首页> 中文期刊> 《植物营养与肥料学报》 >红砂根系形态和功能特征对CO2浓度升高和降水量变化的响应

红砂根系形态和功能特征对CO2浓度升高和降水量变化的响应

         

摘要

[目的]探明CO2浓度升高及降水变化对红砂(Reaumuria soongorica)根系形态结构及其功能特征的影响,为预测未来荒漠生态系统中CO2浓度升高及降水变化下荒漠植物红砂的生长提供基础数据和理论参考.[方法]采用盆栽试验和开顶式CO2控制气室,研究了红砂根系形态及功能特征对不同CO2浓度变化(350、550和700μmol/mol)和降水处理[-30%、-15%、100%(自然降水)、+15%、+30%]的响应.[结果]CO2浓度升高、降雨量变化及二者的交互作用对红砂总根长、总表面积、根生物量和根平均直径均有极显著影响(P<0.01),CO2浓度升高和降水量变化对红砂根冠比、比根长和比表面积均有极显著影响(P<0.01),而两者的交互作用对其影响不显著(P>0.05).CO2浓度升高和降水量变化显著提高了红砂总根长、总表面积、总根体积、根生物量和根平均直径(P<0.01),但总根长、总表面积、总根体积和根平均直径在降水量减少时的增加量大于降水量增加时的增加量(平均高出18.53%),生物量在降水量增加时的增幅大于降水量减少时的增幅(平均高出120.84%).红砂根冠比在降水量减少时比降水量增加时提高更显著(平均高出57.14%),CO2浓度升高显著降低了红砂的根冠比.降水量增多,红砂比根长和比面积显著降低,CO2浓度升高则显著提高了这两个指标.降水量增加显著提高红砂根系的碳、氮含量,CO2增加显著增加根系碳含量而降低氮含量;CO2升高和各降水量的耦合导致红砂根系的C/N随CO2的升高而升高,随降水量的增加而呈波浪形变化.[结论]CO2升高对除红砂根冠比以外的根系形态指标具有显著的正效应,总根长、总根体积、根平均直径、根冠比、比根长和比表面积对降水量减少的响应更为显著,而总表面积和根生物量则对降水增加的响应较为显著.红砂可通过升高C/N来响应CO2浓度的升高,但C/N比对CO2与降水量耦合的响应则因CO2浓度及降水量多少而不同.%[Objectives]Reaumuria soongorica is a dominant desert steppe plant in the arid region of China. The objective of the study was to evaluate the interaction of elevated CO2 concentration and precipitation on root morphology and root function of the desert plant, to provide scientific reference for the growth of R. soongorica under the background climate change in the future.[Methods]A pot experiment was conducted with three CO2 concentrations (350, 550 and 700 μmol/mol) and five precipitation levels. Taking the local natural precipitation as control (100%), precipitation of 30% less (-30%), 15% less (-15%), 15% more (+15%) and 30% more (+30%) were designed. The total root length, total root surface area, total root volume, root average diameter, root biomass, root/shoot ratio, specific root length, specific root area, carbon content, nitrogen content and C/N of R.soongorica. were investigated.[Results]The total root length, total root surface area, root biomass and average diameter of R. soongorica were significantly affected by both the CO2 concentration and precipitation and their interaction (P < 0.01), while the root/shoot ratio, specific root length and specific root area of R. soongorica were significantly affected by CO2 concentration and precipitation (P < 0.01), but not by the synergetic effects. The increases of total root length, total root surface area, total root volume and root average diameter under the-30% and -15% less precipitation treatments were averagely18.53% higher than those under the +15% and+30% more treatments (P < 0.05),while the root biomass under the +15% and +30% treatments were120.8%higher than those under the -30% and -15% less treatments. The root/shoot ratios under the -30% and -15%less treatments were 57.1% higher than those under the +15% and +30% more treatments(P < 0.01), and the root/shoot ratios in all the precipitation treatments were significantly decreased by the elevated CO2 concentration. The specific root length and specific root area were decreased significantly with the precipitation increased from -30% to +30%, and they were increased obviously by the elevated CO2 concentration. The carbon and nitrogen contents were increased significantly with the precipitation increased from -30% to +30%. Under the high CO2 concentration, the carbon content was increased and nitrogen content was decreased. The C/N ratios in roots of R. soongoricawere were significantly increased under the high CO2 concentration, and there was a fluctuant variation of C/N according to the precipitation increased.[Conclusions]The elevation of CO2 concentration has a positive effect on root morphology indexes except the root/shoot ratio. Under the high CO2 concentration, the total root length, total root volume, root average diameter, root/shoot ratio, specific root length and specific root area are significantly affected by low precipitation, while the total root surface area and root biomass are affected by the high precipitation. The root C/N of R. soongorica has positive response to the elevated CO2 concentration, while the response of C/N to the interaction of CO2 and precipitation will not be predicted, depending on the different CO2 concentration and precipitation.

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