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| 1. |  | BELANCHE, A.; HRISTOV, A.; VAN LINGEN, H.; DENMAN, S. E.; KEBREAB, E.; SCHWARM, A.; KREUZER, M.; NIU, M.; EUGÈNE, M.; NIDERKORN, V.; MARTIN, C.; ARCHIMÈDE, H.; MCGEE, M.; REYNOLDS, C. K.; CROMPTON, L. A.; BAYAT, A. R.; YU, Z.; BANNINK, A.; DIJKSTRA, J.; CHAVES, A. V.; CLARK, H.; MUETZEL, S.; LIND, V.; MOORBY, J. M.; ROOKE, J. A.; AUBRY, A.; ANTEZANA, W.; WANG, M.; HEGARTY, R.; HUTTON O. V.; HILL, J.; VERCOE, P. E.; SAVIAN, J.V.; ABDALLA, A. L.; SOLTAN, Y. A.; GOMES MONTEIRO, A. L.; KU-VERA, J. C.; JAURENA, G.; GÓMEZ-BRAVO, C. A.; MAYORGA, O. L.; CONGIO, G. F. S.; YÁÑEZ-RUIZ, D. R. Prediction of enteric methane emissions by sheep using an intercontinental database. Journal of Cleaner Production, 15 January 2023, Volume 384, 135523. OPEN ACCESS. doi: https://doi.org/10.1016/j.jclepro.2022.135523 Article history: Received 24 May 2022; Received in revised form 11 November 2022; Accepted 3 December 2022; Available online 9 December 2022.
Corresponding author: Belanche, A.; Department of Animal Production and Food Sciences, IA2,...| Biblioteca(s): INIA Las Brujas; INIA Treinta y Tres. |
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 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
20/08/2021 |
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Actualizado : |
20/08/2021 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
IRISARRI, J.G.N.; TEXEIRA, M.; OESTERHELD, M.; VERÓN, S.R.; DELLA NAVE, F.; PARUELO, J. |
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Afiliación : |
J. GONZALO N. IRISARRI, Cátedra de Forrajicultura, Departamento de Producción Animal, Facultad de Agronomía, LART IFEVA, Universidad, de Buenos Aires, CONICET, Buenos Aires, Argentina.; MARCOS TEXEIRA, Departamento de Métodos Cuantitativos y Sistemas de Información, Facultad de Agronomía, LART IFEVA, Universidad, de Buenos Aires, CONICET, Buenos Aires, Argentina.; MARTÍN OESTERHELD, Cátedra de Ecología, Facultad de Agronomía, LART IFEVA, Universidad, de Buenos Aires, CONICET, Buenos Aires, Argentina.; SANTIAGO R. VERÓN, Instituto de Clima y Agua, Instituto Nacional de Tecnología Agropecuaria (INTA), Departamento de Métodos Cuantitativos y Sistemas de. Información, Facultad de Agronomía, Universidad, de Buenos Aires, CONICET, Buenos Aires, Argentina.; FACUNDO DELLA NAVE, Cátedra de Ecología, Facultad de Agronomía, LART IFEVA, Universidad, de Buenos Aires, CONICET, Buenos Aires, Argentina.; JOSÉ PARUELO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Dpto. Métodos Cuantitativos y Sistemas de Información, Fac. Agronomía, LART IFEVA, Univ. Bs.As., CONICET, Bs.As. Argentina; Fac. Ciencias, IECA, Univ. de la República, Montevideo, Uruguay. |
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Título : |
Discriminating the biophysical signal from human-induced effects on long-term primary production dynamics. The case of Patagonia. |
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Fecha de publicación : |
2021 |
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Fuente / Imprenta : |
Global Change Biology, 2021, volume 27, Issue 18, Pages 4381 - 4391. Doi: https://doi.org/10.1111/gcb.15733 |
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ISSN : |
1354-1013 |
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DOI : |
10.1111/gcb.15733 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 20 January 2021, Accepted 13 May 2021, To be published September 2021.
Supplementary material.
