Étienne Boucher

Process models and model-data fusion in dendroecology

Dendrochronology (i.e. the study of annually dated tree-ring time series) has proved to be a powerful technique to understand tree-growth. This paper intends to show the interest of using ecophysiological modeling not only to understand and predict tree-growth (dendroecology) but also to reconstruct past climates (dendroclimatology). Process models have been used for several decades in dendroclimatology, but it is only recently that methods of model-data fusion have led to significant progress in modeling tree-growth as a function of climate and in reconstructing past climates. These model-data fusion (MDF) methods, mainly based on the Bayesian paradigm, have been shown to be powerful for both model calibration and model inversion. After a rapid survey of tree-growth modeling, we illustrate MDF with examples based on series of Southern France Aleppo pines and Central France oaks. These examples show that if plants experienced CO2 fertilization, this would have a significant effect on tree-growth which in turn would bias the climate reconstructions. This bias could be extended to other environmental non-climatic factors directly or indirectly affecting annual ring formation and not taken into account in classical empirical models, which supports the use of more complex process-based models. Finally, we conclude by showing the interest of the data assimilation methods applied in climatology to produce climate re-analyses.

Decadal Variations in Eastern Canada’s Taiga Wood Biomass Production Forced by Ocean-Atmosphere Interactions.

Across Eastern Canada (EC), taiga forests represent an important carbon reservoir, but the extent to which climate variability affects this ecosystem over decades remains uncertain. Here, we analyze an extensive network of black spruce (Picea mariana Mill.) ring width and wood density measurements and provide new evidence that wood biomass production is influenced by large-scale, internal ocean-atmosphere processes. We show that while black spruce wood biomass production is primarily governed by growing season temperatures, the Atlantic ocean conveys heat from the subtropics and influences the decadal persistence in taiga forests productivity. Indeed, we argue that 20–30 years periodicities in Sea Surface Temperatures (SSTs) as part of the the Atlantic Multi-decadal Oscillation (AMO) directly influence heat transfers to adjacent lands. Winter atmospheric conditions associated with the North Atlantic Oscillation (NAO) might also impact EC’s taiga forests, albeit indirectly, through its effect on SSTs and sea ice conditions in surrounding seas. Our work emphasizes that taiga forests would benefit from the combined effects of a warmer atmosphere and stronger ocean-to-land heat transfers, whereas a weakening of these transfers could cancel out, for decades or longer, the positive effects of climate change on Eastern Canada’s largest ecosystem.