The principles of remotely estimating grassland cover density in an alpine meadow soil from space lie in the synchronous collection of in situ samples with the satellite pass and statistically linking these cover dens...The principles of remotely estimating grassland cover density in an alpine meadow soil from space lie in the synchronous collection of in situ samples with the satellite pass and statistically linking these cover densities to their image properties according to their geographic coordinates. The principles and procedures for quantifying grassland cover density from satellite image data were presented with an example from Qinghai Lake, China demonstrating how quantification could be made more accurate through the integrated use of remote sensing and global positioning systems (GPS). An empirical model was applied to an entire satellite image to convert pixel values into ground cover density. Satellite data based on 68 field samples was used to produce a map of ten cover densities. After calibration a strong linear regression relationship (r2 = 0.745) between pixel values on the satellite image and in situ measured grassland cover density was established with an 89% accuracy level. However, to minimize positional uncertainty of field samples, integrated use of hyperspatial satellite data and GPS could be utilized. This integration could reduce disparity in ground and space sampling intervals, and improve future quantification accuracy even more.展开更多
Alpine meadow ecosystem is fragile and highly sensitive to climate change.An understanding of the allocation of above-and below-ground plant biomass and correlations with environmental factors in alpine meadow ecosyst...Alpine meadow ecosystem is fragile and highly sensitive to climate change.An understanding of the allocation of above-and below-ground plant biomass and correlations with environmental factors in alpine meadow ecosystem can result in better protection and effective utilization of alpine meadow vegetation.We chose an alpine meadow in the Qinghai-Tibetan Plateau of China as the study area and designed experimental warming plots using a randomized block experimental design.We used single-tube infrared radiators as warming devices,established the warming treatments,and measured plant above- (AGB) and below-ground biomass (BGB) during the growing seasons (May to September) in 2012 and 2013.We determined the allocation of biomass and the relationship between biomass and soil environment under the warming treatment.Biomass indices including above-ground biomass,below-ground biomass and the ratio of root to shoot (R/S) ,and soil factors including soil moisture and soil temperature at different depths were measured.The results showed that (1) BGB of the alpine meadow had the most significant allometric correlation with its AGB (y=298.7x~ (0.44) ,P〈0.001) ,but the relationship decreased under warming treatment and the determination coefficient of the functional equation was 0.102 which was less than that of 0.188 of the unwarming treatment (control) ; (2) BGB increased,especially in the deeper soil layers under warming treatment (P〉0.05) .At 0–10 cm soil depth,the percentages of BGB under warming treatment were smaller than those of the control treatment with the decreases being 8.52% and 8.23% in 2012 and 2013,respectively.However,the BGB increased 2.13% and 2.06% in 2012 and 2013,respectively,at 10–50 cm soil depths; (3) BGB had significant positive correlations with soil moisture at 100 cm depth and with soil temperature at 20–100 cm depths (P〈0.05) ,but the mean correlation coefficient of soil temperature was 0.354,greater than the 0.245 of soil moisture.R/S ratio had a significant negative correlation with soil temperature at 20 cm depth (P〈0.05) .The warmer soil temperatures in shallow layers increased the biomass allocation to above-ground plant parts,which leading to the increase in AGB;whereas the enhanced thawing of frozen soil in deep layers causing by warming treatment produced more moisture that affected plant biomass allocation.展开更多
Three alpine meadows were chosen from the eastern margin of the Qilian Mountain:Polygonum viviparum meadow(P),Stipa capillata grassland(S)and Rhododendron simsii shrub meadow(R);LI-8100 A soil CO2 flux auto-mon...Three alpine meadows were chosen from the eastern margin of the Qilian Mountain:Polygonum viviparum meadow(P),Stipa capillata grassland(S)and Rhododendron simsii shrub meadow(R);LI-8100 A soil CO2 flux auto-monitoring system and lab analysis were applied to analyze the soil organic carbon density,dynamics of carbon flux,and their relationship with environmental factors.The results showed that different vegetations varied greatly in soil organic carbon density:R 〉 S 〉 P,and the soil carbon density reduced with the increasing depth;soil CO2flux:S 〉 P 〉 R,and sample plot P and S showed unimodal changes.The peak values appeared at 14:00-15:00 p.m.;soil CO2 flux was negatively correlated with near-ground air humidity and carbon content,positively correlated with soil temperature and near-ground air temperature,and showed no obvious correlation with soil moisture.展开更多
基金supported by the National Basic Research Program of China (No. 2006CB400505) and the National NaturalSciences Foundation of China (Nos. 49971056 and 40171007)
文摘The principles of remotely estimating grassland cover density in an alpine meadow soil from space lie in the synchronous collection of in situ samples with the satellite pass and statistically linking these cover densities to their image properties according to their geographic coordinates. The principles and procedures for quantifying grassland cover density from satellite image data were presented with an example from Qinghai Lake, China demonstrating how quantification could be made more accurate through the integrated use of remote sensing and global positioning systems (GPS). An empirical model was applied to an entire satellite image to convert pixel values into ground cover density. Satellite data based on 68 field samples was used to produce a map of ten cover densities. After calibration a strong linear regression relationship (r2 = 0.745) between pixel values on the satellite image and in situ measured grassland cover density was established with an 89% accuracy level. However, to minimize positional uncertainty of field samples, integrated use of hyperspatial satellite data and GPS could be utilized. This integration could reduce disparity in ground and space sampling intervals, and improve future quantification accuracy even more.
