Understanding how human activities alter Earth surface processes, including the deposition and preservation of biological signals, is crucial in the Anthropocene. This study investigated how human activities modify land cover changes by examining surface pollen assemblages—a key proxy for land cover—across the complex human-dominated landscapes of Shijiazhuang City on the North China Plain. We analyzed 66 surface soil samples from four land-use types (urban green space, farmland, wasteland, hill) to decode the pollen “fingerprint” of each and, more importantly, to reveal the underlying human-driven surface processes. Our results show that wastelands, under high disturbance but low management, are dominated by pollen of anthropogenic herbs (e.g., Amaranthaceae, Humulus ). Farmlands exhibit a strong cereal Poaceae signal coupled with low total pollen concentrations, indicative of intensive tillage that disrupts pollen deposition and preservation. Urban green spaces are characterized by high abundances of arboreal pollen (especially Pinus ) from artificial plantings, while hill sites retain high pollen diversity and fern spore content, reflecting minimal disturbance. To quantitatively assess this human influence, we developed an Anthropogenic Impact Index (the AI index = Amaranthaceae + Humulus / Arboreal + Shrub - Pinus ). When integrated with absolute pollen concentration (a key indicator of sedimentary and preservation conditions) and diversity indices, the AI index forms the core of a novel multi-dimensional diagnostic framework. This framework effectively discriminates between four distinct human activity-surface process regimes. Our work provides a semi-quantitative toolset that directly links surface pollen patterns to the intensity and type of human disturbance, offering critical modern-process insights for reconstructing past human-induced land cover changes and for understanding the anthropogenic transformation of surface biogeochemical cycles. • The pollen-land use relationships were established in the complex urban landscape. • Urban surface soil pollen reflects both local vegetation and regional inputs. • The AI Index enables semi-quantitative assessment of human activity intensity. • Provides the foundation for modern pollen analysis and reconstruction of land use changes.
Cui et al. (Thu,) studied this question.