1. The scarcity of empirical data on leaf respiration (R) and its temperature sensitivity (e.g. Q(10), defined as the proportional increase in R per 10 degrees C warming) causes uncertainty in current estimates of net primary productivity of tropical forests. 2. 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 analysed variations in R and Q(10) in relation to other leaf functional traits. 3. Respiration rates per leaf area at 25 degrees C (R-A) varied widely among species and were significantly higher in trees than in lianas. R-A was best predicted by a multiple regression model containing leaf phosphorus concentration, photosynthetic capacity and leaf mass per area (r(2)=064). The mean Q(10) value (24) was significantly higher than the commonly assumed value of 20. Q(10) was best predicted by the combination of leaf carbohydrate concentration and growth form (trees vs lianas) (r(2)=026). 4. The night-time leaf respiratory carbon flux from this tropical forest was calculated from these multiple regression models to be 45MgCha(-1)year(-1), with an estimated additional 29MgCha(-1)year(-1) being released by respiration during the day. 5. Trait-based modelling 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 Q(10) 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
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