基金funded by the National Natural Science Foundation of China (41501219)
文摘Alpine meadow ecosystem is fragile and highly sensitive to climate change.An understanding of the allocation of above-and below-ground plant biomass and correlations with environmental factors in alpine meadow ecosystem can result in better protection and effective utilization of alpine meadow vegetation.We chose an alpine meadow in the Qinghai-Tibetan Plateau of China as the study area and designed experimental warming plots using a randomized block experimental design.We used single-tube infrared radiators as warming devices,established the warming treatments,and measured plant above- (AGB) and below-ground biomass (BGB) during the growing seasons (May to September) in 2012 and 2013.We determined the allocation of biomass and the relationship between biomass and soil environment under the warming treatment.Biomass indices including above-ground biomass,below-ground biomass and the ratio of root to shoot (R/S) ,and soil factors including soil moisture and soil temperature at different depths were measured.The results showed that (1) BGB of the alpine meadow had the most significant allometric correlation with its AGB (y=298.7x~ (0.44) ,P〈0.001) ,but the relationship decreased under warming treatment and the determination coefficient of the functional equation was 0.102 which was less than that of 0.188 of the unwarming treatment (control) ; (2) BGB increased,especially in the deeper soil layers under warming treatment (P〉0.05) .At 0–10 cm soil depth,the percentages of BGB under warming treatment were smaller than those of the control treatment with the decreases being 8.52% and 8.23% in 2012 and 2013,respectively.However,the BGB increased 2.13% and 2.06% in 2012 and 2013,respectively,at 10–50 cm soil depths; (3) BGB had significant positive correlations with soil moisture at 100 cm depth and with soil temperature at 20–100 cm depths (P〈0.05) ,but the mean correlation coefficient of soil temperature was 0.354,greater than the 0.245 of soil moisture.R/S ratio had a significant negative correlation with soil temperature at 20 cm depth (P〈0.05) .The warmer soil temperatures in shallow layers increased the biomass allocation to above-ground plant parts,which leading to the increase in AGB;whereas the enhanced thawing of frozen soil in deep layers causing by warming treatment produced more moisture that affected plant biomass allocation.
基金Sponsored by Natural Science Foundation of China(31360569)Key Laboratory of Grassland Ecosystem Program(CYZS-2011007)Modern Agricultural Technical System of Gansu Agricultural University CARS-35
文摘Three alpine meadows were chosen from the eastern margin of the Qilian Mountain:Polygonum viviparum meadow(P),Stipa capillata grassland(S)and Rhododendron simsii shrub meadow(R);LI-8100 A soil CO2 flux auto-monitoring system and lab analysis were applied to analyze the soil organic carbon density,dynamics of carbon flux,and their relationship with environmental factors.The results showed that different vegetations varied greatly in soil organic carbon density:R 〉 S 〉 P,and the soil carbon density reduced with the increasing depth;soil CO2flux:S 〉 P 〉 R,and sample plot P and S showed unimodal changes.The peak values appeared at 14:00-15:00 p.m.;soil CO2 flux was negatively correlated with near-ground air humidity and carbon content,positively correlated with soil temperature and near-ground air temperature,and showed no obvious correlation with soil moisture.