Impact of LUCC on landscape pattern in the Yangtze River Basin during 2001–2019

Ecological protection makes the ecological Kuznets curve turning point come earlier

Exploring the relationship between land use cover/change (LUCC) and ecosystem service value (ESV) under different future scenarios can provide guidance for selecting future development patterns and for the scientific utilization of land resources in the region. In this study, LUCC under different scenarios in the North Slope of Tianshan Mountain (NSTM) was simulated using the PLUS model. The ESV coefficients were adjusted for regional differences and social development factors to better reflect the actual situation in the study area. The interactions between LUCC, landscape pattern (LSP), and ESV were systematically analyzed, while at the same time, ESV and the level of economic development were fitted to the Ecological Kuznets Curve, which was then used to determine its trend and inflection point. The following conclusions were drawn: (1) Cropland and unused land are the main types of land use change in the NSTM, both historically and in the future. Cropland shows an increase in the natural development scenario and a decrease in the ecological protection scenario. Unused land shows an increase in the different development scenarios, indicating that unused land has higher development potential in the NSTM. NSTM shows a continuous decrease in ESV in the natural development scenario and a continuous increase in ESV in the ecological protection scenario. (2) LSP in both historical and future NSTM have evolved to show fragmentation, heterogeneity, and complexity in patch forms. However, this trend is slower in the ecological protection scenario than in the natural development scenario. LUCC, LSP, and ESV form an integrated framework of interactions, where LUCC influences ESV through LSP, and changes in ESV feedback to LUCC through LSP, which acts as a bridging mediator. (3) The Ecological Kuznets Curve of NSTM exhibits an N-shape, showing a clear overall rightward trend across different development scenarios at the annual level. At the interannual level, the curves for the natural development scenario are situated in the middle of the declining phase of the N-shape, with no ecological inflection point occurring during the study period. In contrast, the curves for the ecological protection scenario display a declining-ascending trend, with the ecological inflection point occurring when per capita GDP reaches 2.5 × 10^6 CNY.

Multi-scenario analysis and optimization strategy of ecological security pattern in the Weihe river basin

For many years, the Weihe River Basin (WRB) has struggled to achieve a balance between ecological protection and economic growth. Constructing an Ecological Security Pattern (ESP) is extremely important for ensuring ecological security (ES). This study employed a coupling of multi-objective programming (MOP) and the patch-generating land use simulation (PLUS) model to project land use change (LUCC) in 2040 across three scenarios. Leveraging circuit theory, we generated ecological corridors and identified key ecological nodes, enabling a comparative analysis of ESPs within the WRB. The main results showed that: (1) The Ecological Protection (EP) scenario showed the highest proportions of forestland, grassland, and water, indicating an optimal ecological environment. Conversely, the Economic Development (ED) scenario features the greatest proportion of construction land, particularly evident in the rapid urban expansion. The Natural Development (ND) scenario exhibits a more balanced change, aligning closely with historical trends. (2) The ecological source areas in the EP scenario is 13,856.70 km2, with the largest and most intact patch area. The ecological source patches that have been identified in the ED scenario exhibit fragmentation and dispersion, encompassing a total area of 8018.82 km2. The ecological source areas in the ND scenario is most similar to the actual situation in 2020, encompassing 8474.99 km2. (3) The EP scenario demonstrates minimal landscape fragmentation. The ED scenario presents a more intricate corridor pattern, hindering species and energy flow efficiency. The ND scenario is more similar to the actual distribution in 2020. Protecting and restoring key ecological nodes, and ensuring the integrity and connectivity of ecological sources are crucial for ESP optimization in various scenarios. Combining all results, we categorize the WRB's spatial pattern into "three zones, three belts, and one center" and offer strategic suggestions for ecological preservation, promoting sustainable local ecological and socioeconomic development.

The spatiotemporal evolution of rural landscape patterns in Chinese metropolises under rapid urbanization

Understanding the evolution of rural landscapes in metropolises during rapid urbanization is crucial for formulating policies to protect the rural ecological environment. In this study, remote sensing and geographical information system data, as well as applied landscape index analysis, are used to examine the spatiotemporal evolution of rural landscape patterns in the Beijing-Tianjin region of China, which has experienced rapid urbanization. The relationships between land use/land cover changes and changes in rural landscape patterns are explored. The results revealed significant spatial differences in the rural landscapes in the Beijing-Tianjin region; farmland and forestland were the main types of landscapes, creating a "mountain-field-sea" natural landscape pattern. The conversion of rural landscapes in the Beijing-Tianjin region involved mainly the conversion of farmland to urban areas, with few exchanges between other landscape types. The urban areas in the Beijing-Tianjin region increased by 3% per decade; farmland decreased at the same rate. Additionally, the rural landscape patterns in the Beijing-Tianjin region were dominated by fragmentation, dispersion, and heterogeneity and moved from complex to regular. Water bodies displayed the most fragmented natural landscape; their number of patches increased by 36%, though their network characteristics were maintained. Forestland was the most concentrated natural landscape. In this study, theoretical support and a scientific reference for the optimization of rural landscape patterns and the improvement in rural living environments in rapidly urbanizing areas are provided.

