1. Limiting conditions
One of the goals of the quantitative analysis presented in section V is to find a classification that might be helpful as a basis for prediction of changes in natural vegetations. Will C3 species expand relative to C4 species, and will fast-growing species thrive at the cost of slow-growing ones? There are a number of complications to which we briefly would like to draw the attention. First, the analysis in section V is carried out with species that were grown under more or less ‘optimal’ conditions. This will allow most plants to show their maximal response to CO2, without environmental constraints or stresses. In a natural environment conditions will generally be less favourable. Poorter & Pérez-Soba (2001) reviewed the CO2 response of isolated plants when grown under a variety of stresses. Table 4 gives the average BER of C3 species in the close-to-optimal situation as well as in the case that a given environmental factor causes biomass to be reduced by 50% at control levels of CO2. For most of these factors (irradiance, water, salinity, UV-B) changes in BER are small. Interactions are more substantial in ozone-stressed plants, for which BER is strongly promoted, and for cold- or nutrient stressed plants, where the BER is clearly lower than for plants grown at close-to-optimal conditions. In most natural environments nutrient availability will be low, so purely on that basis we expect the response under those conditions to be small.
Table 4. Average biomass enhancement ratio (BER) of environmentally stressed C3 plants as compared to those of relatively unstressed plants. For each environmental factor it was calculated how the BER would be if the stress factor reduced growth of the 350 µl l −1 plants by 50% when compared with the ‘optimal’ conditions. After Fig. 6 of Poorter & Pérez-Soba (2001 ).
|Environmental stress factor||BER|
|Low Water availability||1.51|
2. Competition versus isolated plants
The second factor that makes a difference between most laboratory experiments and the field is that plants in the lab often grow without any mutual interference at the leaf or root level. This implies that an extra investment in leaves or roots can immediately pay off in the form of extra carbon and nutrient capture, which will, in the absence of sink limitation, result in an extra stimulation in growth. The situation is different when plants are grown together. At low density, total biomass of a monoculture will increase linearly with density, but as crowding becomes stronger the biomass of the stand saturates to a maximum level, with only very limited space for each individual. Under crowded conditions, extra leaf area will not necessarily lead to extra carbon gain. Since both the threshold density and the slope vary among species, the simplest comparison is the biomass of isolated plants with those in crowded monocultures. Under those conditions, woody and herbaceous species are generally responding less to elevated CO2 than individually grown plants (Du Cloux et al., 1987; Wayne & Bazzaz, 1995; Retuerto et al., 1996; Navas et al., 1999). Taken over a range of experiments, no correlation was found between the response of a species grown in isolation and in monoculture (Fig. 8a, r2 = 0.06).
Figure 8. (a) Biomass enhancement ratio (BER) of plants grown in a monoculture plotted against the BER of isolated plants ( r = −0.25, n = 27, P > 0.2). (b) BER of plants grown in a mixed culture of plants plotted against the BER of isolated plants ( r = 0.04, n = 33, P > 0.8). (c) BER of plants grown in a mixture of plants plotted against the BER of plants in monoculture ( r = 0.58, n = 50, P < 0.001). The dotted line indicates a 1:1 relationship. Literature used for the analyses are listed in Appendix 5. Three species that represented less than 5% of the total biomass of the mixture at control levels of CO 2 were excluded from the analysis. Their effect on the analysis was negligible.
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The next level of complexity comes in when mixed stands are analysed. The response to elevated CO2 of a particular species will then not only depend on its own physiological and morphological characteristics, but is also determined by the secondary interactions that arise with the other species that are competing for the same resources (Firbank & Watkinson, 1990). Therefore, the correlation between the BER of a given species grown in isolation and in competition with other species can be expected to be even lower as the one between isolated plants and monocultures, and this happens to be the case (Fig. 8b, r2 = 0.00). The most unpredictable step appears to be the transition from isolated plants to monocultures. The second step, from monostands to mixed stands, shows a much better correlation (Fig. 8c, r2 = 0.33), confirming a previous study by Navas et al. (1999) on artificial herbaceous communities. Therefore, we conclude that any prediction of species responses in a vegetation would be better off with growth analyses at the stand level than at the level of the individual.
