青藏高原植被退化背景下土壤质量评价方法研究

Study on soil quality evaluation methods under the background of vegetation degradation in Qinghai-Tibet Plateau

在青藏高原西大滩至安多地区,根据植被退化的不同程度采集了154个土壤样品.通过主成分分析法确定了影响青藏高原多年冻土区高寒草地植被退化背景下土壤质量的最小数据集:碱解氮、盐分、全磷和有机质.根据影响土壤质量的最小数据集对青藏高原多年冻土区高寒草地土壤质量进行了评价,得出了植被退化下的土壤质量指数(SQI).结果表明,随着植被盖度的增加, SQI呈增加趋势,即植被盖度<30%时, SQI平均值为0.300~0.442;植被盖度30%~50%时, SQI平均值为0.308~0.457;植被盖度50%~70%时, SQI平均值为0.328~0.491;植被盖度>70%时, SQI平均值为0.327~0.532.分别采用线性与非线性得分函数计算得到不同的SQI,通过线性回归分析发现,基于最小数据集的SQI可以较详尽地表达出植被退化背景下土壤的质量变化,相较于SQIL-A、SQIL-WA、SQIN-A方法,基于最小数据集的非线性加权SQIN-WA能够对青藏高原多年冻土区高寒草地植被退化影响下的土壤做出更准确地评价(R2=0.686 4).

154 soil samples were collected according to the degree of vegetation degradation in the Xidatan to Anduo area of the hinterland thereof. The minimum data set affecting soil quality under the background of alpine grassland degradation in the permafrost regions was determined by the principal component analysis: alkali nitrogen, salt, total phosphorus and organic matter. According to the minimum data set in this respect, the soil quality of alpine grassland was evaluated, and the soil quality index(SQI)under vegetation degradation was obtained. The research showed that, with the increase of vegetation coverage, SQI also presented an increasing trend, i.e., when the vegetation coverage was less than 30%,the average value of the SQI was 0.300-0.442;when the vegetation coverage was 30%-50%, the average value of the SQI was 0.308-0.457;when the vegetation coverage was 50%-70%, the average value of the SQI was 0.328-0.491;and when the vegetation coverage was >70%, the average value of the SQI was0.327-0.532. Different soil quality indices were calculated by linear and nonlinear scoring functions respectively. The linear regression analysis of different soil quality indexes showed that the soil quality index based on minimum data set could express the soil quality under the background of vegetation degradation. Compared with the SQIL-A,SQIL-WA, SQIN-A methods, the non-linearly weighted soil quality index(SQIN-WA) based on minimum data set could accurately evaluate(R2=0.686 4) the soil under the vegetation degradation in permafrost regions of the Qinghai-Tibet Plateau.