| 刘鹏,张紫霞,王妍,刘云根.普者黑流域土地利用及“源-汇”景观的氮磷输出响应研究[J].农业环境科学学报,2020,39(6):1332-1341. |
| 普者黑流域土地利用及“源-汇”景观的氮磷输出响应研究 |
| Effect of land use and the source-sink landscape on nitrogen and phosphorus export in the Puzhehei watershed |
| 投稿时间：2019-12-04 |
| DOI：10.11654/jaes.2019-1334 |
| 中文关键词: 土地利用 景观格局 空间负荷对比指数（LWLI） 氮输出 磷输出 普者黑 |
| 英文关键词: land use landscape pattern location-weighted landscape contrast index(LWLI) nitrogen export phosphorus export Puzhehei |
| 基金项目:国家自然科学基金项目（31560237，31760245）；云南省教育厅基金研究生项目（2019Y0138） |
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| 中文摘要: |
| 以滇东南典型岩溶流域普者黑为研究对象，在将流域划分为26个子流域的基础上，以2018年3个水期各子流域的水质数据为依据，结合子流域内土地利用结构和景观格局特征，采用相关性分析、冗余分析和回归分析，探讨流域氮、磷输出与景观特征指数的定量关系。结果表明：丰水期氮、磷输出要高于枯水期和平水期，全流域从外围到中部呈"汇"景观逐渐减小，"源"景观逐渐增大趋势，耕地是流域氮、磷输出的主要"源"景观，水域具有改善水质的"汇"景观功能；耕地、水域面积比例和斑块密度、香农多样性指数与水质之间相互关系显著，说明农业活动是影响普者黑流域氮、磷输出的主要原因，景观的破碎化促使了这一生态过程的发展；3个水期景观空间负荷对比指数（LWLI）与TP、PO43--P和NH4+-N均呈正相关，枯水期和丰水期时LWLI与所有水质指标均集中于同一象限，LWLI与丰水期TP的回归系数最大，R2为0.856，表明LWLI对水质指标的解释能力远大于传统景观指数，对水质评价及预测有重要意义。 |
| 英文摘要: |
| 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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