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Biblioteca (s) : |
INIA Tacuarembó. |
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Fecha : |
23/09/2016 |
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Actualizado : |
23/09/2016 |
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Tipo de producción científica : |
Abstracts/Resúmenes |
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Autor : |
BASILE, P.; FORMOSO, D.; TISCORNIA, G.; BLUMETTO, O. |
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Afiliación : |
PATRICIA CECILIA BASILE LORENZO, Universidad de la República (UdelaR)/ Centro Universitario Regional Tacuarembó; DANIEL FORMOSO CUNHA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GUADALUPE TISCORNIA TOSAR, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; OSCAR RICARDO BLUMETTO VELAZCO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Radiation use efficiency on campos graslands with contrasting grzing methods. [Resumen de poster]. |
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Fecha de publicación : |
2016 |
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Fuente / Imprenta : |
ln: Encuentro de Investigadores de la Región Noreste: Cerro Largo-Rivera-Tacuarembó, 1., 12 de agosto de 2016, Campus Interinstitucional de Tacuarembó, Tacuarembó. Libro de Resúmenes. Tacuarembó: UDELAR; INIA, 2016. |
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Páginas : |
p. 64 |
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Idioma : |
Inglés |
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Contenido : |
Introduction: In Uruguay, the Basaltic region has de highest proportion of natural grasslands of the country. In this pastures, livestock management is the main reason of degradation of natural grasslands. Today, it's possible to estimate ANPP (Aboveground Net Primary Production) using remote sensing techniques. The RUE (Radiation Use Efficiency) is the effectiveness with which fPAR (fraction of Photosyntethically Active Radiation absorbed by plants) is transformed in ANPP and is known to vary according to temperature, precipitation and species composition. Objectives; The aims of this work were: a) to calibrate RUE and b) study the temporal variability
of RUE for two contrasting grazing methods. Materials & Methods: The study was conducted on five livestock farms located in the Basaltic region. In each site, two contrasting pastures with different historical grazing management (controlled vs continuous stocking rate) were selected. Data was collected between september 2013 and february 2015. RUE coefficient was estimated following Monteith equation: RUE= ANPP / APAR and APAR= fPAR x PAR. ANPP was estimated using the technique of regrowth in three exclusion cages. Biomass was cut at 1cm in boxes 20 x 50cm with shears every 45-50 days and was dried in forced air oven at 60 ° C. fPAR
was obtained as a function of ENVI images from MODIS sensor (US Geological Survey) and PAR was estimated from agro-climatic stations of INIA. RUE data were analyzed with a oneway ANOVA and the means were compared with T test for paired samples. Results: Between grazing methods, RUE average values were statistically different (p <0.05), with controlled management reporting values above 44%. When analysing seasonal variation between grazing methods, there were no statistical differences in RUE values. Seasonal variation of RUE for each grazing methods separately, was significantly different within seasons (p <0.05). Conclusions: The RUE values obtained could be used in the estimation of a more accurately ANPP in natural grasslands of this region. MenosIntroduction: In Uruguay, the Basaltic region has de highest proportion of natural grasslands of the country. In this pastures, livestock management is the main reason of degradation of natural grasslands. Today, it's possible to estimate ANPP (Aboveground Net Primary Production) using remote sensing techniques. The RUE (Radiation Use Efficiency) is the effectiveness with which fPAR (fraction of Photosyntethically Active Radiation absorbed by plants) is transformed in ANPP and is known to vary according to temperature, precipitation and species composition. Objectives; The aims of this work were: a) to calibrate RUE and b) study the temporal variability
of RUE for two contrasting grazing methods. Materials & Methods: The study was conducted on five livestock farms located in the Basaltic region. In each site, two contrasting pastures with different historical grazing management (controlled vs continuous stocking rate) were selected. Data was collected between september 2013 and february 2015. RUE coefficient was estimated following Monteith equation: RUE= ANPP / APAR and APAR= fPAR x PAR. ANPP was estimated using the technique of regrowth in three exclusion cages. Biomass was cut at 1cm in boxes 20 x 50cm with shears every 45-50 days and was dried in forced air oven at 60 ° C. fPAR
was obtained as a function of ENVI images from MODIS sensor (US Geological Survey) and PAR was estimated from agro-climatic stations of INIA. RUE data were analyzed with a oneway ANOVA and the mea... Presentar Todo |
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Palabras claves : |
GRASSLAND PRODUCTIVITY; LIVESTOCK MANAGEMENT; PPNA. |
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Thesagro : |
PASTURAS. |
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Asunto categoría : |
P30 Ciencia del suelo y manejo del suelo |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/6099/1/PAGINA-64.pdf
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Marc : |
LEADER 02852naa a2200217 a 4500
001 1055722
005 2016-09-23
008 2016 bl uuuu u00u1 u #d
100 1 $aBASILE, P.
