Land use change plays a crucial role in global environmental change. Understanding the mode and land use change procedure is conducive to improving the quality of the global eco-environment and promoting the harmonized development of human–land relationships. Large river basins play an important role in areal socioeconomic development. The Yellow River Basin (YRB) is an important ecological protective screen, economic zone, and major grain producing area in China, which faces challenges with respect to ecological degradation and water and sediment management. Simulating the alterations in ecosystem service value (ESV) owing to land use change in the YRB under multiple scenarios is of great importance to guaranteeing the ecological security of the basin and improve the regional ESV. According to the land use data of 1990, 2000, 2010, and 2018, the alterations in the land use and ESV in the YRB over the past 30 years were calculated and analyzed on the basis of six land use types: cultivated land, forestland, grassland, water area, built-up land, and unused land. The patch-generating land use simulation (PLUS) model was used to simulate the land use change in the study area under three scenarios (natural development, cultivated land protection, and ecological protection in 2026); estimate the ESV under each scenario; and conduct a comparative analysis. We found that the land use area in the YRB changed significantly during the study period. The ESV of the YRB has slowly increased by ~USD 15 billion over the past 30 years. The ESV obtained under the ecological protection scenario is the highest. The simulation of the YRB’s future land use change, and comparison and analysis of the ESV under different scenarios, provide guidance and a scientific basis for promoting ecological conservation and high-quality development of river basins worldwide.

With continuous urbanization and the fragmentation of green areas that affect human well-being, the establishment of a green infrastructure (GI) network is important in future urban planning. As a National Central City, Zhengzhou has a large population and is undergoing rapid economic development, resulting in an urgent demand for green space within the city in recent years. We selected the main urban area of Zhengzhou as the study area based on the two phases of Landsat 8 satellite remote sensing image data, for 2016 and 2021, and used the patch-generating land use simulation (PLUS) model to predict the spatial distribution of GI in the future; compared with traditional methods, this method identified green spaces from a future perspective. A GI network—consisting of an open space with vegetation as the main body—was designed for the main urban area of Zhengzhou using the traditional landscape ecological pattern theory, integrating morphological spatial pattern analysis (MSPA), the minimum cumulative resistance (MCR) model, circuit theory, and other methods. Evidently, the area of green space in Zhengzhou City in 2021 was 36 231.6 hm2. GI prediction results indicate that continuous expansion of the main urban area did not result in significant changes in the size of GI in the city. The GI within the urban area was relatively fragmented, forming 15 GI hubs, most of which were densely distributed along the edges of the main urban area. This study proposed the construction of a GI network with a target corridor and target points based on the existing corridor. This included the identification of seven target corridors and 15 target hubs; the total length of the corridor was 77.032 km, with a total of 31 target points. In summary, the GI network pattern of “one protection barrier, two lines, three loops and more points” was proposed. With new urban problems constantly emerging, this research could provide a theoretical reference basis for the planning of GI in the main urban area of the National Central City. The study provides concrete evidence on the optimum pattern for the construction of GI networks in cities with large populations.

Land-use change is a global issue, and the built-up land expansion has affected the ecological landscape patterns of the major river basins in the world. However, measurement of the ecological risks of potential landscape and identification of the dynamic relationships by natural and human-driven built-up land expansion at different zoning scales are still less understood. Based on multi-period Landsat satellite image data, we combined remote sensing (RS) and geography information systems (GIS) technologies with Spatial Durbin Panel Model to quantitatively analyze the landscape ecological effects under the built-up land expansion in the Yellow River Basin. The results showed that there is spatial heterogeneity in the built-up land expansion and ecological security patterns, with the expansion gravity center gradually spreading from the downstream to the middle and upstream areas, and the most dramatic change in landscape patches of ecological safety patterns occurring around the year 2000. At different zoning scales, there is a spatial spillover effect on the interaction between built-up land expansion and ecological security, with the significance of the regression estimates decreasing from large sample sizes to small sample sizes. Our findings highlighted the importance of spatial heterogeneity at different zoning scales in identifying the dynamic relationship between built-up land expansion and ecological security, scientific planning of land resources, and mitigation of ecological and environmental crises.

Climate is a dominant factor affecting the potential geographical distribution of species. Understanding the impact of climate change on the potential geographic distribution of species, which is of great significance to the exploitation, utilization, and protection of resources, as well as ecologically sustainable development. Betula platyphylla Suk. is one of the most widely distributed temperate deciduous tree species in East Asia and has important economic and ecological value. Based on 231 species distribution data points of Betula platyphylla Suk. in China and 37 bioclimatic, soil, and topography variables (with correlation coefficients < 0.75), the potential geographical distribution pattern of Betula platyphylla Suk. under Representative Concentration Pathway (RCP) climate change scenarios at present and in the 2050s and 2070s was predicted using the MaxEnt model. We analyzed the main environmental variables affecting the distribution and change of suitable areas and compared the scope and change of suitable areas under different climate scenarios. This study found: (1) At present, the main suitable area for Betula platyphylla Suk. extends from northeastern to southwestern China, with the periphery area showing fragmented distribution. (2) Annual precipitation, precipitation of the warmest quarter, mean temperature of the warmest quarter, annual mean temperature, and precipitation of the driest month are the dominant environmental variables that affect the potential geographical distribution of Betula platyphylla Suk. (3) The suitable area for Betula platyphylla Suk. is expected to expand under global warming scenarios. In recent years, due to the impact of diseases and insect infestation, and environmental damage, the natural Betula platyphylla Suk. forest in China has gradually narrowed. This study accurately predicted the potential geographical distribution of Betula platyphylla Suk. under current and future climate change scenarios, which can provide the scientific basis for the cultivation, management, and sustainable utilization of Betula platyphylla Suk. resources.

ObjectiveSchisandra chinensis (Turcz.) Baill. (S. chinensis) is a Traditional Chinese medicinal herb that can be used both for medicinal purposes and as a food ingredient due to its beneficial properties, and it is enriched with a wide of natural plant nutrients, including flavonoids, phenolic acids, anthocyanins, lignans, triterpenes, organic acids, and sugars. At present, there is lack of comprehensive study or systemic characterization of nutritional and active ingredients of S. chinensis using innovative mass spectrometry techniques.MethodsThe comprehensive review was conducted by searching the PubMed databases for relevant literature of various mass spectrometry techniques employed in the analysis of nutritional components in S. chinensis, as well as their main nutritional effects. The literature search covered the past 5 years until March 15, 2023.ResultsThe potential nutritional effects of S. chinensis are discussed, including its ability to enhance immunity, function as an antioxidant, anti-allergen, antidepressant, and anti-anxiety agent, as well as its ability to act as a sedative-hypnotic and improve memory, cognitive function, and metabolic imbalances. Meanwhile, the use of advanced mass spectrometry detection technologies have the potential to enable the discovery of new nutritional components of S. chinensis, and to verify the effects of different extraction methods on these components. The contents of anthocyanins, lignans, organic acids, and polysaccharides, the main nutritional components in S. chinensis, are also closely associated to its quality.ConclusionThis review will provide guidelines for an in-depth study on the nutritional value of S. chinensis and for the development of healthy food products with effective components.