Decoding carbon allocation in boreal forests: Integrating multi-proxy observations and process-based modelling

Résumé fourni par la source

• Stem structural C allocation is linked to GPP in two boreal forests. • Jack pine shows an active NSC role while black spruce shows buffering strategy. • NSC dynamics reflect species-specific cold adaptation and stand conditions. • Incorporating NSC-mediated trade-offs improves carbon allocation modelling. Understanding how photosynthetic carbon (C) is allocated to woody biomass remains a critical gap in predicting forest responses to climate change, especially in cold-limited ecosystems, due to the pervasive lack of comprehensive carbon-based data at the whole-stand level. We applied a multi-proxy approach integrating eddy covariance, process-based modelling, and quantitative wood anatomy to assess C fluxes and stem-level C allocation in two mature boreal stands in Canada—black spruce ( Picea mariana Mill.) and jack pine ( Pinus banksiana Lamb.)—from 1999 to 2021. At both stands, we found that stem structural C allocation (measured as cell wall area, CWA) was tightly coupled with observed and modelled gross primary productivity (GPP). Modelled non-structural carbohydrates (NSC) dynamics revealed contrasting temporal patterns between species: jack pine showed an immediate response to available NSC and annual CWA, suggesting an active role of NSC in supporting growth under fluctuating environmental conditions. In contrast, black spruce exhibited a delayed effect, suggesting a more passive and buffering role of NSC in stem structural C allocation. Notably, at the jack pine site, extreme cold years corresponded to reduced CWA alongside elevated NSC concentrations, which might indicate a shift in C allocation priorities toward storage over growth. Our findings, based on a multi-proxy approach, provide novel insights into species-specific and possible trade-offs between storage and growth, useful for improving C budget models and adaptive forest management under climate change.

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