Widespread collapse in Iberian forest site productivity projected under future climate change
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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 ranged from 0.46 ( Quercus faginea ) to 0.97 ( Pinus pinaster ); 17 of 21 species reached . BI013 precipitation of the wettest month), not BI014, was the most frequently retained predictor (15/17); BI014 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 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.
