Soil organic carbon within the vadose zone of a floodplain
Abstract Past studies have focused on carbon variation in the upper 1 m of the soil profile. However, there is limited information on carbon variation at deeper depths (e.g., 0–4 m) and mathematical functions to extrapolate carbon content at these depths. The objective of this study was therefore to...
Ausführliche Beschreibung
Autor*in: |
Li, X. [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2018 |
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Schlagwörter: |
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Anmerkung: |
© Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
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Übergeordnetes Werk: |
Enthalten in: Environmental earth sciences - Berlin : Springer, 2009, 77(2018), 6 vom: 22. März |
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Übergeordnetes Werk: |
volume:77 ; year:2018 ; number:6 ; day:22 ; month:03 |
Links: |
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DOI / URN: |
10.1007/s12665-018-7424-4 |
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Katalog-ID: |
SPR026748789 |
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520 | |a Abstract Past studies have focused on carbon variation in the upper 1 m of the soil profile. However, there is limited information on carbon variation at deeper depths (e.g., 0–4 m) and mathematical functions to extrapolate carbon content at these depths. The objective of this study was therefore to assess the vertical variation in SOC (reached 4 m) of the Tarim River floodplain in northwestern China. The vertical distribution in SOC was described by exponential and power functions based on (1) soil depth, (2) soil depth and silt content, (3) soil depth and SOC at the shallowest and deepest depths, (4) soil depth, silt content, and SOC at the shallowest and deepest depths, and (5) soil depth and SOC at the shallowest depth. We found SOC content decreased with depth from 6.82 g $ kg^{−1} $ at 0–0.2 m to < 1.0 g $ kg^{−1} $ below 3.2–3.4 m averaged across five locations along the floodplain. Both the power and exponential functions provided a good fit to the measured data in the upper 1 m of the soil profile, whereas the power function provided a better fit to the data when extrapolating to a depth of 3–4 m. The power function describing SOC as a function of soil depth, silt content, and SOC at the shallowest and deepest depths best portrayed the distribution in SOC with depth. Considering the cost and labor in measuring soil properties, our results suggest that SOC at the shallowest depth can provide good estimates of the vertical distribution in SOC in a floodplain. | ||
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700 | 1 | |a Sharratt, B. |4 aut | |
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10.1007/s12665-018-7424-4 doi (DE-627)SPR026748789 (SPR)s12665-018-7424-4-e DE-627 ger DE-627 rakwb eng Li, X. verfasserin aut Soil organic carbon within the vadose zone of a floodplain 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Past studies have focused on carbon variation in the upper 1 m of the soil profile. However, there is limited information on carbon variation at deeper depths (e.g., 0–4 m) and mathematical functions to extrapolate carbon content at these depths. The objective of this study was therefore to assess the vertical variation in SOC (reached 4 m) of the Tarim River floodplain in northwestern China. The vertical distribution in SOC was described by exponential and power functions based on (1) soil depth, (2) soil depth and silt content, (3) soil depth and SOC at the shallowest and deepest depths, (4) soil depth, silt content, and SOC at the shallowest and deepest depths, and (5) soil depth and SOC at the shallowest depth. We found SOC content decreased with depth from 6.82 g $ kg^{−1} $ at 0–0.2 m to < 1.0 g $ kg^{−1} $ below 3.2–3.4 m averaged across five locations along the floodplain. Both the power and exponential functions provided a good fit to the measured data in the upper 1 m of the soil profile, whereas the power function provided a better fit to the data when extrapolating to a depth of 3–4 m. The power function describing SOC as a function of soil depth, silt content, and SOC at the shallowest and deepest depths best portrayed the distribution in SOC with depth. Considering the cost and labor in measuring soil properties, our results suggest that SOC at the shallowest depth can provide good estimates of the vertical distribution in SOC in a floodplain. Soil profile (dpeaa)DE-He213 Soil texture (dpeaa)DE-He213 Tarim River (dpeaa)DE-He213 Feng, G. aut Sharratt, B. aut Enthalten in Environmental earth sciences Berlin : Springer, 2009 77(2018), 6 vom: 22. März (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:77 year:2018 number:6 day:22 month:03 https://dx.doi.org/10.1007/s12665-018-7424-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 77 2018 6 22 03 |
