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Biblioteca (s) : |
INIA Treinta y Tres. |
Fecha : |
21/02/2014 |
Actualizado : |
28/06/2021 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Autor : |
TERRA, J.A.; SHAW, N.J.; REEVES, D.W.; RAPER, R.L.; VAN SANTEN, E.; MASK, P.L. |
Afiliación : |
JOSÉ ALFREDO TERRA FERNÁNDEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Soil Carbon relationships with terrain attributes, electrical conductivity, and a soil survey in a coastal plain landscape. |
Fecha de publicación : |
2004 |
Fuente / Imprenta : |
Soil Science, 2004, V. 169, No. 12, p. 819-831. |
DOI : |
10.1097/00010694-200412000-00001 |
Idioma : |
Inglés |
Notas : |
Article history: Received May 3, 2004 // Accepted Sept. 30, 2004, Publishing Dec. 2004. |
Contenido : |
Soil organic carbon (SOC) estimation at the landscape level is critical for assessing impacts of management practices on C sequestration and soil quality. We determined relationships between SOC, terrain attributes, field scale soil electrical conductivity (EC), soil texture and soil survey map units in a 9 ha coastal plain field (Aquic and Typic Paleudults) historically managed by conventional means. The site was composite sampled for SOC (0-30 cm) within 18.3 × 8.5-m grids (n = 496), and two data sets were created from the original data. Ordinary kriging, co-kriging, regression kriging and multiple regression were used to develop SOC surfaces that were validated with an independent data set (n = 24) using the mean square error (MSE). The SOC was relatively low (26.13 Mg ha?1) and only moderately variable (CV = 21%), and showed high spatial dependence. Interpolation techniques produced similar SOC maps but the best predictor was ordinary kriging (MSE = 9.11 Mg2 ha?2) while regression was the worst (MSE = 20.65 Mg2 ha?2). Factor analysis indicated that the first three factors explained 57% of field variability; compound topographic index (CTI), slope, EC and soil textural fractions dominated these components. Elevation, slope, CTI, silt content and EC explained up to 50% of the SOC variability (P ? 0.01) suggesting that topography and historical erosion played a significant role in SOC distribution. Field subdivision into soil map units or k-mean clusters similarly decreased SOC variance (about 30%). The study suggests that terrain attributes and EC surveys can be used to differentiate zones of variable SOC content, which may be used as bench marks to evaluate field-level impact of management practices on C sequestration. MenosSoil organic carbon (SOC) estimation at the landscape level is critical for assessing impacts of management practices on C sequestration and soil quality. We determined relationships between SOC, terrain attributes, field scale soil electrical conductivity (EC), soil texture and soil survey map units in a 9 ha coastal plain field (Aquic and Typic Paleudults) historically managed by conventional means. The site was composite sampled for SOC (0-30 cm) within 18.3 × 8.5-m grids (n = 496), and two data sets were created from the original data. Ordinary kriging, co-kriging, regression kriging and multiple regression were used to develop SOC surfaces that were validated with an independent data set (n = 24) using the mean square error (MSE). The SOC was relatively low (26.13 Mg ha?1) and only moderately variable (CV = 21%), and showed high spatial dependence. Interpolation techniques produced similar SOC maps but the best predictor was ordinary kriging (MSE = 9.11 Mg2 ha?2) while regression was the worst (MSE = 20.65 Mg2 ha?2). Factor analysis indicated that the first three factors explained 57% of field variability; compound topographic index (CTI), slope, EC and soil textural fractions dominated these components. Elevation, slope, CTI, silt content and EC explained up to 50% of the SOC variability (P ? 0.01) suggesting that topography and historical erosion played a significant role in SOC distribution. Field subdivision into soil map units or k-mean clusters similarly decreased... Presentar Todo |
Thesagro : |
MANEJO DEL SUELO; SUELO. |
Asunto categoría : |
-- |
Marc : |
LEADER 02522naa a2200229 a 4500 001 1032966 005 2021-06-28 008 2004 bl uuuu u00u1 u #d 024 7 $a10.1097/00010694-200412000-00001$2DOI 100 1 $aTERRA, J.A. 245 $aSoil Carbon relationships with terrain attributes, electrical conductivity, and a soil survey in a coastal plain landscape.$h[electronic resource] 260 $c2004 500 $aArticle history: Received May 3, 2004 // Accepted Sept. 30, 2004, Publishing Dec. 2004. 520 $aSoil organic carbon (SOC) estimation at the landscape level is critical for assessing impacts of management practices on C sequestration and soil quality. We determined relationships between SOC, terrain attributes, field scale soil electrical conductivity (EC), soil texture and soil survey map units in a 9 ha coastal plain field (Aquic and Typic Paleudults) historically managed by conventional means. The site was composite sampled for SOC (0-30 cm) within 18.3 × 8.5-m grids (n = 496), and two data sets were created from the original data. Ordinary kriging, co-kriging, regression kriging and multiple regression were used to develop SOC surfaces that were validated with an independent data set (n = 24) using the mean square error (MSE). The SOC was relatively low (26.13 Mg ha?1) and only moderately variable (CV = 21%), and showed high spatial dependence. Interpolation techniques produced similar SOC maps but the best predictor was ordinary kriging (MSE = 9.11 Mg2 ha?2) while regression was the worst (MSE = 20.65 Mg2 ha?2). Factor analysis indicated that the first three factors explained 57% of field variability; compound topographic index (CTI), slope, EC and soil textural fractions dominated these components. Elevation, slope, CTI, silt content and EC explained up to 50% of the SOC variability (P ? 0.01) suggesting that topography and historical erosion played a significant role in SOC distribution. Field subdivision into soil map units or k-mean clusters similarly decreased SOC variance (about 30%). The study suggests that terrain attributes and EC surveys can be used to differentiate zones of variable SOC content, which may be used as bench marks to evaluate field-level impact of management practices on C sequestration. 650 $aMANEJO DEL SUELO 650 $aSUELO 700 1 $aSHAW, N.J. 700 1 $aREEVES, D.W. 700 1 $aRAPER, R.L. 700 1 $aVAN SANTEN, E. 700 1 $aMASK, P.L. 773 $tSoil Science, 2004, V. 169, No. 12, p. 819-831.
