Figure 1.
Growth versus survival for large trees (blue) and small trees (red).
“Trade-off” shows an overall significant negative relationship between growth and survival. The ‘intercept’ term refers to a difference in intercepts between small and large trees, and a ‘slope’ difference refers to the different slope between large and small trees. These differences indicate that the growth survival trade-off is more pronounced for smaller trees (red line). ANOVA table details in Table 1. Significance codes for all figures: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1.
Figure 2.
Survival versus functional traits.
Leaf mass per area (LMA) shows a positive slope, indicating that species with thicker leaves tend to survive more, as predicted by theory. Seed mass and wood density show weak or no relationship to survival. ANOVA table details in Table 1. Significance codes for all figures: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1.
Figure 3.
Survival versus functional traits with ontogenetic variable as a covariate.
LMA and seed mass shows a difference between intercepts, while wood density shows no overall slope (see Figure 2 panel 3), but the interaction term shows a differential survival between large and small trees depending on wood density, with smaller trees showing an effect of wood density. Slope for large trees is blue and for small trees red. ANOVA table details in Table 1. Significance codes for all figures: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1.
Figure 4.
Growth versus functional traits with environmental and ontogenetic variables as covariates.
Red slopes indicate old stands, plots on slopes, high light, and small trees, while blue indicates young stands, no slope, low light, and large tree levels. Light is the most important effect in these analyses, showing a strong positive shift to higher growth in high-light, regardless of the relationship between the traits and growth. There remains a great deal of scatter around these relationships, however, suggesting a need to test the variables and their interactions in a combined model (Table 2). ANOVA table details in Table 1. Significance codes for all figures: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1.
Table 1.
Individual regressions and ANCOVAs.
Figure 5.
Main effects of the combined model.
Because the variables were standardized using two standard deviations, the main effects of the combined model (Table 2) show standard deviation changes in growth given standard deviation changes in predictor variables, given that all other variables are held at the mean values across all species and conditions. Bars show standard errors of parameter coefficients. Light shows the largest positive influence, but other variables, through their interactions, also affect growth (Table 2).
Table 2.
Optimal regression model of species growth rates against survival and ontogenetic, environmental, and trait variables.
Figure 6.
Influence of light on predicted growth across species.
This figure shows the difference in expected growth due to high and low light across species. All other variables are kept at their means (zero). Lines show expected growth over two standard errors of parameter values. Regardless of expected average growth rate, light increases growth across all species.
Figure 7.
Influence of tree size on growth rate.
The change in expected growth due to ontogeny shows a range of effects across species. All other variables are kept at their means (zero). Lines show expected growth over two standard errors of parameter values. Some species are far more sensitive to ontogenetic stage in growth ability. Combining this information with Figure 6 shows even focusing on two effects can begin to divide niche space across species, with high-light, low-light, short and tall trees differentially affecting growth.