4.5 | Conclusions
Nonlinear models are notoriously difficult to fit when sample sizes are limited, or if multiple solutions can be found. Fitting the temperature response models presented in this study through a probabilistic Bayesian MCMC approach allowed us to constrain parameters to plausible biological ranges, and to determine probabilistic estimates of model parameters when data was sparse at the leaf temperature extremes. These analyses show that despite tropical vegetation having experienced millions of years of relative stability in terms of temperature, the lack of physiological plasticity to effectively respond to changes in mean temperature. In the presence of double-ambient CO2concentrations, plants of the early-successional tree speciesTabebuia rosea can adjust to 4°C warming thereby largely preventing adverse effects on carbon gain. Even short-term exposure to such extreme conditions results in partial acclimation