Globally a large number of process-based models have been assessed for quantification of agricultural greenhouse gas (GHG) emissions. Modelling approaches minimize the presence of spatial variability of biogeochemical...Globally a large number of process-based models have been assessed for quantification of agricultural greenhouse gas (GHG) emissions. Modelling approaches minimize the presence of spatial variability of biogeochemical processes, leading to improved estimates of GHGs as well as identifying mitigation and policy options. The comparative performance of the three dynamic models (e.g., DNDC v9.4, DailyDayCent and ECOSSE v5+) with minimum numbers of common input parameters was evaluated against measured variables. Simulations were performed on conventionally-tilled spring barley crops receiving N fertilizer at 135 - 159 kg·N·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup> and crop residues at 3 t·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup>. For surface soil nitrate (0 - 10 cm), the ECOSSE and DNDC simulated values showed significant correlations with measured values (R<sup>2</sup> = 0.31 - 0.55, p 0.05). Only the ECOSSE-simulated N<sub>2</sub>O fluxes showed a significant relationship (R<sup>2</sup> = 0.33, p 0.05) with values measured from fertilized fields, but not with unfertilized ones. The DNDC and DailyDayCent models significantly underestimated seasonal/annual N<sub>2</sub>O fluxes compared to ECOSSE, with emission factors (EFs), based on an 8-year average, were 0.09%, 0.31% and 0.52%, respectively. Predictions of ecosystem respiration by both DailyDayCent and DNDC showed reasonable agreement with Eddy Covariance data (R<sup>2</sup> = 0.34 - 0.41, p 0.05). Compared to the measured value (3624 kg·C·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup>), the ECOSSE underestimated annual heterotrophic respiration by 7% but this was smaller than the DNDC (50%) and DailyDayCent (24%) estimates. All models simulated CH<sub>4</sub> uptake we展开更多
Soil acidity is an important parameter that can regulate ecosystem structure and function.However,a quantitative understanding of the relationships between soil pH and environmental factors remains unavailable.In this...Soil acidity is an important parameter that can regulate ecosystem structure and function.However,a quantitative understanding of the relationships between soil pH and environmental factors remains unavailable.In this study,relationships of soil pH with both climatic and edaphic factors in alpine grasslands on the Tibetan Plateau,China were quantified using data obtained from a regional soil survey during 2001-2004.Our results showed that soil pH decreased along the gradient of both mean annual temperature and precipitation.Likewise,soil pH exhibited consistent negative correlations with soil moisture and silt content.However,soil organic and inorganic carbon contents played opposite roles in shaping patterns of soil pH:the accumulation of soil organic matter led to higher soil acidity,while the existence of soil inorganic matter was favorable for maintaining higher soil alkalinity.The variation partitioning analysis indicated that the combination of climatic and edaphic variables explained 74.3%of the variation in soil acidity.These results suggest that soil pH could be predicted from routinely-measured variables,allowing a robust pedotransfer function to be developed.The pedotransfer function may facilitate land surface models to generate more reliable predictions on ecosystem structure and function around the world.展开更多
文摘Globally a large number of process-based models have been assessed for quantification of agricultural greenhouse gas (GHG) emissions. Modelling approaches minimize the presence of spatial variability of biogeochemical processes, leading to improved estimates of GHGs as well as identifying mitigation and policy options. The comparative performance of the three dynamic models (e.g., DNDC v9.4, DailyDayCent and ECOSSE v5+) with minimum numbers of common input parameters was evaluated against measured variables. Simulations were performed on conventionally-tilled spring barley crops receiving N fertilizer at 135 - 159 kg·N·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup> and crop residues at 3 t·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup>. For surface soil nitrate (0 - 10 cm), the ECOSSE and DNDC simulated values showed significant correlations with measured values (R<sup>2</sup> = 0.31 - 0.55, p 0.05). Only the ECOSSE-simulated N<sub>2</sub>O fluxes showed a significant relationship (R<sup>2</sup> = 0.33, p 0.05) with values measured from fertilized fields, but not with unfertilized ones. The DNDC and DailyDayCent models significantly underestimated seasonal/annual N<sub>2</sub>O fluxes compared to ECOSSE, with emission factors (EFs), based on an 8-year average, were 0.09%, 0.31% and 0.52%, respectively. Predictions of ecosystem respiration by both DailyDayCent and DNDC showed reasonable agreement with Eddy Covariance data (R<sup>2</sup> = 0.34 - 0.41, p 0.05). Compared to the measured value (3624 kg·C·ha<sup>-</sup><sup>1</sup>·yr<sup>-</sup><sup>1</sup>), the ECOSSE underestimated annual heterotrophic respiration by 7% but this was smaller than the DNDC (50%) and DailyDayCent (24%) estimates. All models simulated CH<sub>4</sub> uptake we
基金Supported by the National Natural Science Foundation of China(Nos.31170410 and 31322011)
文摘Soil acidity is an important parameter that can regulate ecosystem structure and function.However,a quantitative understanding of the relationships between soil pH and environmental factors remains unavailable.In this study,relationships of soil pH with both climatic and edaphic factors in alpine grasslands on the Tibetan Plateau,China were quantified using data obtained from a regional soil survey during 2001-2004.Our results showed that soil pH decreased along the gradient of both mean annual temperature and precipitation.Likewise,soil pH exhibited consistent negative correlations with soil moisture and silt content.However,soil organic and inorganic carbon contents played opposite roles in shaping patterns of soil pH:the accumulation of soil organic matter led to higher soil acidity,while the existence of soil inorganic matter was favorable for maintaining higher soil alkalinity.The variation partitioning analysis indicated that the combination of climatic and edaphic variables explained 74.3%of the variation in soil acidity.These results suggest that soil pH could be predicted from routinely-measured variables,allowing a robust pedotransfer function to be developed.The pedotransfer function may facilitate land surface models to generate more reliable predictions on ecosystem structure and function around the world.