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10.1007/s12665-018-7424-4 doi (DE-627)SPR026748789 (SPR)s12665-018-7424-4-e DE-627 ger DE-627 rakwb eng Li, X. verfasserin aut Soil organic carbon within the vadose zone of a floodplain 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Past studies have focused on carbon variation in the upper 1 m of the soil profile. However, there is limited information on carbon variation at deeper depths (e.g., 0–4 m) and mathematical functions to extrapolate carbon content at these depths. The objective of this study was therefore to assess the vertical variation in SOC (reached 4 m) of the Tarim River floodplain in northwestern China. The vertical distribution in SOC was described by exponential and power functions based on (1) soil depth, (2) soil depth and silt content, (3) soil depth and SOC at the shallowest and deepest depths, (4) soil depth, silt content, and SOC at the shallowest and deepest depths, and (5) soil depth and SOC at the shallowest depth. We found SOC content decreased with depth from 6.82 g $ kg^{−1} $ at 0–0.2 m to < 1.0 g $ kg^{−1} $ below 3.2–3.4 m averaged across five locations along the floodplain. Both the power and exponential functions provided a good fit to the measured data in the upper 1 m of the soil profile, whereas the power function provided a better fit to the data when extrapolating to a depth of 3–4 m. The power function describing SOC as a function of soil depth, silt content, and SOC at the shallowest and deepest depths best portrayed the distribution in SOC with depth. Considering the cost and labor in measuring soil properties, our results suggest that SOC at the shallowest depth can provide good estimates of the vertical distribution in SOC in a floodplain. Soil profile (dpeaa)DE-He213 Soil texture (dpeaa)DE-He213 Tarim River (dpeaa)DE-He213 Feng, G. aut Sharratt, B. aut Enthalten in Environmental earth sciences Berlin : Springer, 2009 77(2018), 6 vom: 22. März (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:77 year:2018 number:6 day:22 month:03 https://dx.doi.org/10.1007/s12665-018-7424-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 77 2018 6 22 03 |
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10.1007/s12665-018-7424-4 doi (DE-627)SPR026748789 (SPR)s12665-018-7424-4-e DE-627 ger DE-627 rakwb eng Li, X. verfasserin aut Soil organic carbon within the vadose zone of a floodplain 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Past studies have focused on carbon variation in the upper 1 m of the soil profile. However, there is limited information on carbon variation at deeper depths (e.g., 0–4 m) and mathematical functions to extrapolate carbon content at these depths. The objective of this study was therefore to assess the vertical variation in SOC (reached 4 m) of the Tarim River floodplain in northwestern China. The vertical distribution in SOC was described by exponential and power functions based on (1) soil depth, (2) soil depth and silt content, (3) soil depth and SOC at the shallowest and deepest depths, (4) soil depth, silt content, and SOC at the shallowest and deepest depths, and (5) soil depth and SOC at the shallowest depth. We found SOC content decreased with depth from 6.82 g $ kg^{−1} $ at 0–0.2 m to < 1.0 g $ kg^{−1} $ below 3.2–3.4 m averaged across five locations along the floodplain. Both the power and exponential functions provided a good fit to the measured data in the upper 1 m of the soil profile, whereas the power function provided a better fit to the data when extrapolating to a depth of 3–4 m. The power function describing SOC as a function of soil depth, silt content, and SOC at the shallowest and deepest depths best portrayed the distribution in SOC with depth. Considering the cost and labor in measuring soil properties, our results suggest that SOC at the shallowest depth can provide good estimates of the vertical distribution in SOC in a floodplain. Soil profile (dpeaa)DE-He213 Soil texture (dpeaa)DE-He213 Tarim River (dpeaa)DE-He213 Feng, G. aut Sharratt, B. aut Enthalten in Environmental earth sciences Berlin : Springer, 2009 77(2018), 6 vom: 22. März (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:77 year:2018 number:6 day:22 month:03 https://dx.doi.org/10.1007/s12665-018-7424-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 77 2018 6 22 03 |
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10.1007/s12665-018-7424-4 doi (DE-627)SPR026748789 (SPR)s12665-018-7424-4-e DE-627 ger DE-627 rakwb eng Li, X. verfasserin aut Soil organic carbon within the vadose zone of a floodplain 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Past studies have focused on carbon variation in the upper 1 m of the soil profile. However, there is limited information on carbon variation at deeper depths (e.g., 0–4 m) and mathematical functions to extrapolate carbon content at these depths. The objective of this study was therefore to assess the vertical variation in SOC (reached 4 m) of the Tarim River floodplain in northwestern China. The vertical distribution in SOC was described by exponential and power functions based on (1) soil depth, (2) soil depth and silt content, (3) soil depth and SOC at the shallowest and deepest depths, (4) soil depth, silt content, and SOC at the shallowest and deepest depths, and (5) soil depth and SOC at the shallowest