Abstract: The Saihanba Forest Farm (SHB), China’s largest plantation base, has experienced significant habitat quality services (HQS) changes following six decades of afforestation. This study developed an integrated “CLUE-S–InVEST–BBN” framework to simulate and optimize HQS spatial patterns under alternative land use/cover change (LUCC) scenarios for 2035. Using Landsat imagery (2002–2022) and twelve biophysical and socio-economic drivers, we projected LUCC under three scenarios: ecological protection (EP), natural development (ND), and economic development (ED). HQS exhibited a “decline-then-recovery” trend from 2002 to 2022, with forests and grasslands contributing 79.6% and 48.2% of total HQS, respectively. The EP scenario projected 89.96% forest cover by 2035 with the highest mean HQS (0.8925), while the ED scenario showed a 1.54% decrease due to urban expansion. Bayesian belief network analysis identified LUCC, NDVI, road proximity, and precipitation as primary HQS determinants and delineated three management zones: key optimization, ecological conservation, and general management. This framework provides a replicable approach for enhancing HQS and supporting sustainable land-use planning in ecologically sensitive mountainous forest areas.

Key words: Habitat quality services, LUCC, CLUE-S InVEST–BBN, Spatial optimization, Saihanba