Trait coordination R project

"Trait coordination R project" including data and R scripts to reproduce analyses, figures and tables from "Drier, more seasonal climates strengthen coordination of hydraulic, leaf economic and reproductive strategies in subtropical forest tree communities"Authors: Julian Radford-Smith and John M. DwyerFor and outline of the folder and file structure, and complete metadata, refer to the README.txt file in the R project.<br><b>Abstract</b>Trade-offs relating to resource acquisition and conservation, reproduction and longevity generate considerable trait variation among co-occurring tree species, yet little is known about how the nature and strength of these trade-offs shift along gradients of resource availability. For rainforest and dry forest tree communities distributed across a continuous gradient of moisture availability in Australia’s subtropics (600 to 2,500 mm rainfall yr^-1), we examined the coordination of hydraulic, leaf economic and reproductive traits using a metric of multi-trait covariance and pairwise trait correlations. We hypothesized that trait coordination would be strongest at the dry and wet extremes of the moisture gradient, capturing strong moisture- and light-driven trade-offs, respectively. Overall trait covariance peaked in the driest sites and declined linearly along the regional moisture gradient, a trend also seen in the correlation of many trait pairs. In dry forests, stronger coordination of hydraulic and leaf economic traits captured a drought tolerance-drought avoidance spectrum, while correlations involving seed size reflected a ‘stature-recruitment’ trade-off. Albeit far weaker, we found that shade-tolerance and height-driven constraints on hydraulic function drove some trait coordination in light-limited sites. Our findings underscore the importance of interpreting trait-based trade-offs within the context of each site’s resource availability. We established that moisture limitation places much stronger constraints on trait combinations than light limitation, and identified key trade-off axes that are likely to become increasingly important under ongoing climate change.