the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Nitrogen limitation information retrieved from data assimilation
Song Wang
Carlos Sierra
Yiqi Luo
Jinsong Wang
Weinan Chen
Yahai Zhang
Aizhong Ye
Shuli Niu
Abstract. Nitrogen (N) limitation greatly constrains terrestrial ecosystem carbon (C) uptake and its response to climate change and elevated carbon dioxide. Hence, accurate assessments of ecosystem N limitation are crucial for predicting C-N feedbacks, and vital for providing guidance for policy making or ecosystem management as well. This study aims to retrieve N limitation information by data model fusion from one field N addition experiment so that we can better understand N controls on the terrestrial C cycle. We estimated two sets of parameters with one C-only model and one coupled C-N model. Our results showed that the estimated leaf photosynthetic efficiency (LPE) and process rates (e.g., senescence and decomposition rates) of organic C from almost all pools were higher with the coupled C-N model than those with the C-only model at the ambient treatment. However, the differences in the LPE and the C exit rates between the coupled C-N model and the C-only model decreased with the increasing N addition rates. Both the C-only and coupled C-N models simulated similar C pool sizes as observed at every N addition treatment with their respective parameter estimates. However, simulated ecosystem C storage and gross primary productivity (GPP) decreased if we ran the coupled C-N model with the parameters estimated by the C-only model. This decrease was larger at the ambient treatment and became smaller with the increase of N addition. In general, we put forward a new method to retrieve N limitation information from observations by data model fusion. This method will make it possible to estimate the global nutrient limitation and benefit ecosystem management and policy making.
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Song Wang et al.
Status: open (until 17 Apr 2023)
Song Wang et al.
Song Wang et al.
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