Decades of research have revealed large uncertainties in paleoclimate reconstructions based on fossil pollen data. To address this issue, modern studies are essential for improving the understanding of the vegetation–climate relationship. In this study, a total of 45 modern surface soil samples were collected along an east–west precipitation gradient and a north–south temperature gradient in Northeast China. These samples were analyzed to investigate modern pollen–vegetation, stomata–parent plant, and pollen–climate relationships. Using Redundancy Analysis (RDA) and random forest modeling, we found that pollen assemblages can effectively distinguish different vegetation types. Furthermore, stomata analysis demonstrated that Pinus and Larix stomata can reliably indicate the local presence of their parent plants. Both RDA and random forest models identified that the mean air temperature of the coldest month was the primary climatic parameter influencing coniferous pollen distribution, while annual precipitation was the dominant factor controlling herb pollen distribution. This study demonstrates that combining pollen assemblages with stomata analysis can remarkably improve the accuracy of vegetation reconstruction in northeastern China, with coniferous and herb pollen serving as reliable respective indicators of coldest month temperature and annual precipitation.
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