Nitrogen cycling has profound effects on carbon uptake in the terrestrial ecosystem and the response of the biosphere to climate changes.However,nutrient cycling is not taken into account in most land surface models f...Nitrogen cycling has profound effects on carbon uptake in the terrestrial ecosystem and the response of the biosphere to climate changes.However,nutrient cycling is not taken into account in most land surface models for climate change.In this study,a nitrogen model,based on nitrogen transformation processes and nitrogen fluxes exchange between the atmosphere and terrestrial ecosystem,was incorporated into the Atmosphere–Vegetation Interaction Model(AVIM)to simulate the carbon cycle under nitrogen limitation.This new model,AVIM-CN,was evaluated against site-scale eddy covariance–based measurements of an alpine meadow located at Damxung station from the FLUXNET 2015 dataset.Results showed that the annual mean gross primary production simulated by AVIM-CN(0.7073 gC m^-2 d^-1)was in better agreement with the corresponding flux data(0.5407 gC m^-2 d^-1)than the original AVIM(1.1403 gC m^-2 d^-1)at Damxung station.Similarly,ecosystem respiration was also down-regulated,from 1.7695 gC m^-2 d^-1 to 1.0572 gC m^-2 d^-1,after the nitrogen processes were introduced,and the latter was closer to the observed vales(0.8034 gC m^-2 d^-1).Overall,the new results were more consistent with the daily time series of carbon and energy fluxes of observations compared to the former version without nitrogen dynamics.A model that does not incorporate the limitation effects of nitrogen nutrient availability will probably overestimate carbon fluxes by about 40%.展开更多
Aims Prediction of changes in ecosystem gross primary productivity(GPP)in response to climatic variability is a core mission in the field of global change ecology.However,it remains a big challenge for the model commu...Aims Prediction of changes in ecosystem gross primary productivity(GPP)in response to climatic variability is a core mission in the field of global change ecology.However,it remains a big challenge for the model community to reproduce the interannual variation(IAV)of GPP in arid ecosystems.Accurate estimates of soil water content(SWC)and GPP sensitivity to SWC are the two most critical aspects for predicting the IAV of GPP in arid ecosystems.Methods We took a widely used model Biome-BGC as an example,to improve the model performances in a temperate grassland ecosystem.Firstly,we updated the estimation of SWC by modifying modules of evapotrainspiration,SWC vertical profile and field capacity.Secondly,we modified the function of controlling water-nitrogen relation,which regulates the GPP-SWC sensitivity.Important Findings The original Biome-BGC overestimated the SWC and underestimated the IAV of GPP sensitivity,resulting in lower IAV of GPP than the observations,e.g.it largely underestimated the reduction of GPP in drought years.In comparison,the modified model accurately reproduced the observed seasonal and IAVs in SWC,especially in the surface layer.Simulated GPP-SWC sensitivity was also enhanced and became closer to the observations by optimizing parameter controlling nitrogen mineralization.Consequently,the model's capability of reproducing IAV of GPP has been largely improved by the modifications.Our results demonstrate that SWC in the surface layer and the consequent effects on nitrogen availability should be among the first considerations for accurate modeling IAV of GPP in arid ecosystems.展开更多
基金supported by a project of the National Key Research and Development Program of China [grant number2016YFA0602501]a project of the National Natural Science Foundation of China [grant numbers 41630532 and41575093]
文摘Nitrogen cycling has profound effects on carbon uptake in the terrestrial ecosystem and the response of the biosphere to climate changes.However,nutrient cycling is not taken into account in most land surface models for climate change.In this study,a nitrogen model,based on nitrogen transformation processes and nitrogen fluxes exchange between the atmosphere and terrestrial ecosystem,was incorporated into the Atmosphere–Vegetation Interaction Model(AVIM)to simulate the carbon cycle under nitrogen limitation.This new model,AVIM-CN,was evaluated against site-scale eddy covariance–based measurements of an alpine meadow located at Damxung station from the FLUXNET 2015 dataset.Results showed that the annual mean gross primary production simulated by AVIM-CN(0.7073 gC m^-2 d^-1)was in better agreement with the corresponding flux data(0.5407 gC m^-2 d^-1)than the original AVIM(1.1403 gC m^-2 d^-1)at Damxung station.Similarly,ecosystem respiration was also down-regulated,from 1.7695 gC m^-2 d^-1 to 1.0572 gC m^-2 d^-1,after the nitrogen processes were introduced,and the latter was closer to the observed vales(0.8034 gC m^-2 d^-1).Overall,the new results were more consistent with the daily time series of carbon and energy fluxes of observations compared to the former version without nitrogen dynamics.A model that does not incorporate the limitation effects of nitrogen nutrient availability will probably overestimate carbon fluxes by about 40%.
基金supported by the National Natural Science Foundation of China(31922053)the National Key Research and Development Program of China(2017YFA0604801).
文摘Aims Prediction of changes in ecosystem gross primary productivity(GPP)in response to climatic variability is a core mission in the field of global change ecology.However,it remains a big challenge for the model community to reproduce the interannual variation(IAV)of GPP in arid ecosystems.Accurate estimates of soil water content(SWC)and GPP sensitivity to SWC are the two most critical aspects for predicting the IAV of GPP in arid ecosystems.Methods We took a widely used model Biome-BGC as an example,to improve the model performances in a temperate grassland ecosystem.Firstly,we updated the estimation of SWC by modifying modules of evapotrainspiration,SWC vertical profile and field capacity.Secondly,we modified the function of controlling water-nitrogen relation,which regulates the GPP-SWC sensitivity.Important Findings The original Biome-BGC overestimated the SWC and underestimated the IAV of GPP sensitivity,resulting in lower IAV of GPP than the observations,e.g.it largely underestimated the reduction of GPP in drought years.In comparison,the modified model accurately reproduced the observed seasonal and IAVs in SWC,especially in the surface layer.Simulated GPP-SWC sensitivity was also enhanced and became closer to the observations by optimizing parameter controlling nitrogen mineralization.Consequently,the model's capability of reproducing IAV of GPP has been largely improved by the modifications.Our results demonstrate that SWC in the surface layer and the consequent effects on nitrogen availability should be among the first considerations for accurate modeling IAV of GPP in arid ecosystems.