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Simulation of soil nitrogen storage of the typical steppe with the DNDC model: A case study in Inner Mongolia, China

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Simulation of soil nitrogen storage of the typical steppe with the DNDC model: A case study in Inner Mongolia, China. / Li, R. H.; Li, X. B.; Li, G. Q. et al.
In: Ecological Indicators, Vol. 41, 06.2014, p. 155-164.

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Li RH, Li XB, Li GQ, Wen WY. Simulation of soil nitrogen storage of the typical steppe with the DNDC model: A case study in Inner Mongolia, China. Ecological Indicators. 2014 Jun;41:155-164. Epub 2014 Mar 6. doi: 10.1016/j.ecolind.2014.01.043

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Li, R. H. ; Li, X. B. ; Li, G. Q. et al. / Simulation of soil nitrogen storage of the typical steppe with the DNDC model : A case study in Inner Mongolia, China. In: Ecological Indicators. 2014 ; Vol. 41. pp. 155-164.

Bibtex

@article{42dd0308006047c9987eaa4187f7d221,
title = "Simulation of soil nitrogen storage of the typical steppe with the DNDC model: A case study in Inner Mongolia, China",
abstract = "Soil nutrient depletion is one of the characteristics of steppe degradation. Soil nitrogen (N) storage is an indicator of ecosystem productivity, and its simulation is necessary to monitor steppe degradation and for recovery measures. The study presents a simulation framework of soil N storage by integrating a denitrification–decomposition (DNDC) ecosystem model-based simulation and multi-source remote sensing data-based inversion. The DNDC model is a key player in the framework, whereas remote sensing prepares the input parameters and verification data. To run a DNDC model spatially, climate, soil, and vegetation databases were built, and land use, slop, grazing, and mowing parameters were formulated by remote sensing inversion. A soil N storage prediction model was established with the maximum of normalized difference vegetation index (NDVI) to provide comparable results with the simulation of soil N storage with the DNDC model. The results indicate that soil N storage declined from east to west throughout the study area. From 1990 to 2011, no change in the spatial distribution of soil N storage was determined, and the spatial heterogeneity of soil N storage decreased with its increase in the low-N area and decrease in the high-N area. A significant correlation (P < 0.01) was determined between soil N storage data detected by remote sensing inversion and that simulated with DNDC, and both estimation results of soil N storage matched well. Soil N storage simulated with the DNDC model was more sensitive to soil organic carbon (SOC), bulk density, pH and N fixation index than other parameters, and using the most sensitive factor (MSF) method, the range of annual mean soil N storage was determined to be between 2339.61 and 5484.61 kg ha−1. The variation in regional soil N storage in a typical steppe in Inner Mongolia, China can therefore be simulated using the DNDC model with support from remote sensing.",
keywords = "DNDC, Remote sensing, Soil N storage, Steppe, Inner Mongolia",
author = "Li, {R. H.} and Li, {X. B.} and Li, {G. Q.} and Wen, {W. Y.}",
year = "2014",
month = jun,
doi = "10.1016/j.ecolind.2014.01.043",
language = "English",
volume = "41",
pages = "155--164",
journal = "Ecological Indicators",
issn = "1470-160X",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Simulation of soil nitrogen storage of the typical steppe with the DNDC model

T2 - A case study in Inner Mongolia, China

AU - Li, R. H.

AU - Li, X. B.

AU - Li, G. Q.

AU - Wen, W. Y.

PY - 2014/6

Y1 - 2014/6

N2 - Soil nutrient depletion is one of the characteristics of steppe degradation. Soil nitrogen (N) storage is an indicator of ecosystem productivity, and its simulation is necessary to monitor steppe degradation and for recovery measures. The study presents a simulation framework of soil N storage by integrating a denitrification–decomposition (DNDC) ecosystem model-based simulation and multi-source remote sensing data-based inversion. The DNDC model is a key player in the framework, whereas remote sensing prepares the input parameters and verification data. To run a DNDC model spatially, climate, soil, and vegetation databases were built, and land use, slop, grazing, and mowing parameters were formulated by remote sensing inversion. A soil N storage prediction model was established with the maximum of normalized difference vegetation index (NDVI) to provide comparable results with the simulation of soil N storage with the DNDC model. The results indicate that soil N storage declined from east to west throughout the study area. From 1990 to 2011, no change in the spatial distribution of soil N storage was determined, and the spatial heterogeneity of soil N storage decreased with its increase in the low-N area and decrease in the high-N area. A significant correlation (P < 0.01) was determined between soil N storage data detected by remote sensing inversion and that simulated with DNDC, and both estimation results of soil N storage matched well. Soil N storage simulated with the DNDC model was more sensitive to soil organic carbon (SOC), bulk density, pH and N fixation index than other parameters, and using the most sensitive factor (MSF) method, the range of annual mean soil N storage was determined to be between 2339.61 and 5484.61 kg ha−1. The variation in regional soil N storage in a typical steppe in Inner Mongolia, China can therefore be simulated using the DNDC model with support from remote sensing.

AB - Soil nutrient depletion is one of the characteristics of steppe degradation. Soil nitrogen (N) storage is an indicator of ecosystem productivity, and its simulation is necessary to monitor steppe degradation and for recovery measures. The study presents a simulation framework of soil N storage by integrating a denitrification–decomposition (DNDC) ecosystem model-based simulation and multi-source remote sensing data-based inversion. The DNDC model is a key player in the framework, whereas remote sensing prepares the input parameters and verification data. To run a DNDC model spatially, climate, soil, and vegetation databases were built, and land use, slop, grazing, and mowing parameters were formulated by remote sensing inversion. A soil N storage prediction model was established with the maximum of normalized difference vegetation index (NDVI) to provide comparable results with the simulation of soil N storage with the DNDC model. The results indicate that soil N storage declined from east to west throughout the study area. From 1990 to 2011, no change in the spatial distribution of soil N storage was determined, and the spatial heterogeneity of soil N storage decreased with its increase in the low-N area and decrease in the high-N area. A significant correlation (P < 0.01) was determined between soil N storage data detected by remote sensing inversion and that simulated with DNDC, and both estimation results of soil N storage matched well. Soil N storage simulated with the DNDC model was more sensitive to soil organic carbon (SOC), bulk density, pH and N fixation index than other parameters, and using the most sensitive factor (MSF) method, the range of annual mean soil N storage was determined to be between 2339.61 and 5484.61 kg ha−1. The variation in regional soil N storage in a typical steppe in Inner Mongolia, China can therefore be simulated using the DNDC model with support from remote sensing.

KW - DNDC

KW - Remote sensing

KW - Soil N storage

KW - Steppe

KW - Inner Mongolia

U2 - 10.1016/j.ecolind.2014.01.043

DO - 10.1016/j.ecolind.2014.01.043

M3 - Journal article

VL - 41

SP - 155

EP - 164

JO - Ecological Indicators

JF - Ecological Indicators

SN - 1470-160X

ER -