Impacts of Climate Change and Human Activity on the Habitat Distribution of <i>Metasequoia glyptostroboides</i>

Extensive evidence supports that global climate change influences shifts in species habitats due to alterations in hydrothermal conditions; however, neglecting dispersal capacities and limits significantly heightens uncertainties regarding spatial distribution patterns among different organisms. In this study, we compared the spatial distribution of <i>Metasequoia glyptostroboides</i> Hu & W.C. Cheng (<i>M. glyptostroboides</i>) in the current Anthropocene context to that in a climate-only context, providing new insights into the effects of climate change, dispersal potential, and dispersal barriers on the habitat changes for <i>M. glyptostroboides</i>. By utilizing optimized MaxEnt and MigClim models, we predicted Mid-Holocene (MH) conditions and potential colonizable habitats under three emission scenarios (SSP126, SSP245, and SSP585) for both the medium and long term. We also assessed habitat distribution and variation differences in future warm-wet conditions and the Anthropocene context. The results revealed that (1) The Precipitation of driest month (BIO14), Mean diurnal range (Bio2) and human footprint (HFP) are the primary factors influencing the expansion or contraction of the habitats of <i>M. glyptostroboides</i>. Human footprint, farmland, roads, and construction land are the main contributors to habitat loss and fragmentation. (2) Habitats of <i>M. glyptostroboides</i> are expected to experience significant loss in the future. There is potential for recovery in South China under the SSP126 emission scenario, but human activities may hinder this recovery. Moderate human intervention is necessary in regions, such as Hubei, Hunan, Anhui, and Sichuan basins. (3) Due to human influence, the habitat and high-suitability areas for <i>M. glyptostroboides</i> are projected to migrate northeastward. Under the SSP126 scenario, a trend of reverse migration may be observed in the long term. This study minimizes the uncertainty in predicting species distribution under climate change while providing theoretical support for future habitat conservation of <i>M. glyptostroboides</i>.