Predicting boreal conifer photosynthesis in field conditions

Abstract

Automatic continuous monitoring of shoot-level gas exchange and environmental factors in natural conditions provides an efficient but unexploited tool for testing the predictive power of plant photosynthesis models. We used automatically operated measurement chambers to monitor the CO₂ exchange of Scots pine (Pinus sylvestris) shoots in Finnish Lapland near the timberline over two growing seasons, yielding a total of 90000 measurements. In this paper, we show that a recent ecophysiological model predicts the daily and seasonal pattern of photosynthesis with the unbiased percentages of explained variance of 90% and 92%, respectively, utilising temporally independent data. Our model combines the optimal stomatal control model of photosynthesis with a model of annual cycle of photosynthesis. The key feature for applications of the model is the temperature driven onset, acceleration and decline of photosynthesis. With these dynamics, the model provides a useful tool for analysing the effects of climate change on annual photosynthetic production in boreal conifers.