245 $aRadiation use efficiency on campos graslands with contrasting grzing methods. [Resumen de poster].$h[electronic resource]
260 $c2016
300 $ap. 64
520 $aIntroduction: In Uruguay, the Basaltic region has de highest proportion of natural grasslands of the country. In this pastures, livestock management is the main reason of degradation of natural grasslands. Today, it's possible to estimate ANPP (Aboveground Net Primary Production) using remote sensing techniques. The RUE (Radiation Use Efficiency) is the effectiveness with which fPAR (fraction of Photosyntethically Active Radiation absorbed by plants) is transformed in ANPP and is known to vary according to temperature, precipitation and species composition. Objectives; The aims of this work were: a) to calibrate RUE and b) study the temporal variability of RUE for two contrasting grazing methods. Materials & Methods: The study was conducted on five livestock farms located in the Basaltic region. In each site, two contrasting pastures with different historical grazing management (controlled vs continuous stocking rate) were selected. Data was collected between september 2013 and february 2015. RUE coefficient was estimated following Monteith equation: RUE= ANPP / APAR and APAR= fPAR x PAR. ANPP was estimated using the technique of regrowth in three exclusion cages. Biomass was cut at 1cm in boxes 20 x 50cm with shears every 45-50 days and was dried in forced air oven at 60 ° C. fPAR was obtained as a function of ENVI images from MODIS sensor (US Geological Survey) and PAR was estimated from agro-climatic stations of INIA. RUE data were analyzed with a oneway ANOVA and the means were compared with T test for paired samples. Results: Between grazing methods, RUE average values were statistically different (p <0.05), with controlled management reporting values above 44%. When analysing seasonal variation between grazing methods, there were no statistical differences in RUE values. Seasonal variation of RUE for each grazing methods separately, was significantly different within seasons (p <0.05). Conclusions: The RUE values obtained could be used in the estimation of a more accurately ANPP in natural grasslands of this region.
650 $aPASTURAS
653 $aGRASSLAND PRODUCTIVITY
653 $aLIVESTOCK MANAGEMENT
653 $aPPNA
700 1 $aFORMOSO, D.
700 1 $aTISCORNIA, G.
700 1 $aBLUMETTO, O.
773 $tln: Encuentro de Investigadores de la Región Noreste: Cerro Largo-Rivera-Tacuarembó, 1., 12 de agosto de 2016, Campus Interinstitucional de Tacuarembó, Tacuarembó. Libro de Resúmenes. Tacuarembó: UDELAR; INIA, 2016.
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Registro original : |
INIA Tacuarembó (TBO) |
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 | Acceso al texto completo restringido a Biblioteca INIA Treinta y Tres. Por información adicional contacte bibliott@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha actual : |
18/02/2019 |
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Actualizado : |
20/02/2020 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
-- - -- |
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Autor : |
BLUMETTO, O.; CASTAGNA, A.; CARDOZO, G.; GARCIA, F.; TISCORNIA, G.; RUGGIA, A.; SCARLATO, S.; ALBICETTE, M.M.; AGUERRE, V.; ALBÍN, A. |
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Afiliación : |
OSCAR RICARDO BLUMETTO VELAZCO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ANDRES CASTAGNA DU PRE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GERONIMO AGUSTIN CARDOZO CABANELAS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FELIPE LUIS GARCIA OLASO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GUADALUPE TISCORNIA TOSAR, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ANDREA PAOLA RUGGIA CHIESA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SANTIAGO SCARLATO GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARIA MARTA ALBICETTE BASTRERI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARIA VERONICA AGUERRE ANTIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ALFREDO SANTIAGO ALBÍN FERREIRA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Ecosystem integrity index, an innovative environmental evaluation tool for agricultural production systems. |
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Fecha de publicación : |
2019 |
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Fuente / Imprenta : |
Ecological indicators, 2019, v. 101, p. 725-733. |
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DOI : |
10.1016/j.ecolind.2019.01.077 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 4 July 2018; Received in revised form 9 January 2019; Accepted 29 January 2019. |
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Contenido : |
ABSTRACT: Environmental assessment of agricultural production systems is an increasing concern within the international community. When evaluation involves biodiversity indicators, as richness or diversity in certain taxa or their roles in ecosystems, the participation of specialists is required to identify, classify and interpret diversity at the level of species, communities and ecosystems. Due to costs and time demand, this can be an important obstacle when a widespread use of these assessments is needed to contribute to policy making and evaluation, field
