Landscape Pattern Evolution Processes and the Driving Forces in the Wetlands of Lake Baiyangdian

The spatiotemporal features of land use changes and the evolution process of landscape pattern from 1980 to 2017 were investigated using historical satellite images from a Landsat Thematic Mapper (TM) for 1980, 1990, 2000, 2005, 2010 and 2017 in the wetlands of Lake Baiyangdian in the North China Plain (NCP). Landscape pattern indices were used to quantify landscape changes in wetlands, and a redundancy analysis (RDA) was conducted to analyze the driving forces and quantitatively explain the effects of human activities and natural changes on wetland fragmentation. The results showed that the total wetland area was 234.4 km2 in 1980 but it decreased by 8.1% at an average decrease rate of 0.5 km2 per year. The dominant transition between land use types was from natural wetlands to artificial wetlands, and wetland conversion to dry land and residential land. The RDA results suggested that agricultural activities and total population were the main driving factors affecting wetland landscape. Additionally, climate change provided a potentially favorable environment for agricultural development, due to the increased temperatures and decreased wind speeds. Additionally, governmental policy changes and dam construction also played the roles in land use changes.

Effects of Intermittent Water Allocation on Vegetation Dynamics in Lake Baiyangdian, North China

The ecological effects of intermittent water supplement in Lake Baiyangdian were analyzed with an NDVI time series based on the data from 1 April 1998 to 31 July 2008. Four NDVI categories were extracted, and twelve stages were grouped based on the specific replenishment time of water allocation. STR (a seasonal-trend decomposition procedure based on regression) and its corresponding linear regression and abrupt change detection were used to highlight the temporal variations in vegetation under the effects of water allocation. ANOVA was used to identify the response quality of the vegetation in each stage. The results showed that the significant increasing trend of each NDVI category was detected by linear regression (p < 0.001). The 95% abrupt change intervals showed uncertainty and complexity in the immediate vegetation response to water division times. The most abrupt changes were detected in the growing seasons. The extremely significant differences in NDVI variation before and after water allocations were detected by ANOVA (p < 0.001, t-test). The longer the duration of water allocation was maintained, the higher the detection of vegetation coverage was relatively. The increased vegetation coverage benefited from the constant water supply. Our results provide evidence of vegetation responses to intermittent water divisions. The positive effects of water allocation on regional ecological restoration were confirmed. This study strengthened the water division effects of regional vegetation restoration and provided a practical strategy for an effective implementation of water allocation.