Introduction



Understanding the response of photosynthesis to climatic variation is needed to predict the forest response to future climate. Commonly, coupled leaf photosynthesis and stomatal conductance models, such as the FvCB model, integrate physiological data from leaf-gas exchange and local environmental conditions to understand plant responses to climate under controlled conditions (e.g., CO2, temperature and light). However, only a few studies explore the variation of the photosynthetic rate under natural conditions. Here, we use field data to parameterise the FvCB photosynthetic model using a separate data set of diurnal cycles of photosynthesis we then evaluate the model. We further explore the variability of photosynthetic rate under natural conditions on an elevation gradient in the Colombian Andes.





Hypotheses



To explore the variability of photosynthetic rate under natural conditions, we used three working hypotheses: i) intra-specific variation of photosynthesis capacity parameters (PCP) affect the model performance, ii) under optimality theory, the photosynthetic rate tends to be close to the optima most of the time along the diurnal cycle, and iii) high photosynthetic rate accumulated along time lead to high tree growth.



Method

We used saplings of seven tropical montane tree species that grow in three sites with different elevations (600; 1300; 2400m asl) . For each species, the FvCB model was parameterized using A-Ci curves under 25ºC for multiple individuals. Then, we used PCP to predict the photosynthetic rate under local climatic conditions employing local meteorological data. We compared: i) models that include average PCP values per species and models that account for intra-specific variability of PCP, ii) compare the variability of the estimated photosynthetic rate along diurnal cycles with optima estimated from A-Ci curves, and iii) estimated accumulated photosynthetic rate for one year and compare with the tree growth rate.



Results



We found that including intra-specific variability increases the goodness of fit of models than using the average PCP value per species. Also, we found that species tend to be close to the optima, at least in some portion of the day. These results highlight the difficulty of modeling photosynthetic rates on tropical montane tree species under natural conditions because different parameters commonly modeled as leaf temperature or average PCP value at community level affect the performance and estimation of photosynthetic rate. Also, tree growth rate is coupled to accumulated photosynthetic rate and is a useful to forecast the response of tropical montane tree species to climate change.