Abstract

Abstract. In this study, we quantified the predictive accuracy loss involved with omitting photosynthetic capacity variation for a Scots pine (Pinus sylvestris L.) stand in Flanders, Belgium. Over the course of one phenological year, we measured the maximum carboxylation capacity at 25 °C (Vm25), the maximum electron transport capacity at 25 °C (Jm25), and the leaf area index (LAI) of different-aged needle cohorts in the upper and lower canopy. We used these measurements as input for a process-based multi-layer canopy model with the objective to quantify the difference in yearly gross ecosystem productivity (GEP) and canopy transpiration (Ecan) simulated under scenarios in which the observed needle age-related and/or seasonal variation of Vm25 and Jm25 was omitted. We compared simulated GEP with estimations obtained from eddy covariance measurements. Additionally, we measured summer needle N content to investigate the relationship between photosynthetic capacity parameters and needle N content along different needle ages. Results show that Vm25 and Jm25 were, respectively, 27% and 13% higher in current-year than in one-year old needles. A significant seasonality effect was found on Vm25, but not on Jm25. Summer needle N content was considerably lower in current-year than in one-year-old needles. As a result, the correlations between Vm25 and needle N content and Jm25 and needle N content were negative and non-significant, respectively. Some explanations for these unexpected correlations were brought forward. Yearly GEP was overestimated by the canopy model by ±15% under all scenarios. The inclusion and omission of the observed needle age-related Vm25 and Jm25 variation in the model simulations led to statistically significant but ecologically irrelevant differences in simulated yearly GEP and Ecan. Omitting seasonal variation did not yield significant simulation differences. Our results indicate that intensive photosynthetic capacity measurements over the full growing season and separate simulation of needle age classes were no prerequisites for accurate simulations of yearly canopy gas exchange. This is true, at least, for the studied stand, which has a very sparse canopy and is exposed to high N deposition and, hence, is not fully representative for temperate Scots pine stands. Nevertheless, we believe well-parameterized process-based canopy models – as applied in this study – are a useful tool to quantify losses of predictive accuracy involved with canopy simplification in modelling.

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