Aim: As a prominent geographical distribution centre for the dark coniferous forests, mountains of Southwest China (MSWC) is experiencing an unprecedented warming trend, posing severe challenges to the survival of dominant fir (Abies) species. Although plant's migration ability is a prerequisite for its survival in changing environments, it has often been ignored in species distribution models (SDMs). This study aimed to quantify the magnitude and direction of range changes by the year 2080 for six dominant fir species, that isAbies recurvata,Abies faxoniana,Abies squamata,Abies ernestii,Abies forrestiiandAbies georgei, with an emphasis on exploring the relationship between migration ability and projected distributions.Location: The mountains of Southwest China.Methods: We applied the Maximum Entropy (Maxent) algorithm to calibrate ecological niche models and to project the climatically suitable areas (CSAs) of each species under two emission scenarios (RCP 4.5 and RCP 8.5). Additionally, we delimited future species ranges by three migration scenarios (full‐, no‐ and partial‐migration scenarios).Results: The simulations showed the distinctive responses of the six fir species to anthropogenic climate change (ACC). By 2080, the distribution areas ofAbies recurvatawere projected to decline only in the no‐migration scenario but increase under the full‐ and partial‐migration scenarios, while the other five species were projected to decline in the majority of emission × migration scenarios. Fir species in the southern region were predicted to be more vulnerable to ACC due to the larger losses in CSAs and a stronger effect of the partial‐migration scenario on the newly colonized areas of this group. The studied species showed a simulated migration trend (northward and westward) to the interior Qinghai‐Tibet Plateau under ACC.Main conclusions: Benefits or losses for species under ACC depended on the geographical location, their ecological niches and migration abilities, which provide essential insights for a spatial conservation assessment of biodiversity hotspots in the future.