| |
|
|
 | Acceso al texto completo restringido a Biblioteca INIA La Estanzuela. Por información adicional contacte bib_le@inia.org.uy. |
|
Registro completo
|
|
Biblioteca (s) : |
INIA La Estanzuela. |
|
Fecha : |
21/09/2020 |
|
Actualizado : |
21/09/2020 |
|
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
|
Autor : |
HAACKER, E.M.K.; SHARDA, V.; CANO, A.M.; HROZENCIK, R.A.; NÚÑEZ, A.; ZAMBRESKI, Z; NOZARI, S.; SMITH, G.E.B.; MOORE, L.; SHARMA, S.; GOWDA, P.; RAY, CH; SCHIPANSKI, M.; WASKOM , R. |
|
Afiliación : |
ERIN M.K. HAACKER, Nebraska Water Center, University of Nebraska, Lincoln, Nebraska, USA.; VAISHALI SHARDA, Nebraska Water Center, University of Nebraska, Lincoln, Nebraska, USA.; AMANDA M. CANO, Department of Plant and Soil Sciences, Texas Tech University, Lubbock, Texas, USA.; R. AARON HROZENCIK, Department of Agricultural and Resource Economics, Colorado State University, Fort Collins, Colorado, USA.; AGUSTIN NUÑEZ RUSSI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ZACHARY ZAMBRESKI, Department of Agronomy, Kansas State University, Manhattan, Kansas, USA.; SOHEIL NOZARI, Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, Colorado, USA.; GARVEY ENGULU B. SMITH, Department of Soil and Crop Sciences, Colorado State University, Fort Collins, Colorado, USA; LACEY MOORE, Department of Agricultural and Resource Economics, Colorado State University, Fort Collins, Colorado, USA.; SUMIT SHARMA, Department of Plant and Soil Sciences, Oklahoma State University, Stillwater, Oklahoma, USA.; PRASANNA GOWDA, Grazinglands Research Laboratory, USDA Agricultural Research Service, El Reno, Oklahoma, USA.; CHITTARANJAN RAY, Nebraska Water Center, University of Nebraska, Lincoln, Nebraska, USA.; MEAGAN SCHIPANSKI, Department of Soil and Crop Sciences, Colorado State University, Fort Collins, Colorado, USA.; REAGAN WASKOM, Colorado Water Institute and Water Center, Colorado State University, Fort Collins, Colorado, USA. |
|
Título : |
Transitio pathways to sustainable agricultural water management: A review of integrated modeling approaches (Review). |
|
Fecha de publicación : |
2020 |
|
Fuente / Imprenta : |
Journal of the American Water Resources Association (JAWRA) , February 2019, Volume 55, Issue 1, Pages 6-23. DOI: https://doi.org/10.1111/1752-1688.12722 |
|
DOI : |
10.1111/1752-1688.12722 |
|
Idioma : |
Inglés |
|
Notas : |
Article history: Received August 1, 2018 /Accepted December 5, 2018.
Citation: Haacker, E.M.K., V. Sharda, A.M. Cano, R.A. Hrozencik, A. Nunez, Z. Zambreski, S. Nozari, G.E.B. Smith, L. Moore, S. Sharma, ~
P. Gowda, C. Ray, M. Schipanski, and R. Waskom. 2019. ?Transition Pathways to Sustainable Agricultural Water Management: A Review of
Integrated Modeling Approaches.? Journal of the American Water Resources Association 1?18. https://doi.org/10.1111/1752-1688.12722. |
|
Contenido : |
Each of these disciplines has developed numerous process?based and empirical models for AWM. However, models that simulate all major hydrologic, water quality, and crop growth processes in agricultural systems are still lacking. As computers become more powerful, more researchers are choosing to integrate existing models to account for these major processes rather than building new cross?disciplinary models. Model integration carries the hope that, as in a real system, the sum of the model will be greater than the parts. However, models based upon simplified and unrealistic assumptions of physical or empirical processes can generate misleading results which are not useful for informing policy. In this article, we use literature and case studies from the High Plains Aquifer and Southeastern United States regions to elucidate the challenges and opportunities associated with integrated modeling for AWM and recommend conditions in which to use integrated models. Additionally, we examine the potential contributions of integrated modeling to AWM ? the actual practice of conserving water while maximizing productivity. Editor's note: This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series. |
|
Palabras claves : |
AGUA SUBTERRÁNEA; DECISION SUPPORT SYSTEMS; GESTION SOSTENIBLE DEL AGUA AGRICOLA; GROUNDWATER; IRRIGATION; SOIL HEALTH; WATER CONSERVATION; WATER SCARCITY ECONOMICS. |
|
Thesagro : |
CONSERVACION DE AGUAS; IRRIGACION. |
|
Asunto categoría : |
-- |
|
Marc : |
LEADER 03098naa a2200421 a 4500
001 1061330
005 2020-09-21
008 2020 bl uuuu u00u1 u #d
024 7 $a10.1111/1752-1688.12722$2DOI
100 1 $aHAACKER, E.M.K.
