Data from: Trait-based scaling of temperature-dependent foliar respiration in a species-rich tropical forest canopy

The scarcity of empirical data on leaf respiration (R) and its temperature sensitivity (e.g., Q10, defined as the proportional increase in R per 10°C warming) causes uncertainty in current estimates of net primary productivity of tropical forests. We measured temperature response curves of R on 123 upper-canopy leaves of 28 species of trees and lianas from a tropical forest in Panama, and analyzed variations in R and Q10 in relation to other leaf functional traits. Respiration rates per leaf area at 25°C (RA) varied widely among species and were significantly higher in trees than in lianas. RA was best predicted by a multiple regression model containing leaf phosphorus concentration, photosynthetic capacity, and leaf mass per area (r2 = 0.64). The mean Q10 value (2.4) was significantly higher than the commonly assumed value of 2.0. Q10 was best predicted by the combination of leaf carbohydrate concentration and growth form (trees vs lianas) (r2 = 0.26). The nighttime leaf respiratory carbon flux from this tropical forest was calculated from these multiple regression models to be 4.5 Mg C ha−1 yr−1, with an estimated additional 2.9 Mg C ha−1 yr−1 being released by respiration during the day. Trait-based modeling has potential for estimating R, thus facilitating carbon flux estimation in species-rich tropical forests. However, in contrast to global analyses, leaf phosphorus content was the most important correlate of R and not leaf nitrogen, so calibration of trait models to the tropics will be important. Leaf traits are poor predictors of Q10 values, and more empirical data on the temperature sensitivity of respiration are critically needed to further improve our ability to scale temperature-dependent respiration in species-rich tropical forests