全球变暖背景下多年冻土融化导致的土壤水分状况的改变影响着植物的根系觅食行为.选取对气候变化十分敏感的青藏高原为研究区域,以多年冻土广泛分布的风火山地区高寒小嵩草(Kobresia pygmaea)草甸和藏嵩草(Kobresia tibetica)沼泽化草甸为研究对象,采用开顶式增温小室(open top chambers,OTCs)模拟气候变暖,开展增温试验(2012-2019年).监测和收集2019年生长季(5-9月)地上20 cm高度处的空气温度(AT)和地下5 cm深度处的土壤湿度(SM)数据,测定并计算得到2019年枯黄期两种草甸表层(0-10 cm)土壤根系形态塑性指标:衡量觅食尺度的总根长(TRL)、根直径(RD)、根表面积(RSA)、根体积(RV)、比根长(SRL)、比根面积(SRA)、根组织密度(RTD)和表征觅食精度的根系生物量(RB),根系生理塑性指标:碳含量(RCC)、氮含量(RNC)、非结构性碳水化合物含量(RNSCs)、可溶性糖含量(RSSC)、淀粉含量(RSC)和可溶性糖比淀粉(RSSC/RSC),以了解多年冻土存在时,青藏高原两种典型高寒草甸根系觅食策略对增温的响应特征.结果表明:(1)增温后小嵩草草甸和藏嵩草沼泽化草甸生长季月平均SM分别下降和上升;(2)增温显著增大了小嵩草草甸RB、SRA和藏嵩草沼泽化草甸RV、SRL,并显著减小了小嵩草草甸SRL和藏嵩草沼泽化草甸RTD;(3)增温显著升高两种草甸RCC、RNSCs、RSSC、RSC和小嵩草草甸RSSC/RSC;(4)增温对小嵩草草甸根系形态塑性指标(RB、SRL、SRA)和根系生理塑性指标(RCC、RNSCs、RSSC、RSC、RSSC/RSC)的影响效应均值分别为0.29和0.91,对藏嵩草沼泽化草甸根系形态塑性指标(RV、SRL、RTD)和根系生理塑性指标(RCC、RNSCs、RSSC、RSC)的影响效应均值分别为0.27和0.87;(5)增温对小嵩草草甸根系觅食精度(RB)和觅食尺度(SRL、SRA)的影响效应均值分别为0.66和0.10.研究结果表明了根系生理塑性在增温对多年冻土区两种高寒草甸表层土壤根系影响中的重要性,小嵩草草甸表层土壤根系对增温的响应在根系形态塑性上更依赖于觅食精度的改变.(图4表2参62)
Responses of root foraging strategies to experimental warming in two typical alpine meadows in permafrost region of the Qinghai-Tibet Plateau
Changes in soil moisture caused by permafrost melting under global warming affect plant root foraging.In this study,the Qinghai-Tibet Plateau,which is very sensitive to climate change,was selected as the research area,along with Kobresia pygmaea meadow and Kobresia tibetica swamp meadow in the Feng Huoshan region,where permafrost is widely distributed.We used open-top chambers(OTCs)to simulate climate warming and conducted artificial warming experiments from 2012 to 2019.Air temperature(AT)data at a height of 20 cm and soil moisture(SM)data at a depth of 5 cm were obtained using sensors and data collectors(MG-EM50)during the growing season(May-September 2019).The root morphological plasticity indices,including total root length(TRL),root diameter(RD),root surface area(RSA),root volume(RV),specific root length(SRL),specific root area(SRA),root tissue density(RTD)representing root foraging scale and root biomass(RB)characterizing root foraging accuracy,root physiological plasticity indices,such as root carbon content(RCC),root nitrogen content(RNC),root non-structural carbohydrate content(RNSCs),root soluble sugar content(RSSC),root starch content(RSC),and root soluble sugar to starch content ratio(RSSC/RSC)of root samples in soil surface layers(0-10 cm)of two meadows were measured using a scanner(Epson)and analyzing software(WinRHIZO)in the yellowing period of 2019 and was calculated to understand the response characteristics of root foraging strategies for two typical alpine meadows on the Qinghai-Tibet Plateau to warming in the presence of permafrost.The results showed that:(1)warming decreased and increased the average soil moisture(SM)in the soil shallow layer(5 cm depth)of the K.pygmaea meadow and K.tibetica swamp meadow,respectively;(2)warming significantly increased RB and SRA in the K.pygmaea meadow and RV and SRL in the K.tibetica swamp meadow,while significantly decreasing SRL in the K.pygmaea meadow and RTD in the K.tibetica swamp meadow;(3)warming remarkably increased the RCC,RNSCs,RSSC,and RSC in two meadows,and the RSSC/RSC in the K.pygmaea meadow;(4)the average effect size of warming on root morphological(RB,SRL,SRA)and root physiological plasticity indices(RCC,RNSCs,RSSC,RSC,RSSC/RSC)in the K.pygmaea meadow were 0.29 and 0.91,respectively,and average effect size of warming on root morphological(RV,SRL,RTD)and root physiological plasticity indices(RCC,RNSCs,RSSC,RSC)in the K.tibetica meadow were 0.27 and 0.87,respectively;(5)the average effect sizes of warming on root foraging accuracy(RB)and root foraging scale(SRL,SRA)in the K.pygmaea meadow were 0.66 and 0.10,respectively.The results of our study highlight the importance of root physiological plasticity in the influence of artificial warming on roots in the soil surface layers of two alpine meadows in the permafrost region.Root morphology plasticity in the surface soil root of the K.pygmaea meadow to warming was more dependent on changes in root foraging accuracy.
万方数据
维普