Spatiotemporal change and prediction of land use in Manasi region based on deep learning

The Manasi region is located in an arid and semi-arid region with fragile ecology and scarce resources. The land use change prediction is important for the management and optimization of land resources. We utilized Sankey diagram, dynamic degree of land use, and landscape indices to explore the temporal and spatial variation of land use and integrated the LSTM and MLP algorithms to predict land use prediction. The MLP-LSTM prediction model retains the spatiotemporal information of land use data to the greatest extent and extracts the spatiotemporal variation characteristics of each grid through a training set. Results showed that (1) from 1990 to 2020, cropland, tree cover, water bodies, and urban areas in the Manasi region increased by 855.3465 km2, 271.7136 km2, 40.0104 km2, and 109.2483 km2, respectively, whereas grassland and bare land decreased by 677.7243 km2 and 598.5945 km2, respectively; (2) Kappa coefficients reflect the accuracy of the mode's predictions in terms of quantity. The Kappa coefficients of the land use data predicted by the MLP-LSTM, MLP-ANN, LR, and CA-Markov models were calculated to be 95.58%, 93.36%, 89.48%, and 85.35%, respectively. It can be found that the MLP-LSTM and MLP-ANN models obtain higher accuracy in most levels, while the CA-Markov model has the lowest accuracy. (3) The landscape indices can reflect the spatial configuration characteristics of landscape (land use types), and evaluating the prediction results of land use models using landscape indices can reflect the prediction accuracy of the models in terms of spatial features. The results indicate that the model predicted by MLP-LSTM model conforms to the development trend of land use from 1990 to 2020 in terms of spatial features. This gives a basis for the study of the Manasi region to formulate relevant land use development and rationally allocate land resources.

Dissolved polycyclic aromatic hydrocarbons (PAHs-d) in response to hydrology variation and anthropogenic activities in the Yangtze River, China

Owing to their bioavailability and toxicity, the dissolved polycyclic aromatic hydrocarbons (PAHs-d) loaded in rivers are harmful to both inland and marine ecosystems. Thus, exploring the changes in PAHs-d levels and sources is important for controlling PAHs pollution. In this study, the concentration of PAHs-d in the mainstream of the Yangtze River during dry and wet seasons was investigated and the source was analyzed using the positive matrix factorization (PMF) model to assess the response of PAHs-d to hydrological and anthropogenic activities changes. The concentration of PAHs-d in the wet season (166.2 ± 52.51 ng/L) was significantly higher than that in the dry season (89.05 ± 20.89 ng/L) (ANOVA, P < 0.001), and the sampling sites with high pollution were mainly distributed in the downstream urban agglomeration. Herein, 2-3 rings were identified to play a dominant role in the composition of PAHs-d. Compared with the dry season, the proportion of the low molecular weight (LMW) PAHs-d were relatively depleted and the high molecular weight (HMW) PAHs-d were accumulated in the wet season. Coal and coke combustion were identified as the main sources of PAHs-d (65.9% in the dry season and 59.2% in the wet season), followed by vehicle emissions, petroleum sources, and biomass combustion. Owing to the change in energy consumption structure and climate characteristics, the sources of PAHs-d displayed seasonal variation and spatial heterogeneity. Further, flow was identified as the most important factor affecting PAHs-d in the hydrological parameters. Increases of flow, pH, and SPM decreased the proportion of LMW PAHs-d, and increased that of HMW PAHs-d. The increase in anthropogenic activities intensified the residual levels of 2-3rings and 5-6 rings in water, but had no significant impact on the levels of 4 rings.

Spatial and Temporal Evolution of Land Use and the Response of Habitat Quality in Wusu, China

Understanding land use change and its impact on habitat quality (HQ) is conducive to land use management and ecological protection. We used the InVEST model and the GeoDetector model to explore the land use and HQ of Wusu from 1980 to 2020. We found that the spatial distribution of land use in Wusu had the most dramatic change from 2000 to 2010, and accordingly, the habitat quality deteriorated seriously from 2000 to 2010. Via correlation analysis, the response of HQ to land use change is obvious, among which the negative effect of forest land to construction land is the largest, and the positive effect of construction land to water is the largest. However, the overall HQ had the largest negative response to the change of grassland to arable land, and the largest positive response to the change of unused land to grassland. Of the driving factors that cause land use change and thus affect HQ, the human factors are the strongest, and the negative impact on HQ is more irreversible. This study can provide a scientific basis for land use management and ecological protection in Wusu, and can help to further promote the exploration of human activities and ecological responses in arid and semi-arid areas.