Analysis of the implementation effects of ecological restoration projects based on carbon storage and eco-environmental quality: A case study of the Yellow River Delta, China

Spatiotemporal variation and dynamic simulation of carbon stock based on PLUS and InVEST models in the Li River Basin, China

The watershed is the optimal natural division for ecosystems, playing a crucial role in carbon reduction and sequestration. Exploring the carbon sequestration potential of terrestrial ecosystems under different land use scenarios and enhancing regional carbon storage capacity is of significant importance. In this study, the LUCC in the Lijiang River basin under the scenarios of natural evolution (NE), natural conservation (NC), urban developmentand (UD) and farmland protection (FP) in 2040 was simulated by using grid data, driver grid data and carbon density data, based on the PLUS model and the InVEST model. Then, the effects of land use change on carbon stock in the Lijiang River Basin from 2000 to 2040 were evaluated. The results show that, (1)from 2000 to 2020, the area of arable land significantly increased in the Li River Basin, while forest and grassland areas decreased significantly. The distribution pattern of land use in the Li River Basin is mainly influenced by factors such as economy, population density, topography, and roads. Population growth and economic development require more arable land, forest land, and construction land. (2)Due to land use change, the carbon stock in the Li River Basin decreased by 3.69 × 106 t over the 20-year period, particularly in the northern and southern regions of the basin. (3)Meanwhile, there was a significant change in the land use pattern, with forest carbon stock accounting for a reduced proportion (90.76%) of the total ecosystem carbon stock in 2020. (4)According to the projected natural evolution scenario, the carbon stock in 2040 will decrease by 3.13 × 106 t compared to 2020 in the Li River Basin. Under the scenario of arable land protection, the carbon stock will decrease significantly. Under the ecological protection scenario, the carbon stock of the terrestrial ecosystem will increase by 2.75 × 105 t. Under the urban development scenario, the carbon stock caused by land use change will be uncertain; however, construction land increase will definitely cause the decrease of carbon stock.This study examines the impact of land use change scenarios on carbon storage in the Li River Basin, highlighting the potential carbon gains under the ecological conservation scenario, providing valuable insights for regional land use planning and carbon reduction strategies.

Scale effects on the accuracy and result of soil nitrogen mapping in coastal areas of northern China

The scale effect is crucial for soil mapping because by influencing the simulation accuracy and results. To date, the scale effect on soil mapping in coastal areas remains unclear, and changes in simulation accuracy and results across multiple scales are urgently to be uncovered. The present study aimed to reveal the scale effects of surface soil total nitrogen mapping over large-extent coastal areas. The northern China's coastal areas were selected as the spatial extent, and two time points in 2010 and 2020 were considered the temporal interval. Ten spatial scales from 100 m to 1000 m were used as the simulation units. Results indicated a distinct increase in soil nitrogen in most of the study area during 2010-2020, and the surface soil total nitrogen density and storage were 0.256 kg/m2 and 16.67 Tg in 2020, increasing by 17.18% and 18.60%, respectively, in the entire study area. This increase was mainly driven by promoting ecological quality through extensive ecological restorations in China. Across the 10 scales, the highest simulation accuracy was achieved by the 200 m scale with a root mean squared error of 0.4217 and Lin's concordance correlation coefficient of 0.4193. The simulation results were similar in the extent of the entire study area but changed considerably in the degree and nature in the extent of small geographical regions. The scale effect on the simulation results increased with the decrease in the area of the analyzed extent and was more distinct in areas with lower soil nitrogen. The study has quantitatively delineated the scale effects on simulation accuracy and results in coastal soil nitrogen mapping and can effectively guide the resolution selection for different mapping extents and demands. Generally, the coarse spatial resolution (1000 m) homogenized the simulation results and was a relatively feasible scale with a low cost at a large extent. In contrast, the fine resolution (100 m and 200 m) presented high spatial heterogeneity and was essential for precise simulation results at a small extent. The 200 m scale is recommended in coastal soil nitrogen mapping under normal circumstances for its highest accuracy of the 10 scales and distinctly lower cost compared with the 100 m scale.

A framework of ecological security patterns in arid and semi-arid regions considering differences socioeconomic scenarios in ecological risk: Case of Loess Plateau, China

