed on plant attribute data from the glasshouse experiment
Source of variationd.f.SSFPr > f
  • *

    Factors significant at P < 0.05.

Avena (weed) biomass
 Fertility 2 744.65 61.340.0001*
 Error24 145.66  
Eucalyptus camaldulensis: emergence
 Fertility 2 485.91  1.440.25
 Avena density 12308.84  6.840.003*
 Fertility × Density 2 902.35  1.340.27
 Error39 607.2  
E. camaldulensis: survival
 Fertility 2   6.82  1.580.2174
 Avena density 1  40 18.610.0001*
 Fertility × Density 2   4.86  1.130.3326
 Error39  83.8  
E. camaldulensis: biomass (with three levels of fertility)
 Fertility 2  42.7 33.880.0001*
 Avena density 1  86.27136.630.0001*
 Fertility × Density 2  42.77 33.870.0001*
 Error39  24.62  
RCI of Avena and E. camaldulensis seedlings
 RCI calculated with biomass data
  Fertility 2   1.56 11.870.0014*
  Error12   0.79  
 RCI calculated with survival data
  Fertility 2   0.641  2.30.1347
  Error12   1.61  
image

Figure 1. Interactive effects of resource availability and competition (glasshouse experiment). Resource availability 1, 0.5 and 0 represent fertiliser applied at 40 g m−2, 20 g m−2 and no fertiliser. (a) The effect of fertiliser application upon Avena barbata biomass and (b) number of emergent E. camaldulensis per pot, in response to increasing densities of A. barbata: for each level n = 30. (c) The number of surviving E. camaldulensis seedlings per pot as a function of A. barbata density, (d) biomass of E. camaldulensis seedlings, at three levels of soil fertility and two levels of A. barbata density, and (e) RIC of A. barbata and E. camaldulensis, calculated with biomass data. All data were analysed with anova and Tukey-Kramer HSD test (see Table 1): levels with the same letter are not significantly different.

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field experiment

Spring census, 2000

Allocasuarina verticillata survival was lower in plots with exotic grasses than in plots without vegetation or plots with A. pycnantha. However, survival in plots with T. triandra was not significantly different from survival in plots with exotic grasses, no vegetation or A. pycnantha (Table 2, Fig. 2a). Fertility and the interaction of fertility and biological neighbourhood did not affect A. verticillata survival (Table 2).

Table 2.  Summary statistics for anovas performed on plant attribute data. Data from the field experiment, spring census (September 2000). BN = biological neighbourhood
Source of variationd.f.SSFPr > f
  • *

    Factors significant at P < 0.05.

Allocasuarina verticillata: survival
 Fertility 1   0.136 1.710.1991
 BN 3   2.3810.040.0001*
 Fertility × BN 3   0.097 0.04090.7473
 Error72   2.53  
E. camaldulensis: leaf number
 Fertility 1   8.45 0.1350.7143
 BN 3 863.35 4.590.0053*
 Fertility × BN 3 260.55 1.380.2534
 Error724505.6  
Percentage of E. camaldulensis leaves with damage
 Fertility 1   0.0462 1.220.273
 BN 3   1.9617.20.0000*
 Fertility × BN 3   0.678 5.960.0011*
 Error72   2.72  
image

Figure 2. Results from the census 3 months after the tree seedlings had been planted in the field experiment (spring 2000): see Tables 2 and 3 for anova statistics. Columns with the same letter are not significantly different (Tukey-Kramer HSD test). (a) The proportion of Allocasuarina verticillata seedlings alive after 3 months. AP = Acacia pycnantha, NW = no weeds, W = weeds (exotic grasses), and TT = Themeda triandra. NF = no additional fertiliser/water, and F = addition of fertiliser and water. (b) Mean number of leaves on Eucalyptus camaldulensis (Redgum) seedlings, (c) proportion of E. camaldulensis leaves with evidence of insect herbivory, and (d) abundance of invertebrates in relation to microhabitat (biological neighbourhood).

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Neither fertility nor its interaction with biological neighbourhood affected the number of leaves on E. camaldulensis seedlings (Table 2). However, E. camaldulensis seedlings growing in plots with exotic grasses or T. triandra had fewer leaves than those in plots with A. pycnantha or no vegetation (Fig. 2b). The proportion of leaves on E. camaldulensis seedlings with evidence of insect damage was significantly affected by biological neighbourhood, and the interaction of fertility and biological neighbourhood, but not by fertility alone (see Table 2, Fig. 2c). Insect damage was highest in plots with exotic pasture grasses and T. triandra (Fig. 2c).