3. Functional groups
Alternatively, we could use published competition experiments, to test whether specific groups of plants profit more than others. A good example is shown in Fig. 9, where results of Winter & Lovelock (1999) and Lovelock et al. (1998) are combined. They grew isolated seedlings of nine tropical tree species in open top chambers at ambient and elevated CO2, and found a stronger response for the fast-growing pioneer species as compared to the slow-growing climax species. This is in agreement with the conclusions of section V. However, when almost the same set of plant species was grown in competition, BER values for all species ranged around 1, with no difference between species that responded strongly or weakly in isolation. Another example of a very poor correlation between the prediction for isolated plants and those in competition are experiments in a calcareous grassland vegetation. The species that showed the strongest growth response, both in the field as in the lab was Carex flacca (Leadley & Körner, 1996; Stöcklin & Körner, 1999), a species with a very low potential growth rate (Van der Werf et al., 1993).
Is it possible to discriminate between groups of species that form ‘winners’ and ‘losers’ in competitive situations? An extended review is given by Reynolds (1996). Similarly as for isolated plants we analysed a number of competition experiments retrospectively for differences in response between functional groups of species. To this end, we used the BER of the whole artificial or natural vegetation as a calibration point. For each species of the mixture we calculated the BER of that species, and divided it by the BER value of the whole vegetation. If this ratio is higher than 1.0 the species is profiting disproportionately and is designated as a ‘winner’. If the ratio is lower than 1.0 the plant would lose out compared to the whole vegetation. On the one hand, it may be naive to test for such a general response for a given group of species, as competition will strongly depend on the competing species that are present, as well as the specific environmental conditions. On the other hand, small differences between species that are hardly of relevance for plants grown in isolation can be of crucial importance in a competitive situation and may magnify differences in response between species. We felt it appropriate to formally test for these winners and losers anyway. We restricted our analysis to competition experiments carried out with herbs, as most of the work in this field has concentrated on this group, but excluded a-priori those species from the analysis that represented less than 2% of the total biomass of the vegetation, as the behaviour of these plants may be erratic if only a few individuals are present. Finally, given the strong difference in response of nutrient-rich and nutrient-stressed plants (Table 4), we classified experiments as carried out under either high or low nutrient conditions. A classical problem in this case is that the observations on different species within a competition experiment are definitely not independent of each other. A very conservative solution is to use only one species per experiment. This would have resulted in a serious loss of information, an aspect we considered more problematic than statistical independence (Gurevitch et al., 2001).
The results are shown in Table 5. As in section V, we analysed the differences both as simple contrasts and in a multiple regression. For experiments with high nutrient levels, the only significant difference found was between C3 and C4 species, with C4 species being the losers at elevated CO2. However, the number of observations for C4 species is rather low (< 15). The difference remains significant in the multiple regression analysis and is in line with the difference we have seen between C3 and C4 species at the individual plant level (Fig. 6). By contrast with the observations at the individual plant level, fast- and slow-growing species respond exactly similar to elevated CO2 under competition. Again, the number of species in one of the categories is low, but as it is in accordance with the idea that there is little scope for fast-growing plants in a vegetation to profit from the extra investments they made, we have as yet no reason to doubt these conclusions. No differences were found between N2-fixing species and other dicots, or between monocots and dicots in general.
