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