The abundance of invertebrates was never significantly affected by fertility, or its interaction with biological neighbourhood (Table 3), although biological neighbourhood significantly affected the abundance of some groups. For example, there were more spiders in plots with A. pycnantha than there were in plots with exotic pasture grasses or T. triandra (Fig. 2d). Ants were more abundant in plots with A. pycnantha than in plots with no vegetation, exotic pasture grasses (weeds) and T. triandra (Fig. 2d). There were more molluscs (slugs) in plots with exotic grasses than in any other type of plot, more Ommatoiulus moreleti (Portuguese millipedes) in plots with A. pycnantha than there were in plots with T. triandra, and there were more collembolans in plots with no vegetation and A. pycnantha than there were in plots with exotic grasses and T. triandra (see Table 3, Fig. 2d).

Table 3.  Summary statistics for anovas performed on the abundance of invertebrates: spring census (September 2000). BN = biological neighbourhood
Source of variationd.f.SSFPr > f
  • *

    Indicates factors significant at the 0.05 level.

Spiders
 Fertility 1     1.65  0.850.3628
 BN 3    38  6.550.0015*
 Fertility × BN 3     0.65  0.110.9524
 Error31    59.9  
Ants
 Fertility 1    56.69  0.9660.333
 BN 3  2271 13.370.0000*
 Fertility × BN 3   173  1.020.3956
 Error31  1755  
Slugs
 Fertility 1     0.218  0.0980.755
 BN 3    95.22 14.380.000*
 Fertility × BN 3     9.45  1.420.2532
 Error31    68.4  
Millipedes
 Fertility 1    19.69  1.540.2231
 BN 3   141.09  3.690.0221*
 Fertility × BN 3    79.26  2.070.124
 Error31   395  
Collembola
 Fertility 1    19  0.7350.3976
 BN 313 387172.740.000*
 Fertility × BN 3    33.44  0.43150.7319
 Error31   800.8  
Dermaptera
 Fertility 1     4.89  0.0560.813
 BN 3     9.22  0.9580.424
 Fertility × BN 3     3.65  1.80.16
 Error31    52.8  
Caterpillars
 Fertility 1     0  01
 BN 3     1.35  2.050.126
 Fertility × BN 3     0.2  0.3030.822
 Error31     6.8  
Slaters
 Fertility 1     1.104  0.0840.7737
 BN 3    53.69  1.360.272
 Fertility × BN 3    29.05  0.7370.537
 Error31   407.1  
Worms
 Fertility 1     8.29  1.690.202
 BN 3    38.41  2.620.068
 Fertility × BN 3     5.29  0.3610.781
 Error31   151.4  
Beetles
 Fertility 1     0.218  1.40.244
 BN 3     0.474  1.020.3967
 Fertility × BN 3     0.84  1.80.1662
 Error31     4.8  
Flying insects
 Fertility 1     1.02  1.080.306
 BN 3     4.06  1.430.252
 Fertility × BN 3     1.82  0.64270.593
 Error31    29.4  
End of summer census, 2001

Biological neighbourhood, fertility and their interaction all affected the biomass of E. camaldulensis seedlings (Table 4). Eucalyptus camaldulensis seedlings growing in fertile plots without competition attained higher levels of biomass than seedlings growing in plots with any other combination of fertility and biological neighbourhood (Fig. 3a). Survival of E. camaldulensis seedlings was affected by biological neighbourhood but not by fertility or their interaction. Survival was lowest in plots with exotic grasses, intermediate in plots with T. triandra, and highest in plots with A. pycnantha or no vegetation (Table 4, Fig. 3b).

Table 4.  Summary statistics for anovas performed on plant attribute data. Data from the field experiment (summer census, March 2001). BN = biological neighbourhood
Source of variationd.f.SSFPr > f
  • *

    Indicates factors significant at the 0.05 level.

E. camaldulensis
 Biomass
  Fertility 1 4605.4 8.340.0069*
  BN 336559.322.090.0000*
  Fertility × BN 314592 8.810.0002*
  Error3217649.6  
 Survival
  Fertility 1    0.625 2.170.1501
  BN 3   23.47527.20.0000*
  Fertility × BN 3    0.675 0.780.5124
  Error32    9.2  
Allocasuarina verticillata
 Biomass
  Fertility 1    5.93 3.250.0806
  BN 3   99.2318.140.0000*
  Fertility × BN 3   19.04 3.480.0270*
  Error32   58.32  
 Survival
  Fertility 1    0.225 0.90.3499
  BN 3   55.2773.70.0000*
  Fertility × BN 3    0.275 0.3660.7775
  Error32    8  
image

Figure 3. Results from the census at the end of summer (March 2001): see Table 4 for anova details, columns with the same letter are not significantly different. (a) Biomass and (b) survival of E. camaldulensis; (c) biomass and (d) survival of A. verticillata. Abbreviations as in Fig. 2.

