Telecoupling between urban expansion and forest ecosystem service loss through cultivated land displacement: A case study of Zhejiang Province, China.

Urbanization can either directly occupy forests or indirectly lead to forest loss elsewhere through cultivated land displacement, resulting in further forest fragmentation and ecosystem service (ES) loss. However, the effects of urban expansion on forest area and ESs are unknown, and this is especially true for indirect effects. Taking Zhejiang Province, China, a typical deforested province, as an example, this study quantified the direct and indirect effects of urban expansion on forest area and five ESs (timber yield, water yield, carbon sequestration, soil conservation, and biodiversity) from 2000 to 2020, explored the relationship between forest structure (forest proportion, mean patch area, edge density, and mean euclidean nearest neighbor distance) change and ESs, and revealed the telecoupling of urban expansion and forest loss and cascade effects among urbanization, deforestation, forest structure, and ESs. The results indicated that the indirect forest loss (4.30%-6.15%) caused by cultivated land displacement due to urban expansion was larger than the direct forest loss (2.42%). Urban expansion has a greater negative impact on carbon sequestration (6.40%-8.20%), water yield (6.08%-7.78%), and biodiversity (5.79%-7.44%) than on timber yield (4.77%-6.17%) and soil conservation (4.43%-5.77%). The indirect forest ES loss was approximately 2.83-4.34 times greater than the direct forest ES loss. Most forest ESs showed a nonlinear significant positive correlation with changes in forest proportion and mean patch area and a significant nonlinear negative correlation with changes in edge density and mean Euclidean nearest neighbor distance (p < 0.05). There is telecoupling between urban expansion in one region and forest ES loss in other distant regions. This study contributes to guiding sustainable forest conservation and management globally.

Projecting the response of ecological risk to land use/land cover change in ecologically fragile regions.

Anthropogenic activities have dramatically altered land use/land cover (LULC), leading to ecosystem service (ES) degradation and further ecological risks. Ecological risks are particularly serious in ecologically fragile regions because trade-offs between economic development and ecological protection are prominent. Thus, ways in which to assess the response of ecological risks to LULC change under each development scenario in ecologically fragile regions remain challenging. In this study, future LUCC and its impact on ESs under four development scenarios in 2040 in western Jilin Province were predicted using a patch-generating land use simulation model and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model. Ecological risk was assessed based on future LUCC possibilities, and potential ES degradation and potential drivers of ecological risks were explored using a geographic detector. The results showed that the cropland development scenario (CDS) would experience large-scale urbanization and cropland expansion. Carbon storage (CS), habitat quality (HQ), and water purification (WP) degraded the most under the CDS, and grain yield (GY) and water yield (WY) degraded the most under the ecological protection scenario (EPS). The LUCC probability under the CDS (14.37 %) was the highest, while the LUCC probability under the comprehensive development scenario (CPDS) (8.68 %) was the lowest. The risk of WP degradation was greatest under the CDS, but the risk of soil retention (SR) degradation was greatest under the natural development scenario (NDS), EPS, and CPDS. Ecological risk coverage was the largest (98.04 %), and ecological risks were the highest (0.21) under the CDS, while those under the EPS were the opposite. Distance to roads and population density had a higher impact on ecological risks than other drivers. Further attention should be given to the ecological networks and pattern establishment in urbanized regions. This study will contribute to risk prevention and sustainable urban and agricultural development.

Water quality pollution assessment and source apportionment of lake wetlands: A case study of Xianghai Lake in the Northeast China Plain.

Surface water pollution has always posed a serious challenge to water quality management. Improving water quality management requires figuring out how to comprehend water quality conditions scientifically and effectively as well as quantitatively identify regional pollution sources. In this study, Xianghai Lake, a typical lake-type wetland on the Northeast China Plain, was taken as the research area. Based on a geographic information system (GIS) method and 11 water quality parameters, the single-factor evaluation and comprehensive water quality index (WQI) methods were used to comprehensively evaluate the water quality of the lake-type wetland in the level period. Four key water quality parameters were determined by the principal component analysis (PCA) method, and more convenient comprehensive water quality evaluation models, the minimum WQI considering weights (WQImin-w) and the minimum WQI without considering weights (WQImin-nw) were established. The multiple statistical method and the absolute principal component score-multiple liner regression (APCS-MLR) model were combined to analyse the lake pollution sources based on the spatial changes in pollutants. The findings demonstrated that the WQImin-nw model's water quality evaluation outcome was more accurate when weights were not taken into account. The WQImin-nw model can be used as a simple and convenient way to comprehend the variations in water quality in wetlands of lakes and reservoirs. It was concluded that the comprehensive water quality in the study area was at a "medium" level, and CODMn was the main limiting factor. Nonpoint source pollution (such as agricultural planting and livestock breeding) was the most important factor affecting the water quality of Xianghai Lake (with a comprehensive contribution rate of 31.65%). The comprehensive contribution rates of sediment endogenous and geological sources, phytoplankton and other plants, and water diversion and other hydrodynamic impacts accounted for 25.12%, 19.65%, and 23.58% of the total impact, respectively. This study can provide a scientific method for water quality assessment and management of lake wetlands, and an effective support for migration of migratory birds, habitat protection and grain production security.

Response of vegetation variation to climate change and human activities in semi-arid swamps.

Vegetation is a sensitive factor in marsh ecosystems, which can provide nesting sites, foraging areas, and hiding places for waterfowl and can affect their survival environment. The Jilin Momoge National Nature Reserve, which consists of large areas of marshes, is located in the semi-arid region of northeast China and is an important stopover site for the critically endangered species of the Siberian Crane (Grus leucogeranus). Global climate change, extreme droughts and floods, and large differences in evaporation and precipitation in this region can cause rapid vegetation succession. In recent years, increased grain production and river-lake connectivity projects carried out in this area to increase grain outputs and restore wetlands have caused significant changes in the hydrological and landscape patterns. Therefore, research on the response of variation trends in vegetation patterns to the main driving factors (climate change and human activities) is critical for the conservation of the Siberian Crane. Based on the Google Earth Engine (GEE) platform, we obtained and processed the Normalized difference vegetation index (NDVI) data of the study area during the peak summer vegetation period for each year from 1984 to 2020, estimated the annual vegetation cover using Maximum value composites (MVC) method and the image dichotomy method, calculated and analyzed the spatial and temporal trends of vegetation cover, explored the response of vegetation cover change in terms of climate change and human activities, and quantified the relative contribution of both. The results revealed that first, from the spatial and temporal changes, the average annual growth rate of regional vegetation was 0.002/a, and 71.14% of the study area was improved. The vegetation cover showed a trend of degradation and then recovery, in which the percentage of high vegetation cover area decreased from 51.22% (1984-2000) to 28.33% (2001-2005), and then recovered to 55.69% (2006-2020). Second, among climate change factors, precipitation was more correlated with the growth of vegetation in the study area than temperature, and the increase in precipitation during the growing season could promote the growth of marsh vegetation in the Momoge Reserve. Third, overall, human activities have contributed to the improvement of vegetation cover in the study area with the implementation of important ecological projects, such as the return of farmland to wetlands, the return of grazing to grass, and the connection of rivers and lakes. Fourth, climate change and human activities jointly drive vegetation change, but the contribution of human activities in both vegetation improvement and degradation areas (85.68% and 78.29%, respectively) is higher than that of climate change (14.32% and 21.71%, respectively), which is the main reason for vegetation improvement or degradation in the study area. The analysis of vegetation pattern change within an intensive time series in semi-arid regions can provide a reference and basis for studying the driving factors in regions with rapid changes in vegetation and hydrological conditions.