The Influence of Land Use Change on Key Ecosystem Services and Their Relationships in a Mountain Region from Past to Future (1995–2050)

Assessing the impact of land use land cover change on regulatory ecosystem services of subtropical scrub forest, Soan Valley Pakistan

This study investigated the effect of land use land cover (LULC) changes on carbon sequestration in the Hayat-ul-Mir subtropical scrub reserve forest, Pakistan. Supervised maximum likelihood classification of Landsat satellite imagery was done to assess spatio-temporal changes in LULC during 2007, 2013 and 2019. The CA–Markov model was used to simulate LULC of 2030. Spatial LULC data and carbon pools data was processed in Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) carbon model to investigate the effect of LULC on future carbon dynamics. The analysis revealed increase in cover of A. modesta and O. ferruginea and decrease in agriculture, built up and barren area of forest during 2007–2019 and 2030. The analysis also showed that the forest would additionally sequester 111 Mg C with an overall Net Present Value of $4112.05 in year 2030. The analysis revealed LULC changes on 25% area with increase and decrease in the value of ecosystem service (at some location) from carbon storage and loss as CO₂ emissions respectively depending on the type of LULC converted. The study is helpful in identifying areas of potential carbon sequestration to maximize net benefits from management interventions.

Analysis of the Driving Force of Land Use Change Based on Geographic Detection and Simulation of Future Land Use Scenarios

Land use and land cover changes (LULCC) are the result of the combined action of many influencing factors such as nature, society, economy and politics. Taking Chongqing as an example, the driving factors of urban land expansion in Chongqing from 1999 to 2019 are analyzed using a geographic detection (GD) method. Based on this analysis, a land use scenario of Chongqing in 2029 is simulated by an Artificial Neural Network-Cellular Automata model. The results of the analysis of factors affecting land use change show that five factors have a significance >0.05: population, distance from central city, school density, GDP and the distance from railway, showing that these factors have a high impact on LULCC in Chongqing. In addition, the results of risk detection analysis show that areas with a population >50/km2; the areas with a distance <200 km from the city center; areas with a school density >5/km2; areas with a high GDP; and areas with a distance <25 km from the railway have a greater impact on urban land use change than other areas. The land use scenario in 2029 also is simulated based on the land use situation in 2019. The predicted results clearly reflect a land use change trend of increasing urban land and decreasing agricultural land in the region. These land use changes are especially related to the expansion of the population, economy, roads, and schools in the process of urbanization. This analysis also shows that the GD-ANN-CA model developed in this paper is well suited to urban land use simulation.

Ecosystem Service Values in the Dongting Lake Eco-Economic Zone and the Synergistic Impact of Its Driving Factors

Ecosystem service values (ESVs) are crucial to ecological conservation and restoration, urban and rural planning, and sustainable development of land. Therefore, it is important to study ESVs and their driving factors in the Dongting Lake Eco-Economic Zone (Dongting Lake). This paper quantifies the changes in ESVs in the Dongting Lake using land use data from 2000, 2005, 2010 and 2018. The eXtreme Gradient Boosting (XGBoost) model is used to study the effects of individual driving factors and the synergistic effects of these driving factors on ESVs. Our analysis suggests that: (1) From 2000 to 2018, the largest dynamic degree values in the Dongting Lake are in unused land types, followed by construction lands and wetlands. The ESVs of the Dongting Lake show an increasing trend, with those of forestlands being the highest, accounting for approximately 44.65% of the total value. Among the ESVs functions, water containment, waste treatment, soil formation and protection, biodiversity conservation and climate regulation contribute the most to ESVs, with a combined contribution of 76.64% to 76.99%; (2) The integrated intensity of anthropogenic disturbance shows a U-shaped spatial distribution, decreasing from U1 to U3. The driving factors in descending order of importance are the human impact index, total primary productivity (GPP), slope, elevation, population, temperature, gross domestic product, precipitation and PM2.5; (3) When the GPP is low (GPP < 900), the SHAP (SHapley Additive exPlanation) value of the high human impact index is greater than zero, indicating that an increase in GPP increases the ESVs in the Dongting Lake. This study can provide technical support and a theoretical basis for ecological environmental protection and ecosystem management in the Dongting Lake.

Spatio-Temporal Change of Multiple Ecosystem Services and Their Driving Factors: A Case Study in Beijing, China

Driven by rapid urbanization, land use patterns have undergone dramatic changes, which have in turn influenced ecosystem services (ESs). The government has implemented ecological compensation and conservation actions to mitigate this negative impact, especially in metropolises. However, whether these measures will have the desired effect remains unclear. Therefore, understanding the spatio-temporal characteristics of ESs and their driving factors are crucial for regional development. In this study, we quantified carbon storage, water yield and soil conservation services based on land use maps. A Geographical Detector (GD) was used to analyze the driving mechanisms of ES changes in Beijing from 1985 to 2020. The results showed that (1) the obvious landscape pattern changes are urbanization, afforestation and cultivated land degradation in Beijing, (2) the three services showed an increasing trend overall, but the changes were different in each period, (3) in general, land use change is the main factor affecting ESs, and the urbanization and afforestation contributed the most. These results suggest that in highly urbanized metropolises, humans can still balance the demands of regional development and ESs reasonable planning. This study highlights the importance of afforestation for ESs, the necessity of harmonizing environmental concerns and human activities, and the need to conduct ecological management in Beijing to protect the ecological environment and coordinate regional development.