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Moister soils at elevated CO2 stimulate root biomass but suppress aboveground biomass production in Lolium perenne

多年生黑麦草 农学 生物量(生态学) 多年生植物 牧场 环境科学 含水量 草原 灌溉 单作 土壤水分 生长季节 黑麦草 生物 禾本科 土壤科学 岩土工程 工程类
作者
Mark J. Hovenden,Amanda L. Sinclair,Rose Brinkhoff,Kate Stevenson,Zachary A. Brown,Meagan Porter,Anna Flittner,Marion Nyberg,RP Rawnsley
出处
期刊:Crop & Pasture Science [CSIRO Publishing]
卷期号:75 (1)
标识
DOI:10.1071/cp22287
摘要

Context Increases in atmospheric carbon dioxide concentration ([CO2]) drive increases in biomass production via impacts on photosynthesis and water use. In grasslands, the scale of this stimulation is related to soil water availability. Recently, it has become clear that the way precipitation controls elevated CO2 (eCO2) effects on grassland biomass is strongly seasonal but no mechanism yet exists to explain these observations. Aims The aims of this study were to determine how seasonal water availability affects aboveground, belowground and total biomass responses of a perennial ryegrass pasture to [CO2]. Methods We established the TasFACE2 experiment in a well-fertilised perennial ryegrass (Lolium perenne) monoculture with four seasonal irrigation schedules and three [CO2]. Key results The total biomass production of perennial ryegrass pasture was strongly stimulated by eCO2, but this extra biomass was preferentially allocated to belowground growth. The relationship between soil water content and aboveground biomass varied seasonally but there was a strong positive relationship between soil water content and root biomass production in all seasons. Conclusions Increases in soil moisture caused by eCO2 contributed to increases in root growth, but root biomass production was also stimulated directly by eCO2. Restriction of irrigation, therefore, suppressed the belowground response to eCO2 and created a non-linear response of biomass to CO2 concentration. Implications Antagonistic above- and belowground responses mean that the rising [CO2] might not increase pasture production in the manner generally predicted.

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