management decision-making or implementation of a specific technology. We developed a new index that combines different environmental characteristics which can be evaluated qualitatively and quantitatively with a basic training, can be implemented quickly and each index component is directly associated with key aspects for the assessment of ecosystem capacity to sustain wildlife and ecosystem services. The Ecosystem Integrity Index (EII) evaluates the status of a specific ecosystem under agricultural use, referred to an optimal condition that must be established for the ecoregion. Its application involves a qualitative and quantitative visual evaluation considering four components: vegetation structure, plant species, soil and riparian areas. Each component is valued on a 0?5 scale, where 5 is the best possible condition. EII is a simple and robust tool for evaluating and monitoring integrity of groecosystems and the primary validation demonstrates good correlation with other environmental variables such as wildlife diversity and soil organic carbon. MenosABSTRACT: Environmental assessment of agricultural production systems is an increasing concern within the international community. When evaluation involves biodiversity indicators, as richness or diversity in certain taxa or their roles in ecosystems, the participation of specialists is required to identify, classify and interpret diversity at the level of species, communities and ecosystems. Due to costs and time demand, this can be an important obstacle when a widespread use of these assessments is needed to contribute to policy making and evaluation, field
management decision-making or implementation of a specific technology. We developed a new index that combines different environmental characteristics which can be evaluated qualitatively and quantitatively with a basic training, can be implemented quickly and each index component is directly associated with key aspects for the assessment of ecosystem capacity to sustain wildlife and ecosystem services. The Ecosystem Integrity Index (EII) evaluates the status of a specific ecosystem under agricultural use, referred to an optimal condition that must be established for the ecoregion. Its application involves a qualitative and quantitative visual evaluation considering four components: vegetation structure, plant species, soil and riparian areas. Each component is valued on a 0?5 scale, where 5 is the best possible condition. EII is a simple and robust tool for evaluating and monitoring integrity of groecosystems and the pr... Presentar Todo |
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Palabras claves : |
BIODIVERSITY; ECOSYSTEM SERVICES; GRAZING MANAGEMENT; RIPARIAN ECOSYSTEM; SUSTAINABILITY; VEGETATION STRUCTURE. |
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Thesagro : |
BIODIVERSIDAD; ECOSISTEMAS; MANEJO DE PASTOREO; SUSTENTABILIDAD. |
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Asunto categoría : |
F40 Ecología vegetal |
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Marc : |
LEADER 02790naa a2200373 a 4500
001 1059498
005 2020-02-20
008 2019 bl uuuu u00u1 u #d
024 7 $a10.1016/j.ecolind.2019.01.077$2DOI
100 1 $aBLUMETTO, O.
245 $aEcosystem integrity index, an innovative environmental evaluation tool for agricultural production systems.$h[electronic resource]
260 $c2019
500 $aArticle history: Received 4 July 2018; Received in revised form 9 January 2019; Accepted 29 January 2019.
520 $aABSTRACT: Environmental assessment of agricultural production systems is an increasing concern within the international community. When evaluation involves biodiversity indicators, as richness or diversity in certain taxa or their roles in ecosystems, the participation of specialists is required to identify, classify and interpret diversity at the level of species, communities and ecosystems. Due to costs and time demand, this can be an important obstacle when a widespread use of these assessments is needed to contribute to policy making and evaluation, field management decision-making or implementation of a specific technology. We developed a new index that combines different environmental characteristics which can be evaluated qualitatively and quantitatively with a basic training, can be implemented quickly and each index component is directly associated with key aspects for the assessment of ecosystem capacity to sustain wildlife and ecosystem services. The Ecosystem Integrity Index (EII) evaluates the status of a specific ecosystem under agricultural use, referred to an optimal condition that must be established for the ecoregion. Its application involves a qualitative and quantitative visual evaluation considering four components: vegetation structure, plant species, soil and riparian areas. Each component is valued on a 0?5 scale, where 5 is the best possible condition. EII is a simple and robust tool for evaluating and monitoring integrity of groecosystems and the primary validation demonstrates good correlation with other environmental variables such as wildlife diversity and soil organic carbon.
650 $aBIODIVERSIDAD
650 $aECOSISTEMAS
650 $aMANEJO DE PASTOREO
650 $aSUSTENTABILIDAD
653 $aBIODIVERSITY
653 $aECOSYSTEM SERVICES
653 $aGRAZING MANAGEMENT
653 $aRIPARIAN ECOSYSTEM
653 $aSUSTAINABILITY
653 $aVEGETATION STRUCTURE
700 1 $aCASTAGNA, A.
700 1 $aCARDOZO, G.
700 1 $aGARCIA, F.
700 1 $aTISCORNIA, G.
700 1 $aRUGGIA, A.
700 1 $aSCARLATO, S.
700 1 $aALBICETTE, M.M.
700 1 $aAGUERRE, V.
700 1 $aALBÍN, A.
773 $tEcological indicators, 2019$gv. 101, p. 725-733.
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