Abstract
<jats:p>Aim: Here we aim to disentangle species-specific bioclimatic drivers of forest site productivity and project their future dynamics, providing a spatially explicit basis for anticipating climate-driven shifts in productivity and their implications for forest carbon sequestration. Location: Iberian Peninsula. Time period: 1985-2014 (calibration); 2071-2100 (projected under CMIP6 scenarios). Major taxa studied: 21 Iberian tree species. Methods: We used Site Form (SF) maps derived from the Third Spanish National Forest Inventory, spatially interpolating plot-level SF estimates as a continuous productivity index and relating them to 25 bioclimatic variables. Multiple linear regression models were selected via complementary stepwise and subset regression and validated on independent hold-out data (80%/20% split). Results: Validated R2val ranged from 0.46 (Quercus faginea) to 0.97 (Pinus pinaster ); 17 of 21 species reached R2val ≥ 0.70. BIO13 (precipitation of the wettest month), species lose total productivity by 2071-2100, six (including Fagus sylvatica and Betula alba) collapsing to below 1% of their reference-period value; only Pinus pinaster gains, and only under the lowest-emission pathway (up to 175%) (under SSP5-8.5 it too loses productivity, albeit less than any other species (35% of its reference-period value retained). Limiting warming to SSP1-2.6 spares Mediterranean pine and oak species but not Euro-Siberian and montane ones. Main conclusions: These validated, extrapolation-aware models reveal a near universal, climate-driven collapse in Iberian forest site productivity, with direct implications for the carbon-sink potential currently attributed to these forest types, and provide a route to dynamic, climate-aware carbon-uptake estimates for the region not BIO14, was the most frequently retained predictor (15/17); BIO14 was retained in only 11/17 models with a near-even sign split. Combining projected changes in mean productivity and habitat extent under SSP5-8.5, fifteen of sixteen applicable.</jats:p>