Fine-resolution assessment of potential refugia for a dominant fir species (<Emphasis Type="Italic">Abies mariesii</Emphasis>) of subalpine coniferous forests after climate change

The questions “Will the environment surrounding moorlands become refugia for a Japanese subalpine coniferous species, Abies mariesii Mast., after climate change?” and “How does the spatial resolution of a species distribution model affect the global warming predictions?” have been discussed in this study. This study was conducted at Hakkoda Mountains, the northern side of Honshu Island, Japan. We constructed 50-m mesh model using a climate variable, two topography variables and two variables relating to moorlands. We applied the model to eight global warming scenarios, including decreasing or non-decreasing scenarios of moorlands. We also constructed a coarse-resolution model at approximately 1-km resolution and compared the model predictions with the fine ones. The results showed that the coarse-resolution model tended to overestimate the range of suitable habitats for A. mariesii. On the other hand, some suitable habitats around moorlands could only be predicted by the fine-resolution model. The fine-resolution model indicated that the peripheries of the moorlands are the most important potential refugia for A. mariesii on Hakkoda Mountains. Although these suitable areas were notable in the +2°C scenario, all suitable habitats completely disappeared in the +4°C scenario. We concluded that it would be effective to conserve the A. mariesii populations around moorlands which are likely to persist after global warming, as well as moorlands themselves. This assessment could only be achieved by fine-resolution models that incorporate non-climatic variables including topography and moorland-related variables with climatic variables. In contrast, a coarse-resolution model overestimated the suitable habitats whilst underestimating potential local refugia. Thus, fine-resolution models are more effective for developing practical adaptation of conservation measures.