[Objectives]To study the effects of fungi Fusarium sp.to rhizosphere soil and physiological characteristics of Camellia oleifera Abel.[Methods]We investigated the effects of Fusarium sp.to rhizosphere soil nutrient el...[Objectives]To study the effects of fungi Fusarium sp.to rhizosphere soil and physiological characteristics of Camellia oleifera Abel.[Methods]We investigated the effects of Fusarium sp.to rhizosphere soil nutrient element content and metabolites of C.oleifera.C.oleifera was inoculated with the suspension of Fusarium sp.in pot experiments and ammonium-N,available phosphorus,available potassi-um,organic matter,enzymes and pH of rhizosphere soil,MDA content,activity of SOD,POD of C.oleifera leaves were analyzed.[Results]Fusarium sp.stress significantly inhibited soil enzyme activities and significantly reduced available phosphorus content,especially for phospha-tase and sucrase.Antioxidant enzyme activities in C.oleifera tissues showed that Fusarium sp.stress significantly increased MDA and SOD enzyme activities and decreased POD enzyme activity.Especially,SOD enzyme activity was elevated by 53.86%compared with the CK group.In addition,analysis of the content of major metabolites in C.oleifera leaves showed that Fusarium sp.stress significantly reduced the content of total flavonoids,quercetin,isoquercitrin and isoquercitrin in C.oleifera leaves by 7.80%,50.00%and 75.90%,respectively.[Conclusions]Our results are an important step which showed strong resistance of C.oleifera and can give a novel insight for researches on the effects in the rhizosphere soil enzyme,soil nutrient elements and metabolites of C.oleifera under the Fusarium sp.too.展开更多
Information on soil hydraulic properties(SHPs)and soil moisture(SM)is essential to understand and model water and energy cycles at terrestrial surfaces.However,information regarding these soil properties in existing d...Information on soil hydraulic properties(SHPs)and soil moisture(SM)is essential to understand and model water and energy cycles at terrestrial surfaces.However,information regarding these soil properties in existing datasets is often scarce and inaccurate for high,cold mountainous areas such as the Qinghai-Tibet Plateau(QTP).To help bridge this gap,we have compiled an SHP and SM dataset for the northeastern QTP(a major high,cold mountainous area)using measurements of soil collected at 5 and 25 cm depths from 206 sampling sites,and in-situ observations from 32 SM monitoring stations at 5,15,25,40,and 60 cm depths.We used this dataset to explore large-scale variations(spatial and temporal)in SHPs and SM across the study area.We also evaluated several widely used SHP(soil texture,bulk density,and saturated hydraulic conductivity)and SM datasets derived by remote-sensing methods,reanalysis and data assimilation.Our datasets showed that SM significantly decreases from the southeastern part to the northwestern part in the study area,and SM decreases with increases in depth over 0–70 cm.Moreover,the regional annual SM showed decreased trend from 2014 to 2020 in the study area.Additionally,we detected substantial bias in the currently available large SHP datasets,which do not capture the spatial variability recorded in the in-situ observations.Especially,clay and sand estimates from both HWSD and SoilGrid datasets were significantly overestimated,and silt was significantly underestimated within the depth of 0–30 cm in the study area.We also found that SM values derived from remote sensing datasets fitted the in-situ SM observations better than those derived from the reanalysis data(which had higher bias)and data assimilation(which did not capture the temporal variability of SM).Our findings emphasize the unneglectable bias of the widely-used large-scale SHP datasets,especially for the soil texture data.Thus,an urgent need for large-scale field sampling of SHP in mountainous areas.The in-situ observation dataset presented here provides important information with unprecedented coverage and resolution regarding the SHP variability and long-term SM trends across a large,high,cold mountainous area,thereby enhancing our understanding of water cycles and energy exchange processes over the QTP.展开更多
基金Supported by Key Field Project of Education Department of Guizhou Province(QJHKYZ[2021]044)Forestry Research Project of Guizhou Province(QLKH[2021]11)+1 种基金Project of Guizhou Provincial Characteristic Key Laboratory(QJHKY[2021]002)National Natural Science Foundation of China(41761010).
文摘[Objectives]To study the effects of fungi Fusarium sp.to rhizosphere soil and physiological characteristics of Camellia oleifera Abel.[Methods]We investigated the effects of Fusarium sp.to rhizosphere soil nutrient element content and metabolites of C.oleifera.C.oleifera was inoculated with the suspension of Fusarium sp.in pot experiments and ammonium-N,available phosphorus,available potassi-um,organic matter,enzymes and pH of rhizosphere soil,MDA content,activity of SOD,POD of C.oleifera leaves were analyzed.[Results]Fusarium sp.stress significantly inhibited soil enzyme activities and significantly reduced available phosphorus content,especially for phospha-tase and sucrase.Antioxidant enzyme activities in C.oleifera tissues showed that Fusarium sp.stress significantly increased MDA and SOD enzyme activities and decreased POD enzyme activity.Especially,SOD enzyme activity was elevated by 53.86%compared with the CK group.In addition,analysis of the content of major metabolites in C.oleifera leaves showed that Fusarium sp.stress significantly reduced the content of total flavonoids,quercetin,isoquercitrin and isoquercitrin in C.oleifera leaves by 7.80%,50.00%and 75.90%,respectively.[Conclusions]Our results are an important step which showed strong resistance of C.oleifera and can give a novel insight for researches on the effects in the rhizosphere soil enzyme,soil nutrient elements and metabolites of C.oleifera under the Fusarium sp.too.
基金supported by the National Natural Science Foundation of China(Grant Nos.42030501,91125010,42101022)。
文摘Information on soil hydraulic properties(SHPs)and soil moisture(SM)is essential to understand and model water and energy cycles at terrestrial surfaces.However,information regarding these soil properties in existing datasets is often scarce and inaccurate for high,cold mountainous areas such as the Qinghai-Tibet Plateau(QTP).To help bridge this gap,we have compiled an SHP and SM dataset for the northeastern QTP(a major high,cold mountainous area)using measurements of soil collected at 5 and 25 cm depths from 206 sampling sites,and in-situ observations from 32 SM monitoring stations at 5,15,25,40,and 60 cm depths.We used this dataset to explore large-scale variations(spatial and temporal)in SHPs and SM across the study area.We also evaluated several widely used SHP(soil texture,bulk density,and saturated hydraulic conductivity)and SM datasets derived by remote-sensing methods,reanalysis and data assimilation.Our datasets showed that SM significantly decreases from the southeastern part to the northwestern part in the study area,and SM decreases with increases in depth over 0–70 cm.Moreover,the regional annual SM showed decreased trend from 2014 to 2020 in the study area.Additionally,we detected substantial bias in the currently available large SHP datasets,which do not capture the spatial variability recorded in the in-situ observations.Especially,clay and sand estimates from both HWSD and SoilGrid datasets were significantly overestimated,and silt was significantly underestimated within the depth of 0–30 cm in the study area.We also found that SM values derived from remote sensing datasets fitted the in-situ SM observations better than those derived from the reanalysis data(which had higher bias)and data assimilation(which did not capture the temporal variability of SM).Our findings emphasize the unneglectable bias of the widely-used large-scale SHP datasets,especially for the soil texture data.Thus,an urgent need for large-scale field sampling of SHP in mountainous areas.The in-situ observation dataset presented here provides important information with unprecedented coverage and resolution regarding the SHP variability and long-term SM trends across a large,high,cold mountainous area,thereby enhancing our understanding of water cycles and energy exchange processes over the QTP.
