Liriodendron chinense (Hemsl.) Sarg. (Magnoliales: Magnoliaceae), valued for its medicinal properties and timber and as an ornamental plant, is now classified as an endangered species. Investigating how future climate-change scenarios might affect the potential geographic distribution of L. chinense will provide a crucial scientific basis for its protection and management strategies. The MaxEnt model was calibrated using the ENMeval optimization package, and then it was coupled with ArcGIS 10.8 to forecast the possible distribution areas of L. chinense in China, utilizing elevation data, bioclimatic factors, and human footprint as environmental variables. The results indicate: (1) The optimal model parameters were set as follows: FC = LQ, RM = 0.5, the MaxEnt model demonstrated high predictive accuracy and minimal overfitting; (2) The total suitable habitat area for the potential geographical distribution of L. chinense during the current period is estimated at 151.55 × 10⁴ km², predominantly located in central, eastern, and southwestern regions of China; (3) The minimum temperature of the coldest month (bio6), precipitation of the driest month (bio14), precipitation of the driest quarter (bio17), precipitation of the warmest quarter (bio18), elevation (alt), and human footprint (hf) are the main environmental variables determining the suitable habitat distribution of L. chinense; (4) During the period from 2041 to 2060, under the carbon emission scenarios of SSP126, SSP245, and SSP370, the suitable habitat for L. chinense shows varying degrees of increase compared to the current period. However, under the highest concentration scenario of SSP585, the suitable habitat area decreases to some extent; (5) The distribution of L. chinense is likely to move towards higher latitudes and elevations in the future due to changes in the climate. This research provides a comprehensive analysis of the potential impacts of climate change on L. chinense, offering valuable information for its protection and management under future climatic conditions.

The field of landscape architecture has placed significant emphasis on low-carbon landscapes due to the increasing challenges posed by global warming and environmental deterioration in recent years. The soil ecological conditions in saline–alkaline areas are characterized by poor quality, resulting in suboptimal growth conditions for trees. This, in turn, hampers their ability to effectively sequester carbon, thereby diminishing the potential benefits of carbon sinks. Additionally, the maintenance of tree landscapes in such areas generates more carbon emissions than does conventional green land, making it difficult to reap the benefits of tree-based carbon. A comprehensive evaluation of trees in green park spaces in saline–alkaline areas is conducted from a low-carbon perspective; by identifying the dominant tree species that are well suited to greening, we can offer a precise scientific foundation for implementing low-carbon greening initiatives in cities situated in saline–alkaline environments. Therefore, as a case study, this study investigates Tianjin Qiaoyuan Park, a typical saline park in the Bohai Bay region. The hierarchical analysis method (AHP) was used to evaluate 50 species of trees and shrubs in the park from a low-carbon perspective. The results show that the evaluation system consists of four criterion layers and 15 indicator factors. The relative weight of the criterion layer followed the order of habitat adaptability (B2) > carbon sequestration capacity (B1) > low-carbon management and conservation (B3) > landscape aesthetics (B4). The indicator layer assigned greater weight values to net assimilation (C1), saline and alkaline adaptability (C3), drought tolerance (C4), irr igation and fertilization needs (C8), growth rate (C2), and adaptability to barrenness (C5). The trees were classified into five distinct categories, with each exhibiting significant variation in terms of the strengths and weaknesses of the indicators. According to the comprehensive score, the trees were categorized into three levels. The Grade I plants exhibited the best carbon efficiency performance, comprising a total of 12 species (e.g. Sabina chinensis, Fraxinus chinensis ’Aurea’ and Hibiscus syriacu), and demonstrated superior performance in all aspects. Grade II trees, consisting of 26 species (e.g Pinus tabuliformis, Paulownia fortunei, Ligustrum × vicaryi), had the second-highest comprehensive score. Moreover, Grade III trees, encompassing 12 species (e.g Acer mono, Cedrus deodara, Magnolia denudata), exhibited lower comprehensive scores. The extensive use of Grade I and II tree species is recommended in the implementation of low-carbon greening projects in the Bohai Bay region, while Grade III tree species should be judiciously utilized. The findings of this research can serve as a valuable resource for the scientific identification of tree species that are suitable for urban park green spaces in the Bohai Bay region, which is characterized by predominantly saline and alkaline soil. Additionally, the development of an evaluation system can guide the selection of low-carbon tree species when evaluating other types of saline and alkaline lands.