Understanding the establishment of ecological security patterns in arid and semi-arid regions is critical for global ecological risk prevention, control, and sustainable development. Nonetheless, there remains a relative deficiency in ecological risk assessment and construction of Ecological Security Patterns (ESP) in these areas, along with insufficient verification regarding the changes in ecological security patterns under diverse scenarios. This study employs Morphological Spatial Pattern Analysis (MSPA) to identify ecological sources and utilizes circuit theory alongside Minimum Cumulative Resistance (MCR) to delineate ecological corridors. Additionally, the framework integrates the impacts of human activities on ecosystems and accounts for the disparities and uncertainties associated with future scenarios in constructing ESP. Results indicate discrepancies between the least risky pathway (SSP5-8.5) and the most stable pathway (SSP1-2.6) on the Loess Plateau, with varying manifestations of ecological risk. This study identified 28 large-scale ecological sources covering 65,642.745 km2, including 10 core sources exceeding 2000 km2; delineated 65 ecological corridors totaling 6695.061 km, encompassing 19 core corridors spanning 4091.452 km. The spatial overlap between ecological corridors and high-risk areas presents challenges to constructing ecological security patterns. In consideration of future uncertainties, we propose an ecological pattern optimization strategy incorporating "three barriers, five corridors, three protections, two zones, two belts, and multiple scattered points". This strategy emphasizes the potential of combining primary planting corridors, returning farmland to forests, and planning ecological buffer zones to address ecological risks. The study aims to enhance ecological security levels and readiness to confront ecological challenges in arid and semi-arid regions.

Exploring dynamics relationship between carbon emissions and eco-environmental quality in Samarinda Metropolitan Area: A spatiotemporal approach

Carbon emissions have a negative impact on climate change. Environmental quality has faced significant challenges in the last decades. Eco-environmental quality helps assess the condition of the ecological environment to support humans' civilization and development. By using emissions raster dataset, remote sensing images, and LULC data, this study explores the status of carbon emissions (CE), eco-environmental quality (RSEICs), and the dynamic relationship between both variables in Samarinda Metropolitan Area, Indonesia. This study uses the spatiotemporal approach to deepen the understanding of CE-RSEICs during 2000-2021. The methods include the analysis of CE and the principal component of RSEICs. To understand the CE-RSEICs spatial features, the directional distribution ellipse method is used. Also, this study performs CE-RSEICs coupling analysis and identifies its LULC type composition. The findings show that CE status is still on an increasing trend, concentrating in the eastern region and keeping expanding during the period. The location of the low-emission ellipse is in the southwest, while the high-emission ellipse is in the east and intersects with the core cities. The mean RSEICs value is between 0.2878 to 0.4223, which indicates that the eco-environmental quality is categorized as fairly poor to inferior. Greenness, wetness, and Csink have a positive impact on RSEICs. The very poor-class ellipse is located in the inland region, and the very good-class ellipse is in the coastal area. The CE-RSEICs coupling status shows that the majority of the area has a weaker coupling degree. However, the higher coupling degree is concentrated in the population center and built-up region, which is the settlement area. The dominance composition of settlement area in higher coupling degree shows that settlement area has an impact on increasing CE-RSEICs coupling degree. So, sustainable low carbon development in coastal metropolitan area must continue to be carried out by considering CE-RSEICs and its spatial aspects.

Comprehensive comparison of two models evaluating eco-environmental quality in Fangshan

It is crucial to employ scientifically sound models for assessing the quality of the ecological environment and revealing the strengths and weaknesses of ecosystems. This process is vital for identifying regional ecological and environmental issues and devising relevant protective measures. Among the widely acknowledged models for evaluating ecological quality, the ecological index (EI) and remote sensing ecological index (RSEI) stand out; however, there is a notable gap in the literature discussing their differences, characteristics, and reasons for selecting either model. In this study, we focused on Fangshan District, Beijing, China, to examine the differences between the two models from 2017 to 2021. We summarized the variations in evaluation indices, importance, quantitative methods, and data acquisition times, proposing application scenarios for both models. The results indicate that the ecological environment quality in Fangshan District, Beijing, remained favorable from 2017 to 2021. There was a discernible trend of initially declining quality followed by subsequent improvement. The variation in the calculation results is evident in the overall correlation between the RSEI and EI. Particularly noteworthy is the significantly smaller correlation between EI and the RSEI in 2021 than in the other two years. This discrepancy is attributed to shifts in the contribution of the evaluation indices within the RSEI model. The use of diverse quantitative methods for evaluating indicators has resulted in several variations. Notably, the evaluation outcomes of the EI model exhibit a stronger correlation with land cover types. This correlation contributes to a more pronounced fluctuation in RSEI levels from 2017 to 2021, with the EI model's evaluation results in 2019 notably surpassing those of the RSEI model. Ultimately, the most prominent disparities lie in the calculation results for water areas and construction land. The substantial difference in water areas is attributed to the distinct importance assigned to evaluation indicators between the two models. Moreover, the notable difference in construction land arises from the use of different quantification methods for evaluation indicators. In general, the EI model has suggested to be more comprehensive and effectively captures the annual comprehensive status of the ecological environment and the multiyear change characteristics of the administrative region. On the other hand, RSEI models exhibit greater flexibility and ease of implementation, independent of spatial and temporal scales. These findings contribute to a clearer understanding of the models' advantages and limitations, offering guidance for decision makers and valuable insights for the improvement and development of ecological environmental quality evaluation models.