Читать книгу Ecology - Michael Begon - Страница 146

Intriguingly, when the thinning and boundary lines of all sorts of plants are plotted on the same figure, they all appear to have approximately the same slope and also to have intercepts (i.e. values of c in Equation 5.24) falling within a narrow range (Figure 5.37). To the lower right of the figure are high‐density populations of small plants (annual herbs and perennials with short‐lived shoots), while to the upper left are sparse populations of very large plants, including coastal redwoods (Sequoia sempervirens), the tallest known trees. Fashions change in science as in everything else. At one time, ecologists looked at Figure 5.37 and saw uniformity – all plants marching in −3/2 time, with variations from the norm seen either as ‘noise’ or of only minor interest (e.g. White, 1980). Subsequently, however, serious doubt was cast on the conformity of individual slopes to −3/2, and on the whole idea of a single, ideal thinning line (Weller, 1987 , 1990 ; Zeide, 1987; Lonsdale, 1990). This is reminiscent of discussions we described in Section 3.9 about whether there is a general rule (and a common slope) at the heart of a metabolic theory of ecology, and again, there really is no contradiction. On the one hand, the lines in Figure 5.37 occupy a very much smaller portion of the graph than one would expect by chance alone. There is apparently some fundamental phenomenon linking this whole spectrum of plant types: not an invariable ‘rule’ but an underlying trend. On the other hand, the variations between the lines are real and important and in as much need of explanation as the general trend.

Figure 5.37 Self‐thinning in a wide variety of herbs and trees. Each line is a different species, and the line itself indicates the range over which observations were made. The blue arrows, drawn on representative lines only, indicate the direction of self‐thinning over time. The figure is based on Figure 2.9 of White (1980), which also gives the original sources and the species names for the 31 datasets.