Wenbo Zhu

Rapid urbanization has led to a significant expansion of urban space, causing ecological problems such as fragmentation, declining landscape connectivity, and decreasing biodiversity. There is an urgent need to mitigate the conflict between urban expansion and ecological environmental protection by constructing ecological networks to help promote sustainable regional development. This study selected the Funiu Mountain area as the study area. Morphological spatial pattern analysis, the minimal cumulative resistance model, and network index evaluation were used to construct an ecological network in the study area and conduct a comparative analysis with local nature reserves. The results showed: (1) nine ecological source sites were identified, concentrated in the central and northern regions, which had a high spatial overlap with local nature reserves; (2) 34 ecological corridors were extracted, which could effectively connect all ecological source sites as well as most nature reserves; (3) 32 ecological nodes were identified, of which 20 strategic points were scattered along ecological corridors, and 12 artificial environment points were scattered in low-lying areas around nature reserves; (4) the ecological network showed a structure of central concentration and peripheral dispersion. The structural evaluation of the network indicated that it had strong integrity.

Soil erosion is a serious form of land degradation and poses a considerable threat to food supply, human health, and terrestrial ecosystems globally. The Qinba Mountains are an important geo-ecological transitional zone in China, and quantifying soil erosion in response to climate and land use/land cover (LULC) change can help inform plans for the area’s ecological protection. The spatiotemporal variation of soil erosion intensity in the Qinba Mountains during 2001–2020 was estimated using revised universal soil loss equation (RUSLE). Based on CMIP6 data, combined with Statistical Down Scaling Model (SDSM) and the CA-Markov model, future soil erosion intensity was predicted. The changing trend of soil erosion intensity was compared under four different shared socio-economic pathways (SSPs). The potential contributions of long-term changes in climate and LULC to soil erosion were assessed using statistical methods. The results show that future rainfall and rainfall erosivity will increase by 8%–12% and 3%–14%, respectively. Depending on the different socio-economic pathways, the soil erosion rate will increase by between 12 and 32%, with SSP2-4.5 predicted to cause greatest soil erosion. The analysis of influencing factors showed that rainfall frequency, intensity, and duration could increase the risk of soil erosion, while high temperatures could slow down the erosion rate. Barren land is the most vulnerable to erosion and should continue to be prioritized. Our spatial distribution map of soil erosion risk will help inform sustainable land practices and provide support for adaptation to future ecological environmental hazards caused by climate change.

As a major component of the north–south transition zone in China, the vegetation ecosystem of the Qinling-Daba Mountains (QBM) is highly sensitive to climate change. However, the impact of sunshine duration, specifically, on regional vegetation remains unclear. By using linear trend, correlation, and multiple regression analyses, this study systematically analyzed the spatiotemporal characteristics and trend changes of the vegetation coverage in the QBM from 2000–2020. Changes in the main climate elements in different periods and the responses to them are also discussed. Over the past 21 years, the vegetation coverage on the east and west sides of the QBM has been lower than that in the central areas. However, it is showing a continuously improving trend, especially in winters and springs. The findings indicate that change of FVC in the QBM exhibited a positive correlation with temperature, a negative correlation with sunshine hours, and both positive and negative correlation with precipitation. On an annual scale, average temperature was the main controlling climatic factor. On a seasonal scale, the area dominated by precipitation in spring was larger. In summer, the relative importance of the three was weak. In autumn and winter, sunshine duration became the main factor affecting vegetation coverage in most areas.

An urban development boundary is an effective means to guide urban development and restrain unplanned expansion of urban space. Scientifically-based delineation and control of the boundary can help with sustainable use of land resources and better spatial planning. This study took land use data from 2000, 2010, and 2020 for the central urban area of Zhengzhou and predicted the land use pattern in 2035. We used auto-logistic selection of driving factors, future land use simulation, and system dynamics models to delineate the development boundary of the central urban area. We complemented and optimized the boundary using agricultural and ecological perspectives. The results indicated the following: (1) The ROC values of land driving factors were greater than 0.75 in the regression test, and the Kappa and OA were greater than 0.92 in the accuracy test of land simulation results. (2) The boundary range initially delineated based on morphology was 2319 km². There was a clear overall development trend of the central urban area to the east and southeast, which included the historical urban area of Zhengzhou and the new government planning area. (3) The optimized boundary of the central district area was 2209 km², the ecological land control area was 136 km², and the basic farmland protection area was 54 km². The Yellow River, the airport, and the western, southern, and eastern areas were already formed. The study concluded that the delineated boundary was in line with the scientific concepts of ‘rigid’ and ‘flexible’ factors, which have positive effects on the protection of arable land resources and ecological land, as well as meeting the needs of urban development. The level of sustainable development of the region was effectively improved.

Rapid urbanization aggravates issues related to protection and optimization of the ecological environment. Constructing an ecological network system, including ecological values in planning, and using landscape effects efficiently are important for adjusting regional ecological space and promoting local sustainable development. Land use data from eight time points between 1980 and 2020 in the Zhengzhou Metropolitan Area were used to identify the local ecological sources, corridors and nodes and to identify an ecological network with high structural integrity. The study used the FLUS, MSPA, MCR, and gravity models, hydrological analysis, and network structure evaluation by applying tools such as ArcGIS, Guidos Toolbox and Conefor. The results indicated that: (1) among the nine major ecological sources, those in the Yellow River Basin connected the large−scale sources in the east and west of the network, and the rest were located in the northeast, southeast and southwest of the research area, semi−enclosing the main urban area of Zhengzhou. (2) There were 163 least−cost paths and 58 ecological corridors, mainly distributed along the Yellow River Basin. (3) There were 70 ecological nodes, divided into 10 strategic, 27 natural ecological and 33 artificial environment nodes, distributed in key locations such as the core of each source and the intersection of corridors. (4) The ecological network included all the landscape elements in the research area and connected the main ecological substrates in a semi−enclosing network structure with one horizontal and two vertical corridors and four clusters.

Multi-scenario simulation and pattern optimization of land use plays a role in improving regional functionality and balancing anthropogenic and natural environments. The simulation of future land use can provide a reference to demark the regional urban development boundary and identify spaces for ecological protection and agricultural development. Policy makers can use the simulated dynamic process to identify problems in the current trend of regional land use change. On the basis of land use data for Xiong’an New Area, China in 2010, 2015, and 2020, this paper established four scenarios to meet the planning requirements for this region: comprehensive evolution, protection of basic farmland, control of construction land, and prioritization of ecological protection. We used an optimized Markov–FLUS coupling model to simulate future land use changes. We found that the land suitability probability in the four scenarios successfully calculated the effect of land expansion in Xiong’an New Area. In 2010–2015 and 2015–2020, the overall accuracy was 0.9827 and 0.8805, respectively, and Kappa was 0.9675 and 0.7892, respectively. In 2035, the simulation results from the four scenarios and the eight land types were significantly different. Construction land, water area, wetland, and woodland increased by approximately 380%, 178%, 137%, and 3224%, respectively, while dry land and rural land decreased by approximately 55% and 43%, respectively. The multi-scenario simulation results were able to couple production, living, and ecological needs to optimize the spatial pattern and resource allocation in Xiong’an New Area. The scenarios provide new strategies to control population growth, permanently protect essential farmland, and restrict urban development.