Protected areas (PAs) are pivotal in the conservation of global forest ecosystems, and understanding their effectiveness and spillover effects is crucial to evaluate their overall performance. While PAs are well-documented for their role in reducing deforestation, research examining their influence on mitigating non-stand replacement forest degradation or forest carbon emissions remains insufficient. Additionally, the nuanced heterogeneity in the effectiveness and spillover effects of PAs are not yet fully understood, impeding our ability to leverage outcome-based evidence for crafting spatial conservation strategies to expand PAs. In this study, integrating a rigorous counterfactual analysis and remote sensing observations, we probed the effectiveness and spillover effects of the Gutianshan National Nature Reserve (GNNR), located in Kaihua County of China, in curbing forest degradation, forest loss, and forest carbon emissions. We also explored the heterogeneity of these effects and identified spatial conservation priorities based on nonuniform impacts of effectiveness. Our findings showed that the GNNR designation remarkably curtailed forest degradation, forest loss, and forest carbon emissions by 78.56 %, 95.54 %, and 97.01 %, respectively, while also extending these mitigating effects to adjacent areas. However, we also detected leakage effects, causing a displacement of forest carbon emissions in areas 5–15 km around the reserve. The effectiveness and spillover effects exhibited heterogeneous patterns across geographical conditions. Informed by this heterogeneity, we pinpointed areas showing high conservation suitability as spatial conservation priorities, covering 35.64 % of Kaihua County, thereby boosting future forest and carbon management efforts. Our results advance the understanding of PA effectiveness and spillover effects within low-altitude subtropical forest ecosystems and offer insights into integrating outcome-based and area-based conservation approaches to achieve the 30 × 30 conservation target at a regional scale.