depth. We found SOC content decreased with depth from 6.82 g $ kg^{−1} $ at 0–0.2 m to < 1.0 g $ kg^{−1} $ below 3.2–3.4 m averaged across five locations along the floodplain. Both the power and exponential functions provided a good fit to the measured data in the upper 1 m of the soil profile, whereas the power function provided a better fit to the data when extrapolating to a depth of 3–4 m. The power function describing SOC as a function of soil depth, silt content, and SOC at the shallowest and deepest depths best portrayed the distribution in SOC with depth. Considering the cost and labor in measuring soil properties, our results suggest that SOC at the shallowest depth can provide good estimates of the vertical distribution in SOC in a floodplain. Soil profile (dpeaa)DE-He213 Soil texture (dpeaa)DE-He213 Tarim River (dpeaa)DE-He213 Feng, G. aut Sharratt, B. aut Enthalten in Environmental earth sciences Berlin : Springer, 2009 77(2018), 6 vom: 22. März (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:77 year:2018 number:6 day:22 month:03 https://dx.doi.org/10.1007/s12665-018-7424-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 77 2018 6 22 03 |
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10.1007/s12665-018-7424-4 doi (DE-627)SPR026748789 (SPR)s12665-018-7424-4-e DE-627 ger DE-627 rakwb eng Li, X. verfasserin aut Soil organic carbon within the vadose zone of a floodplain 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Past studies have focused on carbon variation in the upper 1 m of the soil profile. However, there is limited information on carbon variation at deeper depths (e.g., 0–4 m) and mathematical functions to extrapolate carbon content at these depths. The objective of this study was therefore to assess the vertical variation in SOC (reached 4 m) of the Tarim River floodplain in northwestern China. The vertical distribution in SOC was described by exponential and power functions based on (1) soil depth, (2) soil depth and silt content, (3) soil depth and SOC at the shallowest and deepest depths, (4) soil depth, silt content, and SOC at the shallowest and deepest depths, and (5) soil depth and SOC at the shallowest depth. We found SOC content decreased with depth from 6.82 g $ kg^{−1} $ at 0–0.2 m to < 1.0 g $ kg^{−1} $ below 3.2–3.4 m averaged across five locations along the floodplain. Both the power and exponential functions provided a good fit to the measured data in the upper 1 m of the soil profile, whereas the power function provided a better fit to the data when extrapolating to a depth of 3–4 m. The power function describing SOC as a function of soil depth, silt content, and SOC at the shallowest and deepest depths best portrayed the distribution in SOC with depth. Considering the cost and labor in measuring soil properties, our results suggest that SOC at the shallowest depth can provide good estimates of the vertical distribution in SOC in a floodplain. Soil profile (dpeaa)DE-He213 Soil texture (dpeaa)DE-He213 Tarim River (dpeaa)DE-He213 Feng, G. aut Sharratt, B. aut Enthalten in Environmental earth sciences Berlin : Springer, 2009 77(2018), 6 vom: 22. März (DE-627)599673451 (DE-600)2493699-6 1866-6299 nnns volume:77 year:2018 number:6 day:22 month:03 https://dx.doi.org/10.1007/s12665-018-7424-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2360 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 77 2018 6 22 03 |
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However, there is limited information on carbon variation at deeper depths (e.g., 0–4 m) and mathematical functions to extrapolate carbon content at these depths. The objective of this study was therefore to assess the vertical variation in SOC (reached 4 m) of the Tarim River floodplain in northwestern China. The vertical distribution in SOC was described by exponential and power functions based on (1) soil depth, (2) soil depth and silt content, (3) soil depth and SOC at the shallowest and deepest depths, (4) soil depth, silt content, and SOC at the shallowest and deepest depths, and (5) soil depth and SOC at the shallowest depth. We found SOC content decreased with depth from 6.82 g $ kg^{−1} $ at 0–0.2 m to < 1.0 g $ kg^{−1} $ below 3.2–3.4 m averaged across five locations along the floodplain. Both the power and exponential functions provided a good fit to the measured data in the upper 1 m of the soil profile, whereas the power function provided a better fit to the data when extrapolating to a depth of 3–4 m. The power function describing SOC as a function of soil depth, silt content, and SOC at the shallowest and deepest depths best portrayed the distribution in SOC with depth. 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Soil organic carbon within the vadose zone of a floodplain Soil profile (dpeaa)DE-He213 Soil texture (dpeaa)DE-He213 Tarim River (dpeaa)DE-He213 |
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Soil organic carbon within the vadose zone of a floodplain |
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soil organic carbon within the vadose zone of a floodplain |
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Soil organic carbon within the vadose zone of a floodplain |