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Biological neighbourhood and its interaction with fertility both influenced the growth of A. verticillata seedlings, but the effect of fertility was marginally non-significant anova (Table 4). Allocasuarina verticillata seedlings growing in fertile plots without competition achieved higher levels of biomass than seedlings in any other treatment combination (Fig. 3c). Survival of A. verticillata seedlings was affected only by biological neighbourhood: none survived in plots with exotic grasses or T. triandra, whereas significant numbers survived in the plots with A. pycnantha and no vegetation (Table 4, Fig. 3d).

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

In contrast to many studies that have used artificial resource gradients (Goldberg & Barton 1992), our results are consistent with the unified concept of competition, closely mirroring those of Reader (1990). Without additional resources (i.e. in unfertilized pots and unfertilized/unwatered plots), the absence of competitors did not benefit tree seedlings. Thus competition was constrained by low nutrient supply both in the glasshouse (where we were able to measure both above- and below-ground biomass of eucalypt seedlings) and in the field (where we were restricted to measuring aerial biomass). Thus, whilst our results cannot falsify the argument that there is a trade-off between root and shoot competition, they provide strong support for the argument that the overall intensity of competitive interactions reaches a maximum in fertile habitats.

However, the variable used to assess competitive effects influences the outcome of the analyses: when survival (rather than biomass) data are used the relationship between resource availability and competitive intensity appears to be neutral (zero slope), as predicted by Newman (1973) and Tilman (1988). Reader (1990), Berkowitz et al. (1995) and Sammul et al. (2000) also found that the choice of dependent variable has significant implications. This problem could be resolved by using a mathematical function that includes more than one demographic parameter, as developed for instance in McPeek & Peckarsky (1998), although their model is not easy to generalize because it must be tailored to the life history of the species under study. However, because of the modular construction of vegetation, biomass is often an excellent indicator of plant fitness (e.g. Molofsky et al. 2000) and multiple parameter models may not be necessary. Some of the surviving E. camaldulensis seedlings in the plots with T. triandra had only one or two leaves left, and invertebrates had eaten 75% of each remaining leaf: their poor condition is apparent from their biomass, but not from survival data. Similarly, comparable numbers of tree seedlings survived in plots with Acacia pycnantha and no vegetation, and fertility had no effect upon survival, although E. camaldulensis seedlings in plots with no vegetation and additional resources were, on average, four times as large as those in unfertilized plots with no vegetation, and 12 times as large as in plots with A. pycnantha. We therefore conclude that biomass data, at least in this instance, are more meaningful and that increased resource availability resulted in more intense competition. This conclusion is supported by the correlation between seedling size and probability of survivorship reported by Sarukhán et al. (1984).

Previous field studies demonstrated a logarithmic relationship between standing crop and RCI (Reader et al. 1994; Belcher et al. 1995; Bonser & Reader 1995; Foster 1999). However, the argument that failure to detect a positive correlation between fertility and RCI may result from the use of a narrow range of fertility levels, and/or the use of fertility levels in the upper regions of the relevant gradient, where the log function flattens out, is seriously weakened because the effects of disturbance and resource availability can be confounded on gradients of standing crop (Wilson & Tilman 1991, 1993; Peltzer et al. 1998). As our glasshouse experiment used an artificial resource availability gradient, and there was no disturbance, we can assert with confidence that RCI increased substantially between the lowest and the intermediate resource level but barely, if at all, between the intermediate and the highest resource availability. This is consistent with a logarithmic response of RCI to resource availability.

Our results suggest that the effects of resource competition and herbivory can be heavily confounded, as previously reported (e.g. Southwood et al. 1988; Reader 1992; Burger & Louda 1994; Cebrián & Duarte 1994; Berkowitz et al. 1995; Bonser & Reader 1995; Strong et al. 2000; Groner & Ayal 2001; Scheidel & Bruelheide 2001). Although the leaf damage data suggest that the main mode of suppression may have been herbivory rather than competition, tree seedlings in the plots with Acacia pycnantha were only lightly grazed, and hence their reduced growth (an effect that increased with resource availability) was probably caused by resource competition. Regardless of the mechanism (invertebrate herbivory or resource competition) that limited the establishment of tree seedlings, the same underlying outcome was always apparent, i.e. additional growth was not possible without additional resources.

