Climate change adaptation of Iberian dehesa: a simulation approach using the Hi-sAFe model
摘要
Agroforestry is a promising solution to enhance the resilience of agricultural systems against climate change. However, evidence on the long-term response of semi-natural agroforestry systems, such as extensive silvopastures, remains limited. To address this knowledge gap, this study assessed the production and temporal stability of a Mediterranean silvopastoral system, the Iberian dehesa, under climate change. The process-based Hi-sAFe model was used to simulate tree growth, pasture production, and their temporal stability from 1990 to 2100 under the very high emissions Representative Concentration Pathway 8.5 scenario in open grasslands and silvopastures with 25 and 50 trees ha-1. Simulations were validated with long-term data on tree growth (2011-2023) and pasture production (2014-2024). We explored the optimal farm composition to maximize production and its temporal stability. The model accurately simulated tree growth (stem diameter; RMSE=1.63 cm, R2 = 0.98) and pasture production (RMSE=0.4 t ha-1, R2=0.95). Results indicated higher tree development and pasture biomass temporal stability at 25 than at 50 trees ha-1, with 40% and 111% higher diameter increase and temporal stability, respectively. Open pastures had higher productivity than agroforestry and declined at all tree land covers over the 1990-2100 period. The agroforestry scenario at 25 trees ha-1 showed the smallest decrease in pasture production (-1.4 kg ha-1 yr-1), compared to open pastures (-2.1 kg ha-1 yr-1) and 50 trees ha-1 (-4.1 kg ha-1 yr-1), indicating a buffering effect against increased aridity. The optimal farm composition showed an increasing share of agroforestry at 25 trees ha-1 density as climate change effects intensify. At the farm/landscape scale, a combination of open pastures and dehesas with different tree densities is recommended. This is the first study to apply the Hi-sAFe model to complex silvopastoral systems, indicating its usefulness and limitations in exploring trends and outcomes associated with different tree density scenarios under climate change.