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
18/06/2015 |
Actualizado : |
20/06/2015 |
Tipo de producción científica : |
Informes Agroclimáticos |
Autor : |
CASTAÑO, J.; GIMENEZ, A.; FUREST, J.; AUNCHAYNA, R. |
Afiliación : |
JOSE PEDRO CASTAÑO SANCHEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; AGUSTIN EDUARDO GIMENEZ FUREST, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JOSE MARIA FUREST CROCCO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ROSSINA MARIANA AUNCHAYNA REILLY, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Informe Agroclimático 2009 - Situación a Agosto. |
Fecha de publicación : |
2009 |
Fuente / Imprenta : |
Montevideo (Uruguay): INIA, 2009. |
Páginas : |
74 p. |
Idioma : |
Español |
Palabras claves : |
AGROCLIMA; AGROCLIMATOLOGÍA; BOLETIN AGROCLIMÁTICO; CARACTERIZACIÓN AGROCLIMÁTICA; DIRECCION VIENTO; ESTACIONES AGROMETEOROLOGICAS; ESTACIONES AUTOMATICAS; ESTACIONES INIA; ESTADO DEL TIEMPO; ESTRÉS HÍDRICO; GRAFICAS AGROCLIMATICOS; GRAS; HELIOFANOGRAFO; INFORMACION SATELITAL; INUNDACIONES; LLUVIAS DIARIAS; MAXIMA; MEDIA; MINIMA; PANEL SOLAR; PERSPECTIVAS CLIMATICAS; PLUVIOMETRO; PRECIPITACION NACIONAL; PREVENCION HELADAS; PRONOSTICO; SENSOR; SIMETRICO; TANQUE A; TERMOCUPLAS; TERMOHIDROGRAFO; VARIABLES AGROCLIMATICAS; VELETA. |
Thesagro : |
AGROCLIMATOLOGIA; CAMBIO CLIMATICO; CLIMA; CLIMATOLOGIA; ESTACIONES METEOROLOGICAS; ESTRES HIDRICO; EVAPORACION; EVAPOTRANSPIRACION; HUMEDAD; HUMEDAD RELATIVA; LLUVIA; METEOROLOGIA; PERSPECTIVAS; PLUVIOMETROS; PRONOSTICO DEL TIEMPO; SENSORES; SISTEMAS; SISTEMAS DE INFORMACION; SUELO; TEMPERATURA; TERMOMETROS. |
Asunto categoría : |
P40 Meteorología y climatología |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/4666/1/Inf.Agr.-agosto-2009.pdf
http://www.inia.uy/Publicaciones/Paginas/publicacion-1962.aspx
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Marc : |
LEADER 02041nam a2200781 a 4500 001 1052822 005 2015-06-20 008 2009 bl uuuu u0uu1 u #d 100 1 $aCASTAÑO, J. 245 $aInforme Agroclimático 2009 - Situación a Agosto.$h[electronic resource] 260 $aMontevideo (Uruguay): INIA$c2009 300 $a74 p. 650 $aAGROCLIMATOLOGIA 650 $aCAMBIO CLIMATICO 650 $aCLIMA 650 $aCLIMATOLOGIA 650 $aESTACIONES METEOROLOGICAS 650 $aESTRES HIDRICO 650 $aEVAPORACION 650 $aEVAPOTRANSPIRACION 650 $aHUMEDAD 650 $aHUMEDAD RELATIVA 650 $aLLUVIA 650 $aMETEOROLOGIA 650 $aPERSPECTIVAS 650 $aPLUVIOMETROS 650 $aPRONOSTICO DEL TIEMPO 650 $aSENSORES 650 $aSISTEMAS 650 $aSISTEMAS DE INFORMACION 650 $aSUELO 650 $aTEMPERATURA 650 $aTERMOMETROS 653 $aAGROCLIMA 653 $aAGROCLIMATOLOGÍA 653 $aBOLETIN AGROCLIMÁTICO 653 $aCARACTERIZACIÓN AGROCLIMÁTICA 653 $aDIRECCION VIENTO 653 $aESTACIONES AGROMETEOROLOGICAS 653 $aESTACIONES AUTOMATICAS 653 $aESTACIONES INIA 653 $aESTADO DEL TIEMPO 653 $aESTRÉS HÍDRICO 653 $aGRAFICAS AGROCLIMATICOS 653 $aGRAS 653 $aHELIOFANOGRAFO 653 $aINFORMACION SATELITAL 653 $aINUNDACIONES 653 $aLLUVIAS DIARIAS 653 $aMAXIMA 653 $aMEDIA 653 $aMINIMA 653 $aPANEL SOLAR 653 $aPERSPECTIVAS CLIMATICAS 653 $aPLUVIOMETRO 653 $aPRECIPITACION NACIONAL 653 $aPREVENCION HELADAS 653 $aPRONOSTICO 653 $aSENSOR 653 $aSIMETRICO 653 $aTANQUE A 653 $aTERMOCUPLAS 653 $aTERMOHIDROGRAFO 653 $aVARIABLES AGROCLIMATICAS 653 $aVELETA 700 1 $aGIMENEZ, A. 700 1 $aFUREST, J. 700 1 $aAUNCHAYNA, R.
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