期刊
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
卷 29, 期 23, 页码 34624-34636出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s11356-021-15842-x
关键词
Landscape pattern metrics; Nitrogen output; InVEST model; Stepwise multiple regression analysis; Taihu Lake Basin
资金
- Strategic Priority Research Program of the Chinese Academy of Sciences [XDA23020201]
The changes in landscape pattern caused by rapid urbanization and intensive agricultural activities have put significant pressure on regional water purification services. The relationship between landscape metrics and nitrogen-related ecosystem services has been a major focus of research, particularly in highly developed reticular river network areas. The study found that different regions showed varying responses of nitrogen output to landscape patterns, highlighting the importance of controlling nitrogen output in sensitive areas with high pollution sources, such as the Taihu Lake Basin.
Landscape pattern changes induced by rapid urbanization and intensified agricultural activities have exerted great pressure on regional water purification services. Relationship between landscape metrics and nitrogen-related ecosystem services has been a major concern of many scholars and has been widely used for guidance for land use and cover (LULC) management. However, clear zonal differences may exist, especially in highly developed reticular river network area, thus limiting our understanding of nitrogen output (NOP) to landscape pattern in the details. The spatial distribution of regional NOP was obtained based on the InVEST model. The zonal responses of NOP to landscape patter were examined under hydraulic subregions and subbasin scale. The results show that the unit value of average NOP in the Taihu Lake Basin (TLB) was 146.14 (kg/km(2)), and the total output reached 23677.92 t in 2020. The simulation NOP showed reasonable agreement with verified water quality observations in the lake inlet stations, with an R-2 of 0.76. In terms of space composition, merely cropland have significant effects on NOP in the whole basin scale, while the explanatory variables include cropland and developed land in Pudong (PD), Puxi (PX), Wuchengxiyu (WC), and Hangjiahu (HJ) regions. In Huxi (HX) and Yangchengdianmao (YC) regions, cropland and forest are the significant impact types, while in (Zhexi) ZX region, cropland, developed land, and forest are significant impact types. In the space configuration, the percentage of landscape (PLAND) or largest patch index (LPI) of cropland showed positive effects about NOP, whether in the whole basin or the hydraulic subregions. Edge density (ED) (-3.48), number of patches (NP) (-3.91), and percentage of like adjacencies (PLAND) (-2.80) of the forest exhibit negative correlations with NOP, in the HX, ZX, and YC region, respectively. It displays diversiform in the response of NOP to the landscape metric of developed land, which speculate that the heterogeneity of developed land can also have a constraint on NOP, in the highly urbanized areas with less forest area. In addition, the total nitrogen output of the TLB needs to be controlled, especially in HJ region which was identified as the sensitive area of pollution sources with the largest NOP and should be paid more attention to. Compared with the administrative management unit, it is more reasonable to control and manage the pollution sources by referring to the hydraulic subregions and subbasin units. Senior managers are required to strengthen communication and cooperation with hydraulic subregions across administrative regions. However, when managing NOP through the landscape modifications, measures should be taken to reduce the aggregation of nitrogen sources and increase the fragmentation of nitrogen sinks. As for high aggregation developed and agricultural land regions, the types of land used should be enriched to help the sustainable development.
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