17 Conditional effect of covariates
In this chapter, we assessed the conditional effects of each covariate on the population growth rate (\(\lambda\)) for each species. Specifically, we quantified how \(\lambda\) varies with changes in competition intensity for both conspecific and heterospecific individuals. Furthermore, we examined how \(\lambda\) changes in response to variations in mean annual temperature and mean annual precipitation, spanning the range from the minimum to maximum observed values in the dataset. This analysis is similar to the sensitivity analysis discussed in Chapter 16. However, due to the larger number of conditions for each covariate, we performed this analysis using only 50 replicates from the posterior distribution of the parameters.
For the competition effect analysis, we maintained temperature and precipitation at the optimal conditions defined by the average of the optimal climate conditions among the growth, survival, and recruitment models. When assessing the effect of conspecific competition, heterospecific competition was set to null. Conversely, when evaluating the effect of heterospecific competition, the conspecific competition was defined as a small population size of \(N = 0.1\).
We evaluated the climate effect under two competition conditions: low competition, where conspecific population size was set to \(N = 0.1\), and high conspecific competition, where population size was established at the 99th percentile distribution of plot basal area experienced by the species in the dataset. When analyzing temperature, precipitation was held at its optimal condition, and vice versa.