Functional traits help predict post-disturbance demography of tropical trees

Abstract

How tropical tree species respond to disturbance is a central issue of forest ecology, conservation and resource management. We define a hierarchical model to investigate how functional traits measured in control plots relate to the population change rate and to demographic rates for recruitment and mortality after disturbance by logging operations. Population change and demographic rates were quantified on a 12-year period after disturbance and related to seven functional traits measured in control plots. The model was calibrated using a Bayesian Network approach on 53 species surveyed in permanent forest plots (37.5 ha) at Paracou in French Guiana. The network analysis allowed us to highlight both direct and indirect relationships among predictive variables. Overall, 89% of interspecific variability in the population change rate after disturbance were explained by the two demographic rates, the recruitment rate being the most explicative variable. Three direct drivers explained 45% of the variability in recruitment rates, including leaf phosphorus concentration, with a positive effect, and seed size and wood density with negative effects. Mortality rates were explained by interspecific variability in maximum diameter only (25%). Wood density, leaf nitrogen concentration, maximum diameter and seed size were not explained by variables in the analysis and thus appear as independent drivers of post-disturbance demography. Relationships between functional traits and demographic parameters were consistent with results found in undisturbed forests. Functional traits measured in control conditions can thus help predict the fate of tropical tree species after disturbance. Indirect relationships also suggest how different processes interact to mediate species demographic response.

Figure 1. Ecological and data models.

a) Hierarchical theoretical relationships between Performance currency measured at population level and indicative of species performance, Demographic parameters measured at population level and indicative of population dynamics, and Species functional traits measured at individual level and indicative of species strategies . b) Data model: variables used to quantify the components of the ecological model. Performance is evaluated by the population change rate, ; population dynamics is evaluated by recruitment and mortality rates; seven functional traits are considered in relation with the LHS scheme . Gray and white boxes indicate variables measured in disturbed and control conditions, respectively.

Figure 2. Results of the Bayesian Network analysis.

Directed Acyclic Graph (DAG) showing the network of relationships between the population growth rate (), demographic parameters (, recruitment rate, , mortality rate) and functional traits (see main text for labels). Grey (white) indicates variables measured after disturbance (in control conditions). Dashed boxes indicate variables having no parent (explicative variable) in the network: SV, WD, LNC and . The figure represents a statistical summary of the inferred relationships. Numbers indicate the posterior estimates of the model parameters: the intercept and the proportion of variance explained by the parents (r²; see relation 1) are given in boxes, the regression coefficients () are shown on arrows. Arrow width is proportional to the corresponding standardized regression coefficient. Italic numbers are estimates of the residual variance (; see relation 1, to be compared with raw variances in Table S3 in Appendix S1).

Figure 3. Correlation analysis.

Relationships between population change rate () and demographic parameters (, ) after disturbance and functional traits measured in control conditions (see main text for labels definition). Panels show respectively variables distribution in the diagonal, pairwise connections with lines showing linear regressions in the top triangle, and Spearman correlation coefficients on rank with tests results in the lower triangle. Large numbers indicate significant correlations with p-values as follows: . , , , and SV were log-transformed.