Abstract
Arctic–Boreal terrestrial ecosystems are rapidly changing under amplified high-latitude warming, including widespread expansion of shrubs, with consequences for regional carbon and energy balances. Yet, high-latitude vegetation diversity and vegetation–climate interactions remain under-represented in many global land surface models. In ORCHIDEE, the land surface component of the IPSL Earth system model, high-latitude vegetation is represented primarily as boreal trees or grasslands, omitting explicit shrubs. Here, we implement three high-latitude shrub plant functional types (PFTs) (tall deciduous, low deciduous, and evergreen dwarf shrubs) in ORCHIDEE (revision 9269). Following literature recommendations, this classification combines phenology and stature to capture key functional contrasts while keeping the number of new PFTs limited. The implementation builds on ORCHIDEE's existing woody vegetation scheme by recalibrating a targeted set of parameters controlling allometry, carbon allocation, recruitment, mortality and phenology. Parameter values are constrained using synthesised pan-Arctic observations to obtain regionally representative shrub traits. Shrub spatial distributions are prescribed with updated PFT maps that combine ESA CCI products with Arctic and regional shrub mapping information. The resulting shrub PFTs reproduce observed ranges of shrub size and biomass allocation across the Arctic–Boreal domain. Introducing shrubs reduces simulated total aboveground biomass in the Arctic–Boreal region from 54 to 46.7 Pg C (−13.5 %) and mean annual gross primary productivity from 498 to 481 gCm-2yr-1 (−3.4 %) over the simulated period 1992–2020, with a stronger reduction in the tundra region (4.6 to 3 Pg C (−34.8 %); and 334 to 289 gCm-2yr-1 (−13.5 %)), increasing agreement with benchmarking datasets. A key strength of our implementation is its simplicity, as it builds on ORCHIDEE’s existing woody vegetation framework. In addition, the use of synthesised pan-Arctic observations provides regionally representative observational constraints, making the methodological choices transferable beyond ORCHIDEE. Overall, this work provides a data-constrained shrub representation in ORCHIDEE with minimal added process complexity and establishes a foundation for future development of shrub-climate interactions and dynamic shrubification processes.