Corresponging author: Irisarri, J.G.N.; Cátedra de Forrajicultura, Departamento de Producción Animal, Facultad de Agronomía, LART IFEVA, Universidad, de Buenos Aires, CONICET, Buenos Aires, Argentina; email:irisarri@agro.uba.ar |
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Contenido : |
ABSTRACT - The temporal trend of aboveground net primary production (ANPP) is frequently used to estimate the effect of humans on ecosystems. In water-limited ecosystems, like most grazing areas in the world, the effect of humans act upon ANPP in combination with environmental variations. Our main objective was to quantify long-term (1981?2012) changes of ANPP and discriminate the causes of these changes between environmental and human at a subcontinental scale, across vast areas of Patagonia. We estimated ANPP through a radiative model based on remote sensing data. Then, we evaluated the relation between ANPP and environmental interannual variations of two hierarchically related factors: El Niño Southern Oscillation (ENSO) through the Southern Oscillation Index (SOI), and precipitation. We described the effect of humans through the shape of the temporal trends of the residuals (RESTREND) of the environmental model and quantified human relative impact through the RESTREND: ANPP trend ratio. ANPP interannual variation was significantly explained by ENSO (through SOI) and precipitation in 65% of the study area. The SOI had a positive association with annual precipitation. The association between ANPP and annual precipitation was positive. RESTREND analysis was statistically significant in 92% of the area where the tested environmental model worked, representing 60% of the study area, and it was mostly negative. However, its magnitude, revealed through the RESTREND: ANPP trend ratio, was relatively mild. Our analysis revealed that most of ANPP trends were associated with climate and that even when human density is low, its incidence seems to be mainly negative. © 2021 John Wiley & Sons Ltd. MenosABSTRACT - The temporal trend of aboveground net primary production (ANPP) is frequently used to estimate the effect of humans on ecosystems. In water-limited ecosystems, like most grazing areas in the world, the effect of humans act upon ANPP in combination with environmental variations. Our main objective was to quantify long-term (1981?2012) changes of ANPP and discriminate the causes of these changes between environmental and human at a subcontinental scale, across vast areas of Patagonia. We estimated ANPP through a radiative model based on remote sensing data. Then, we evaluated the relation between ANPP and environmental interannual variations of two hierarchically related factors: El Niño Southern Oscillation (ENSO) through the Southern Oscillation Index (SOI), and precipitation. We described the effect of humans through the shape of the temporal trends of the residuals (RESTREND) of the environmental model and quantified human relative impact through the RESTREND: ANPP trend ratio. ANPP interannual variation was significantly explained by ENSO (through SOI) and precipitation in 65% of the study area. The SOI had a positive association with annual precipitation. The association between ANPP and annual precipitation was positive. RESTREND analysis was statistically significant in 92% of the area where the tested environmental model worked, representing 60% of the study area, and it was mostly negative. However, its magnitude, revealed through the RESTREND: ANPP trend ... Presentar Todo |
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Palabras claves : |
Ecosystems; ENSO; Environmental variations; GIMMS; NDVI; RESTREND; SOI. |
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Asunto categoría : |
F01 Cultivo |
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Marc : |
LEADER 02961naa a2200301 a 4500
001 1062363
005 2021-08-20
008 2021 bl uuuu u00u1 u #d
022 $a1354-1013
024 7 $a10.1111/gcb.15733$2DOI
100 1 $aIRISARRI, J.G.N.
245 $aDiscriminating the biophysical signal from human-induced effects on long-term primary production dynamics. The case of Patagonia.$h[electronic resource]
260 $c2021
500 $aArticle history: Received 20 January 2021, Accepted 13 May 2021, To be published September 2021. Supplementary material. Corresponging author: Irisarri, J.G.N.; Cátedra de Forrajicultura, Departamento de Producción Animal, Facultad de Agronomía, LART IFEVA, Universidad, de Buenos Aires, CONICET, Buenos Aires, Argentina; email:irisarri@agro.uba.ar
520 $aABSTRACT - The temporal trend of aboveground net primary production (ANPP) is frequently used to estimate the effect of humans on ecosystems. In water-limited ecosystems, like most grazing areas in the world, the effect of humans act upon ANPP in combination with environmental variations. Our main objective was to quantify long-term (1981?2012) changes of ANPP and discriminate the causes of these changes between environmental and human at a subcontinental scale, across vast areas of Patagonia. We estimated ANPP through a radiative model based on remote sensing data. Then, we evaluated the relation between ANPP and environmental interannual variations of two hierarchically related factors: El Niño Southern Oscillation (ENSO) through the Southern Oscillation Index (SOI), and precipitation. We described the effect of humans through the shape of the temporal trends of the residuals (RESTREND) of the environmental model and quantified human relative impact through the RESTREND: ANPP trend ratio. ANPP interannual variation was significantly explained by ENSO (through SOI) and precipitation in 65% of the study area. The SOI had a positive association with annual precipitation. The association between ANPP and annual precipitation was positive. RESTREND analysis was statistically significant in 92% of the area where the tested environmental model worked, representing 60% of the study area, and it was mostly negative. However, its magnitude, revealed through the RESTREND: ANPP trend ratio, was relatively mild. Our analysis revealed that most of ANPP trends were associated with climate and that even when human density is low, its incidence seems to be mainly negative. © 2021 John Wiley & Sons Ltd.
653 $aEcosystems
653 $aENSO
653 $aEnvironmental variations
653 $aGIMMS
653 $aNDVI
653 $aRESTREND
653 $aSOI
700 1 $aTEXEIRA, M.
700 1 $aOESTERHELD, M.
700 1 $aVERÓN, S.R.
700 1 $aDELLA NAVE, F.
700 1 $aPARUELO, J.
773 $tGlobal Change Biology, 2021, volume 27, Issue 18, Pages 4381 - 4391. Doi: https://doi.org/10.1111/gcb.15733
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