The intensity of human pressure (HP) has an important impact on the biodiversity and ecosystem services of nature reserves (NRs), and the conflict and the coordination between NRs and human activities are now key issues to solve in the construction of NR systems. This study improved and applied a human footprint (HF) model that considers population density, land use, night light, grazing intensity, and road construction as indicators of human activity to evaluate the effectiveness of NRs in the Qinghai–Tibet Plateau in mitigating HP from 2000 to 2020. The results indicated that during this period, the average HP in the national NRs of the plateau increased from 1.47646 to 1.76687, where values were generally high in the east and low in the west. The average value in wetland NRs was the largest and had the smallest growth rate, while that in desert NRs was the smallest and had the largest growth rate. From 2000 to 2020, the average HP in the core areas, buffer areas, and experimental areas of the NRs increased by 0.12969, 0.29909, and 0.44244, respectively. It is a challenge for the Chinese government to strengthen the ability of NRs to mitigate HP on the wetland reserves and experimental zones in the Qinghai–Tibet Plateau region.

Agriculture, as an important activity on which human beings depend for their livelihood, brings serious environmental problems while meeting the needs of human survival, among which agricultural non-point source (NPS) pollution is one of the most urgent environmental problems. This study quantitatively assessed the loading characteristics spatial and temporal evolution patterns of two agricultural NPS pollutants, chemical oxygen demand (COD) and ammonia nitrogen (NH₃-N), from 2010 to 2020 in the Nansi Lake Basin as an example, and constructed a system dynamics (SD) simulation model to simulate and analyze agricultural NPS pollution under different development and treatment scenarios, based on an investigation of the regional prevention and control strategy of agricultural NPS pollution and the technological system. The results show that the current status of agricultural NPS pollution load in the Nansi Lake Basin is poor, and the level of pollution load is high, showing obvious geographical differences. In terms of temporal changes, the pollution loads of the two pollutants showed a decreasing trend from 2010 to 2020, among which the pollution load of NH₃-N showed the largest change. Spatially, the spatial distribution of each type of pollutant has some similarities, with smaller pollution loads in Jining and Zaozhuang and relatively larger pollution loads in Heze and Ningyang. The main source of COD pollution in the Nansi Lake Basin is rural life, with an emission proportion of 52.85%, and the main sources of NH₃-N pollution from agricultural NPS pollution in the area are rural life and livestock and poultry farming, with emission proportions of 47.55% and 35.36%, respectively. Under the status quo continuum scenario, the pollution load values for COD are consistently higher than those for NH₃-N, so the relative impact of COD is greater. In this study, the principles and methods of SD in system science are adopted to deal with the agricultural NPS pollution of Nansi Lake Basin, and the evolution of its behavioral characteristics are simulated, forecasted, and predicted, and policy experiments are conducted, with a view to providing references for the prevention and control of agricultural NPS pollution in Nansi Lake Basin and further research.

Land system multifunctionality is increasingly recognized as a key source of competition among production, living, and ecological functions. However, how these interactions are spatially manifested as functional competition within production–living–ecological space (PLES) through nonlinear relationships remains insufficiently understood. This study develops a land-system-oriented framework to assess four representative PLES functional conflicts within farmland production–ecological (PE) and natural ecological (E) spaces. Using Shandong Province, China, as a case study, we characterize PLES patterns in 2010, 2015, and 2020 and use a coupling-based index (D) as a proxy for functional competition intensity. XGBoost–SHAP is employed to examine the nonlinear spatial associations between selected environmental, socioeconomic, and spatial factors and proxy-based functional competition intensity during the 2010–2020 observation period. Results show that (1) the regional land system underwent marked functional reconfiguration, with urban–rural and fishing production–ecological spaces expanding while farmland production–ecological and natural ecological spaces contracted; (2) the four representative conflict scenarios exhibited pronounced spatial heterogeneity, with grain-production-related conflicts generally showing higher functional competition intensity than ecological-function-related conflicts; and (3) the dominant associated factors varied across conflict scenarios and exhibited distinct nonlinear response patterns. Overall, the findings reveal differentiated spatial associations between land-system multifunctionality and proxy-based functional competition intensity during 2010–2020. The identified response ranges provide empirical reference points for spatial monitoring and functionally differentiated territorial planning.