Ecophysiological modeling of photosynthesis and carbon allocation to the tree stem in the boreal forest
- 1CEREGE, Aix-Marseille University, CNRS, IRD, Aix en Provence, 13545, France
- 2Departamento de Sistemas y Recursos Forestales, CIFOR-INIA, Madrid, 28040, Spain
- 3Département de géographie, Université du Québec à Montréal, Montréal, H3C3P8, Canada
- 4Department of Forest Sciences, University of Helsinki, Helsinki, 00014, Finland
- 5Département de biologie, chimie et géographie, Université du Québec à Rimouski, Rimouski, G5L3A1, Canada
- anow at: INRA Centre Grand Est – Nancy, UMR1137 Ecologie et Ecophysiologie Forestières, Champenoux, 54280, France
Abstract. A better understanding of the coupling between photosynthesis and carbon allocation in the boreal forest, together with its associated environmental factors and mechanistic rules, is crucial to accurately predict boreal forest carbon stocks and fluxes, which are significant components of the global carbon budget. Here, we adapted the MAIDEN ecophysiological forest model to consider important processes for boreal tree species, such as nonlinear acclimation of photosynthesis to temperature changes, canopy development as a function of previous-year climate variables influencing bud formation and the temperature dependence of carbon partition in summer. We tested these modifications in the eastern Canadian taiga using black spruce (Picea mariana (Mill.) B.S.P.) gross primary production and ring width data. MAIDEN explains 90 % of the observed daily gross primary production variability, 73 % of the annual ring width variability and 20–30 % of its high-frequency component (i.e., when decadal trends are removed). The positive effect on stem growth due to climate warming over the last several decades is well captured by the model. In addition, we illustrate how we improve the model with each introduced model adaptation and compare the model results with those of linear response functions. Our results demonstrate that MAIDEN simulates robust relationships with the most important climate variables (those detected by classical response-function analysis) and is a powerful tool for understanding how environmental factors interact with black spruce ecophysiology to influence present-day and future boreal forest carbon fluxes.