Studying the spatio-temporal changes and driving mechanisms of vegetation’s net primary productivity (NPP) is critical for achieving green and low-carbon development, as well as the carbon peaking and carbon neutrality goals. This article employs various analytical approaches, including the Carnegie–Ames–Stanford approach (CASA) model, Theil–Sen median estimator, coefficient of variation, Hurst index, and land-use and land-cover change (LUCC) transition matrix, to conduct a thorough study of NPP variations in the Shandong Hilly Plain (SDHP) region. Furthermore, the geographic detector method was used to investigate the synergistic effects of meteorological changes and human activities on NPP in this region. Between 2000 and 2020, the vegetation NPP in the SDHP exhibited an average increase rate of 0.537 g C·m⁻²·a⁻¹. However, the fluctuation in mean annual NPP, ranging from 203 to 230 g C·m⁻²·a⁻¹, underscores an uneven growth pattern. Significant regional disparities are evident in vegetation NPP, gradually ascending from the southeast to the northwest and from the coastal areas to inland regions. The average Hurst index for the entire study area stands at 0.556, indicating an overall sustained growth trend in the time series of SDHP vegetation NPP. The vegetation NPP changes in SDHP can be well explained by climate variables (mean annual temperature, mean annual precipitation) and human activities (LUCC, night light index); of these, LUCC (q = 0.684) has the highest explanatory power on the impact of NPP and is a major influencing factor. This study deepens the understanding of the driving factors and patterns of vegetation’s dynamic response to climate change and human activities in the SDHP region. At the same time, it provides valuable scientific insights for improving ecosystem quality and promoting the carbon peaking and carbon neutrality goals.

With the global energy crisis and the decline of fossil fuel resources, biofuels are gaining attention as alternative energy sources. China, as a major developing country, has long depended on coal and is now looking to biofuels to diversify its energy structure and ensure sustainable development. However, due to its large population and limited arable land, it cannot widely use corn or sugarcane as raw materials for bioenergy. Instead, the Chinese government encourages the planting of non-food crops on marginal lands to safeguard food security and support the biofuel sector. The Southern China Karst Region, with its typical karst landscape and fragile ecological environment, offers a wealth of potential marginal land resources that are suitable for planting non-food energy crops. This area is also one of the most impoverished rural regions in China, confronting a variety of challenges, such as harsh natural conditions, scarcity of land, and ecological deterioration. Idesia polycarpa, as a fast-growing tree species that is drought-tolerant and can thrive in poor soil, is well adapted to the karst region and has important value for ecological restoration and biodiesel production. By integrating 19 bioclimatic variables and karst landform data, our analysis reveals that the Maximum Entropy (MaxEnt) model surpasses the Random Forest (RF) model in predictive accuracy for Idesia polycarpa’s distribution. The karst areas of Sichuan, Chongqing, Hubei, Hunan, and Guizhou provinces are identified as highly suitable for the species, aligning with regions of ecological vulnerability and poverty. This research provides critical insights into the strategic cultivation of Idesia polycarpa, contributing to ecological restoration, local economic development, and the advancement of China’s biofuel industry.

The medium development characteristics and controlling factors of the karst peak forest plain water system constitute the core of analyzing the complex and variable hydrogeological environment, especially in revealing the controlling factors between the hydrological system and karst development characteristics, which is crucial for a deeper understanding of karst hydrogeological environments. This study takes Zengpiyan in Guilin as an example and conducts a dynamic clustering analysis on the advantageous occurrence of fracture development in three sampling areas. A total of 3472 karst channels and fractures were identified and measured. Our research reveals the following: (1) The high degree of development of fissures on surface rock outcrops is mainly formed by the expansion of shear joints through dissolution and erosion. The dip angles of fissures are mainly characterized by low angles, with fissures with dip angles between 18° and 80° accounting for 65.44% of the total observed fissures. The linear density of fissures is 3.64 per meter. (2) There are significant differences in the line density of cracks and fissures in different areas of the research area. For example, the line density in Sampling Area 1 is 0.99 lines per meter, while the line density in Sampling Area 3 reaches 5.02 lines per meter. In addition, the extension length of cracks is generally long, with joints with extension lengths exceeding 1.5 m accounting for 77.46% of the total observed joints and through cracks with extension lengths exceeding 5 m accounting for 23.33%. (3) The development characteristics of underground karst reveal that underground karst caves are mainly distributed at elevations of 120 to 160 m, with a drilling encounter rate of about 43.3%. It is also noted that geological structures control the horizontal distribution of karst, and geological lithology, hydrodynamic conditions, and water carbon dioxide concentrations are key factors affecting the vertical zoning of karst. This study provides an important scientific basis for understanding the development characteristics and controlling factors of karst water system media in peak forest plains and has important guiding significance for water resource management in karst areas and disaster prevention during tunnel excavation.