abstract |
Abstract Past studies have focused on carbon variation in the upper 1 m of the soil profile. However, there is limited information on carbon variation at deeper depths (e.g., 0–4 m) and mathematical functions to extrapolate carbon content at these depths. The objective of this study was therefore to assess the vertical variation in SOC (reached 4 m) of the Tarim River floodplain in northwestern China. The vertical distribution in SOC was described by exponential and power functions based on (1) soil depth, (2) soil depth and silt content, (3) soil depth and SOC at the shallowest and deepest depths, (4) soil depth, silt content, and SOC at the shallowest and deepest depths, and (5) soil depth and SOC at the shallowest depth. We found SOC content decreased with depth from 6.82 g $ kg^{−1} $ at 0–0.2 m to < 1.0 g $ kg^{−1} $ below 3.2–3.4 m averaged across five locations along the floodplain. Both the power and exponential functions provided a good fit to the measured data in the upper 1 m of the soil profile, whereas the power function provided a better fit to the data when extrapolating to a depth of 3–4 m. The power function describing SOC as a function of soil depth, silt content, and SOC at the shallowest and deepest depths best portrayed the distribution in SOC with depth. Considering the cost and labor in measuring soil properties, our results suggest that SOC at the shallowest depth can provide good estimates of the vertical distribution in SOC in a floodplain. © Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
abstractGer |
Abstract Past studies have focused on carbon variation in the upper 1 m of the soil profile. However, there is limited information on carbon variation at deeper depths (e.g., 0–4 m) and mathematical functions to extrapolate carbon content at these depths. The objective of this study was therefore to assess the vertical variation in SOC (reached 4 m) of the Tarim River floodplain in northwestern China. The vertical distribution in SOC was described by exponential and power functions based on (1) soil depth, (2) soil depth and silt content, (3) soil depth and SOC at the shallowest and deepest depths, (4) soil depth, silt content, and SOC at the shallowest and deepest depths, and (5) soil depth and SOC at the shallowest depth. We found SOC content decreased with depth from 6.82 g $ kg^{−1} $ at 0–0.2 m to < 1.0 g $ kg^{−1} $ below 3.2–3.4 m averaged across five locations along the floodplain. Both the power and exponential functions provided a good fit to the measured data in the upper 1 m of the soil profile, whereas the power function provided a better fit to the data when extrapolating to a depth of 3–4 m. The power function describing SOC as a function of soil depth, silt content, and SOC at the shallowest and deepest depths best portrayed the distribution in SOC with depth. Considering the cost and labor in measuring soil properties, our results suggest that SOC at the shallowest depth can provide good estimates of the vertical distribution in SOC in a floodplain. © Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
abstract_unstemmed |
Abstract Past studies have focused on carbon variation in the upper 1 m of the soil profile. However, there is limited information on carbon variation at deeper depths (e.g., 0–4 m) and mathematical functions to extrapolate carbon content at these depths. The objective of this study was therefore to assess the vertical variation in SOC (reached 4 m) of the Tarim River floodplain in northwestern China. The vertical distribution in SOC was described by exponential and power functions based on (1) soil depth, (2) soil depth and silt content, (3) soil depth and SOC at the shallowest and deepest depths, (4) soil depth, silt content, and SOC at the shallowest and deepest depths, and (5) soil depth and SOC at the shallowest depth. We found SOC content decreased with depth from 6.82 g $ kg^{−1} $ at 0–0.2 m to < 1.0 g $ kg^{−1} $ below 3.2–3.4 m averaged across five locations along the floodplain. Both the power and exponential functions provided a good fit to the measured data in the upper 1 m of the soil profile, whereas the power function provided a better fit to the data when extrapolating to a depth of 3–4 m. The power function describing SOC as a function of soil depth, silt content, and SOC at the shallowest and deepest depths best portrayed the distribution in SOC with depth. Considering the cost and labor in measuring soil properties, our results suggest that SOC at the shallowest depth can provide good estimates of the vertical distribution in SOC in a floodplain. © Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
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title_short |
Soil organic carbon within the vadose zone of a floodplain |
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https://dx.doi.org/10.1007/s12665-018-7424-4 |
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Feng, G. Sharratt, B. |
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2024-07-03T22:33:31.093Z |
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|
score |
7.397687 |