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- W4382888615 abstract "<strong class=journal-contentHeaderColor>Abstract.</strong> 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." @default.
- W4382888615 created "2023-07-03" @default.
- W4382888615 creator A5077717369 @default.
- W4382888615 date "2023-05-12" @default.
- W4382888615 modified "2023-10-17" @default.
- W4382888615 title "Reply on RC2" @default.
- W4382888615 doi "https://doi.org/10.5194/bg-2023-33-ac2" @default.
- W4382888615 hasPublicationYear "2023" @default.
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