## Introduction

Growth, survival and reproduction are the three imperatives of any organism. In plants, growth is particularly important because both survival and reproduction depend on plant size and therefore on growth rate. Relative growth rate (RGR, g g^{−1} day^{−1}) is therefore a key variable in influential models in plant ecology (Grime 1979; Tilman 1988; Westoby 1998; Grime 2001), and an understanding of its comparative ecology is critical in evaluating and improving such models.

Despite its importance, RGR is a complex phenomenon that is determined by differences in physiology, morphology and biomass partitioning. The relative contribution of these three factors is usually evaluated by decomposing RGR into its classical growth components (net assimilation rate, specific leaf area and leaf mass ratio; see equation 1). These components are functions of plant mass (*M*_{P}), leaf mass (*M*_{L}) and leaf projected surface area (*A*_{L}). In order to compare the relative contribution of each growth component, Poorter & Van der Werf (1998) defined a ‘growth-response coefficient’ (GRC) as the slope (β_{1}) of the linear regression given in equation 2. Such GRC values are therefore scaling (allometric) slopes. The natural logarithm of each growth component is regressed on the natural logarithm of RGR rather than the contrary, so that the slope with respect to each growth component *X* (β_{1}, GRC) is independent of the others.

The first paper to decompose RGR explicitly and measure such correlations for a group of species with contrasting ecology (Poorter & Remkes 1990) found that specific leaf area (SLA) was most strongly correlated to RGR, while net assimilation rate (NAR) and leaf mass ratio (LMR) were largely independent of RGR. If this is generally true, then one can replace RGR, a difficult and time-consuming measurement, with SLA, which is easily and quickly measured. Although a number of subsequent studies have found strong correlations between RGR and SLA, other studies have reported weak correlations between RGR and SLA, and strong correlations with other growth components. The strength of the interspecific relationships between RGR and its components therefore varies between studies. Identifying the differences between studies that control such changes may point the way to a more complete understanding of the trade-offs involved in the evolution of RGR.

Given the practical difficulties involved in such comparative experiments, it is not feasible for a single researcher to study many species and many different environmental conditions simultaneously. An alternative approach is to combine studies. A few such meta-analyses have already been published: Poorter & Van der Werf (1998) compiled data for herbaceous species, while two other studies (Cornelissen *et al*. 1998; Veneklaas & Poorter 1998) did the same for woody species. Cornelissen *et al*. (1998) found SLA to be the primary determinant of RGR, while Veneklaas & Poorter (1998) found NAR to be the primary determinant of RGR. Both Poorter & Van der Werf (1998) and Shipley (2002) evaluated the possibility that differences in the light environment might affect the relative importance of the growth components in determining RGR, and came to different conclusions, with Poorter & Van der Werf (1998) concluding that the light environment had no effect.

Here I present a more complete meta-analysis with the following properties: First, I combine both woody and herbaceous species, and compare them. Second, I explicitly model the effects of different growth conditions and species types (herbaceous/woody) in a single analysis, while taking into account the non-independence that arises from combining different studies in a single data set. Third, I determine if different growth conditions change the growth-response coefficients. Finally, I use a much larger database than other studies. Specifically, I ask three questions: (i) What is the relative importance of the three growth components in determining variation in RGR? (ii) How variable are the relationships between RGR and its growth components between experiments? (iii) Can the differences in the growth-response coefficients between experiments be related to differences in the light environment or types of species (woody/herbaceous) included in each experiment?