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| Effect of land use and the source-sink landscape on nitrogen and phosphorus export in the Puzhehei watershed |
| Received:December 04, 2019 |
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| KeyWord:land use;landscape pattern;location-weighted landscape contrast index(LWLI);nitrogen export;phosphorus export;Puzhehei |
| Author Name | Affiliation | E-mail | | LIU Peng | College of Ecology and Environment, Southwest Forestry University, Kunming 650224, China | | | ZHANG Zi-xia | College of Ecology and Environment, Southwest Forestry University, Kunming 650224, China | | | WANG Yan | Rocky Desertification Research Institute, Southwest Forestry University, Kunming 650224, China | wycaf@126.com | | LIU Yun-gen | Yunnan Key Laboratory for Ecological Environment Evolution and Pollution Control in Mountainous Rural Areas, Southwest Forestry University, Kunming 650224, China | |
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| Abstract: |
| Based on the water quality data, land use structure, and landscape index of 26 sub-watersheds in Puzhehei examined from April to October 2018, the relationship between N and P export and the landscape index was analyzed by correlation analysis, redundancy analysis, and regression analysis. Our data showed that N and P export in the high-water period was higher, the amount of sink landscapes decreased, and the amount of source landscapes increased in the whole basin from the periphery areas to the middle areas. Farmland was the main source landscape and waters had the function of a sink landscape. The farmland, water, patch density(PD), and Shannon's diversity index(SHDI)were significantly related to water quality, which meant that agricultural activities were the main sources of N and P export and the landscape fragmentation degree promoted this ecological process. There was a positive correlation between the location-weighted landscape contrast index(LWLI)and total phosphorus(TP), PO43--P, and NH4+ -N. The LWLI and all the water quality parameters were in the same quadrant. The regression coefficient(R2)between the LWLI and TP was 0.856 during the high-water period, which meant that the LWLI was better than the traditional landscape index for explaining water quality parameters. This has great significance for water quality assessment and prediction. |
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