Because the effects of herbivores and resource competition in the field were correlated, the unified concept of competition was best supported when competition was defined phenomenologically. In the original C-S-R model (Grime 1977), herbivory was considered to be a form of disturbance, as was any factor that caused the partial or total destruction of biomass. Because the effects of resource competition and invertebrate herbivory are so closely associated, and are often confounded in experiments, it may be more appropriate to adopt a phenomenological definition of the interaction, and to group these processes under a single banner (e.g. interference), as suggested in the Southwood-Greenslade habitat templet (Southwood 1988). Studies that have assessed the relationship between RCI and resource availability using removal experiments on natural (standing crop) gradients may have measured the combined effects of invertebrate herbivory and competition, rather than resource competition alone. This may in part explain the observation by Goldberg & Barton (1992) that studies with natural gradients generally support the UCC, whereas studies with artificial resource gradients generally refute it. It also validates one of Tilman's (1987a) main objections to the C-S-R model: indirect effects are extremely easy to confuse with resource competition in removal type experiments. This observation highlights the value of continually revising and modifying the general framework (see Southwood 1988; Pickett et al. 1994).

Our results also indicate an important effect of biotic neighbourhood, or ‘plant architecture’ (Lawton 1983). The four neighbourhoods created harboured vastly different assemblages of invertebrates, resulting from different physical microenvironments or different food availability. The fact that plants can modify the environment is well established (Jones et al. 1994). The effects of competition from A. pycnantha were minimal in comparison with the negative effects of the grasses, and the correlation of the distribution and abundance of invertebrates with this pattern further supports the argument that competition should be defined, or at least considered, in a phenomenological sense for the purposes of the habitat templet/C-S-R model.

Many studies have tested whether competitive intensity and resource availability are correlated. Here the intensity of competition could be related to the effects of fertility, or to the size and abundance (biomass) of the neighbouring vegetation. Although we did not harvest the competitors at the end of the experiment, it was clear that biomass of the four A. pycnantha individuals, which were over 2 m tall by the end of the experiment, dwarfed that of both T. triandra and weeds (Fig. 4). We therefore conclude that the extent to which neighbouring vegetation inhibited the growth of tree seedlings was related to architecture of the neighbouring vegetation rather than the quantity of biomass.

image

Figure 4. Photographs of field plots showing how biomass of Acacia pycnantha (top photograph, centre) dwarfs that of exotic pasture grasses (top photograph, right end) and Themeda triandra (bottom photograph) planted as biological neighbourhood. The plants had been established 2 years prior to the introduction of the target species.

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Our results are consistent with a recent meta-analysis (Langellotto & Denno 2004) suggesting that reductions in habitat complexity may cause a large decrease in natural enemy abundance. While litter has been implicated as one of the principal causes of this pattern, we observed very little litter accumulation. The high abundance of invertebrate herbivores in the plots with exotic grasses and T. triandra may have been attributable to several factors, including better protection against harsh, desiccating physical conditions, reduced abundances of invertebrate predators (e.g. ants and spiders) and/or a reduction in the foraging efficiency of predators such as birds (see Groner & Ayal 2001). It should also be noted that there was a low abundance of collembolans in the plots with exotic grasses and T. triandra. Collembola may be an important component in the diet of ants (Wilson 1959). Their relatively high abundance in the plots with A. pycnantha and no vegetation may have sustained the large number of predatory ants found there. It is also possible that higher C : N ratios in grasses (Elser et al. 2000) affected the growth efficiency of herbivores, resulting in low levels of predation.

The argument that habitats with a high abundance of resources should sustain high levels of competition was supported both in the glasshouse, where we were able to study competitive intensity as a function of resource availability without the natural variability characteristic of ecological systems, and in the field, although the effects of resource competition and invertebrate herbivory were then heavily confounded. We therefore conclude that a phenomenological definition of competition is most tractable and also suggest that habitat complexity should be the focus of future research, as it may provide insight into the durational stability (disturbance) component of the habitat templet/C-S-R model.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Our thanks to George Ganf (the very best devil's advocate), Wendy Stubbs, Kristian Hodgson, Tanja Lenz, Andrew Barritt, Andrew Crompton, Jennifer Gardiner, Dudley Pinnock and Jane Prider. Sincere thanks to the anonymous referees, and to the editors Lindsay Haddon and Jacob Weiner. Thanks to Peter Chesson for discussions on herbivory and to the Australian Research Council for providing a PhD scholarship.

References

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
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