Table 5. Average values for the biomass enhancement ratio (BER) value of herbaceous plants grown in a mixed stand divided by the BER of the vegetation as a whole. Data are from a range of experiments, listed in Appendix 5. The averages and the number of species on which the average are based, are for simple contrasts of plants of different categories. For more information see the legend of Table 1
|Class||High nutrients||Low nutrients|
|C4||0.78||13|| || ||1.05||4|| || |
|Slow-growing||0.97||16|| || ||0.96||44|| || |
|Dicots||1.04||46|| || ||1.00||47|| || |
|others||1.00||75|| || ||0.88||60|| || |
For competition at low nutrient levels, the situation is different. Here no differences between C3 and C4 species are observed, although we stress again that the number of C4 species investigated is low. The fact that C4 species are not negatively affected under these circumstances might well be due to the fact that at a low nutrient level a large CO2 response of C3 species is precluded (Table 4). The exception to this rule is the group of species capable of symbiotic N2 fixation, they are clearly the winners under these conditions. There is some indication of a difference between dicots and monocots, but closer analysis showed that the response only came from the nitrogen-fixing dicots. Decreases in grasses and increases in dicots, mostly due to an enhanced biomass of legumes, were found in most field studies (Schäppi, 1996; Clark et al., 1997, Navas et al. 1997; Lüscher et al., 1998; Warwick et al., 1998; Reich et al., 2001). The increase in leguminous species is particularly evident under conditions of low N and high P availability (Stöcklin & Körner, 1999; Körner, 2001).
Competition per se can be thought of as consisting of two components: the competitive effect, which is the ability of a plant to suppress neighbours, and the competitive response, the ability of a plant to tolerate its neighbours (Goldberg, 1990). An estimate of the first component is the dominance of a species in a community. In some field studies, not so much the dominant but some subordinate species were found to be highly responsive to CO2 (Leadley & Körner, 1996; Clark et al., 1997, Navas et al. 1997; Berntson et al., 1998; Stöcklin & Körner, 1999). It has therefore been suggested that elevated CO2 may reduce the overall size difference between dominant and subordinate plants (Catovsky & Bazzaz, 2002). Does that imply that we can consider subordinate species as a special ‘response group’, whose inherently low competitive effect is compensated for by a high responsiveness to CO2? As mentioned above, just by the nature of the fact that a species forms a minority in a vegetation, it may show larger proportional fluctuations than dominant species. It could well be that large proportional increases in a species strongly draw the attention of the researchers. Considered over all competition experiments compiled, we tested whether subordinate species are more often winners than dominant species, calculating the percentage of the total stand biomass taken up by a given species as an estimate for dominance. Using this parameter as the independent variable and the winner scale as the dependent variable, we did not find any indication of a difference between subordinate and dominant species (Fig. 10a; r2 = 0.00, P > 0.4), although the former show larger variability in their response to CO2 than the latter.
Figure 10. Winning and loosing species in the response of mixed communities to elevated CO 2 . The dependent variable is the ratio of the biomass enhancement ratio (BER) value of a species, growing in a mixed community, and the BER of the whole community. Independent variables are (a) the percentage of the biomass of a given species at control CO 2 levels, indicating the dominance of a species ( n = 204, r = 0.05, P > 0.4) and (b) the Relative Competition Intensity (RCI), indicating to what extent the biomass of a species is suppressed by the growth of the neighbouring species ( n = 37, r = 0.26, P > 0.1). Dotted lines indicate the nonsignificant linear regressions.
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The second factor that may play a role in the response to CO2 is the reaction of a species to competition from neighbouring vegetation. It can be estimated by the Relative Competition Intensity (RCI; Wilson & Keddy, 1986; Keddy et al., 1998), which is defined as the absolute decrease in the biomass of species because of competition, normalised against the biomass of isolated individuals. An RCI value of zero means that competition has no effect on plant performance, whereas an RCI value of one corresponds to complete competitive exclusion. Catovsky & Bazzaz (2002) suggested that tree species with a high response to elevated CO2 were those that suffered less from neighbouring plants when grown in competition. However, tested for herbaceous plants, we were not able to find a correlation between our winner scale and RCI (Fig. 10b; r2 = 0.07, P > 0.1).
In conclusion, there is no scope for using the response of isolated plants as a predictor of changes in the vegetation. Furthermore, there is no relationship between the competitive ability of a species and its responsiveness to CO2. As far as differences can be generalised over a larger group of experiments, C3 species may win from C4 species in vegetations with a high nutrient availability, and nitrogen-fixing dicots may profit at low nutrient availability.