Improving the quantification of terrestrial ecosystem carbon dynamics over the United States using an adjoint method

2013

Biogeosciences

Abstract. Boreal forest and tundra are the major ecosystems in the northern high latitudes in which a large amount of carbon is stored. These ecosystems are nitrogen-limited due to slow mineralization rate of the soil organic nitrogen. Recently, abundant field studies have found that organic nitrogen is another important nitrogen supply for boreal forest and tundra ecosystems. In this study, we incorporated a mechanism that allowed boreal plants to uptake small molecular amino acids into a process-based biogeochemical model, the Terrestrial Ecosystem Model (TEM), to evaluate the impact of organic nitrogen uptake on ecosystem carbon cycling. The new version of the model was evaluated for both boreal forest and tundra sites. We found that the modeled organic nitrogen uptake accounted for 36-87 % of total nitrogen uptake by plants in tundra ecosystems and 26-50 % for boreal forests, suggesting that tundra ecosystem might have more relied on the organic form of nitrogen than boreal forests. The simulated monthly gross ecosystem production (GPP) and net ecosystem production (NEP) tended to be larger with the new version of the model since the plant uptake of organic nitrogen alleviated the soil nitrogen limitation especially during the growing season. The sensitivity study indicated that the most important factors controlling the plant uptake of organic nitrogen was the soil amino acid diffusion coefficient (D e ) in our model, suggesting that the organic nitrogen uptake by plants is likely to be regulated by the edaphic characteristics of diffusion. The model uncertainty due to uncertain parameters associated with organic nitrogen uptake of the tundra ecosystem was larger than the boreal forest ecosystems. This study suggests that considering the organic nitrogen uptake by plants is important to carbon modeling of boreal forest and tundra ecosystems.

Section: Adjoint-tem Parameterization Methodsmentioning

confidence: 99%

Section: Overviewmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Parameterizationmentioning

confidence: 99%

See 2 more Smart Citations

Modeling the effects of organic nitrogen uptake by plants on the carbon cycling of boreal forest and tundra ecosystems

Zhu

2013

Biogeosciences

“…Our next steps include integrating the improved LAI modeling into GPP and ET quantification with TEM. In previous studies of carbon dynamics with TEM (e.g., Zhu and Zhuang 2013), LAI was not used for modeling GPP. With our spatial-explicitly calibrated LAI, we now could improve GPP simulations, thus net primary production (NPP) and net ecosystem production defined as the difference of NPP and heterotrophic respiration.…”

Section: Future Applications Of Lai Modelingmentioning

confidence: 99%

Modeling leaf area index in North America using a process‐based terrestrial ecosystem model

2018

Ecosphere

Self Cite

Abstract. Leaf area index (LAI) is often used to quantify plant production and evapotranspiration with terrestrial ecosystem models (TEMs). This study evaluated the LAI simulation in North America using a data assimilation technique and a process-based TEM as well as in situ and satellite data. We first optimized the parameters related to LAI in the TEM using a Markov Chain Monte Carlo method, and AmeriFlux site-level and regional LAI data from advanced very high-resolution radiometer. The parameterized model was then verified with the observed monthly LAI of major ecosystem types at site level. ). Both the spring and fall LAI in the 2000s are higher than that in the 1980s in the region, suggesting that the leaf phenology has an earlier onset and later senescence in the 2000s. The average LAI increased in April and September by 0.03 and 0.24 m 2 /m 2 , respectively. This study provides a way to quantify LAI with ecosystem models, which will improve future carbon and water cycling studies.

Parameterization and sensitivity analysis of a process‐based terrestrial ecosystem model using adjoint method

Zhu

2014

J Adv Model Earth Syst

Self Cite

We developed an adjoint version of a process-based biogeochemistry model, the Terrestrial Ecosystem Model (TEM). The adjoint model of TEM was then used to: (1) conduct sensitivity studies of net ecosystem production (NEP) for three terrestrial ecosystems: grassland, deciduous broadleaf forest and evergreen needle-leaf forest; (2) rank the importance of parameters in controlling NEP; (3) optimize the model parameters by assimilating eddy flux data of NEP; and (4) evaluate parameterization by extrapolating optimal parameters to other sites that have the same plant functional type as the calibration sites. We found that: (1) the maximum rate of photosynthesis (C MAX ) was the most important parameter in determining NEP, while the importance of the remaining parameters varied depending on plant functional type, suggesting that the same ecosystem process has different degrees of importance in modeling carbon fluxes; (2) the sensitivity of NEP to C MAX had a significant seasonal variability and the control of C MAX on NEP was much larger in growing season (defined as from April to October) than that in nongrowing season (defined as from December to March); and (3) after parameterization, TEM could reasonably reproduce carbon fluxes observed at eddy flux tower sites. This study provided an effective model-data fusion framework of TEM, which could improve the future quantification of terrestrial ecosystem carbon fluxes at both site and regional levels.