245 $aTransitio pathways to sustainable agricultural water management$bA review of integrated modeling approaches (Review).$h[electronic resource]
260 $c2020
500 $aArticle history: Received August 1, 2018 /Accepted December 5, 2018. Citation: Haacker, E.M.K., V. Sharda, A.M. Cano, R.A. Hrozencik, A. Nunez, Z. Zambreski, S. Nozari, G.E.B. Smith, L. Moore, S. Sharma, ~ P. Gowda, C. Ray, M. Schipanski, and R. Waskom. 2019. ?Transition Pathways to Sustainable Agricultural Water Management: A Review of Integrated Modeling Approaches.? Journal of the American Water Resources Association 1?18. https://doi.org/10.1111/1752-1688.12722.
520 $aEach of these disciplines has developed numerous process?based and empirical models for AWM. However, models that simulate all major hydrologic, water quality, and crop growth processes in agricultural systems are still lacking. As computers become more powerful, more researchers are choosing to integrate existing models to account for these major processes rather than building new cross?disciplinary models. Model integration carries the hope that, as in a real system, the sum of the model will be greater than the parts. However, models based upon simplified and unrealistic assumptions of physical or empirical processes can generate misleading results which are not useful for informing policy. In this article, we use literature and case studies from the High Plains Aquifer and Southeastern United States regions to elucidate the challenges and opportunities associated with integrated modeling for AWM and recommend conditions in which to use integrated models. Additionally, we examine the potential contributions of integrated modeling to AWM ? the actual practice of conserving water while maximizing productivity. Editor's note: This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.
650 $aCONSERVACION DE AGUAS
650 $aIRRIGACION
653 $aAGUA SUBTERRÁNEA
653 $aDECISION SUPPORT SYSTEMS
653 $aGESTION SOSTENIBLE DEL AGUA AGRICOLA
653 $aGROUNDWATER
653 $aIRRIGATION
653 $aSOIL HEALTH
653 $aWATER CONSERVATION
653 $aWATER SCARCITY ECONOMICS
700 1 $aSHARDA, V.
700 1 $aCANO, A.M.
700 1 $aHROZENCIK, R.A.
700 1 $aNÚÑEZ, A.
700 1 $aZAMBRESKI, Z
700 1 $aNOZARI, S.
700 1 $aSMITH, G.E.B.
700 1 $aMOORE, L.
700 1 $aSHARMA, S.
700 1 $aGOWDA, P.
700 1 $aRAY, CH
700 1 $aSCHIPANSKI, M.
700 1 $aWASKOM , R.
773 $tJournal of the American Water Resources Association (JAWRA) , February 2019, Volume 55, Issue 1, Pages 6-23. DOI: https://doi.org/10.1111/1752-1688.12722
Descargar
Esconder MarcPresentar Marc Completo |
|
Registro original : |
INIA La Estanzuela (LE) |
|
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
|
|
| Acceso al texto completo restringido a Biblioteca INIA Tacuarembó. Por información adicional contacte bibliotb@tb.inia.org.uy. |
|
Registro completo
|
|
Biblioteca (s) : |
INIA Tacuarembó. |
|
Fecha actual : |
22/04/2019 |
|
Actualizado : |
22/04/2019 |
|
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
|
Circulación / Nivel : |
Internacional - -- |
|
Autor : |
MIRABALLES, C.; RIET-CORREA, F.; SAPORITI, T.; LARA, S.; PARODI, P.; SÁNCHEZ, J. |
|
Afiliación : |
MÓNICA CECILIA MIRABALLES FERRER, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FRANKLIN RIET-CORREA AMARAL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; TATIANA SAPORITI NOGUEIRA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. Universidad de la República (UdelaR)/ Facultad de Veterinaria.; STEPHANIE YOHANA LARA MARFETAN, Universidad de la República (UdelaR)/ Facultad de Veterinaria.; PABLO PARODI TEXEIRA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. Universidad de la República (UdelaR)/ Facultad de Veterinaria.; JAVIER SÁNCHEZ, University of Prince Edwards Island, Canada. |
|
Título : |
Probability of Rhipicephalus microplus introduction into farms by cattle movement using a Bayesian Belief Network. |
|
Fecha de publicación : |
2019 |
|
Fuente / Imprenta : |
Ticks and Tick-borne Diseases, 2019. |
|
DOI : |
10.1016/j.ttbdis.2019.04.009 |
|
Idioma : |
Inglés |
|
Notas : |
History Article: Received 1 October2018 // Received in revisedform 19March 2019 // Accepted 10April 2019. |
|
Contenido : |
Attempts to eliminate Rhipicephalus microplus from Uruguay have been unsuccessful, and, currently, the country is divided into two areas: a tick-free area and a tick-infested area. In the tick-infested area, different farms face different situations. Some farms are in regions where, due to environmental conditions or a lack of infrastructure, it is difficult to eliminate R. microplus, and the only option is to control it. In contrast, other farms can attempt complete removal. Before deciding whether a farmer should attempt to eliminate R. microplus, the probability of reintroduction must be evaluated. The objective of this study was to develop a probabilistic model
based on a Bayesian Belief Network (BBN) to assess the likelihood of a farm becoming infested with R. microplus via the introduction of tick-infested cattle. Only the tick-infested area was considered in the development of this model. Nine variables related to environmental conditions and biosecurity measures, with a focus on cattle
movement, were considered. Three different sources of data were used to populate the BBN model: data from the literature; a representative national survey from 2016; and a survey developed to identify biosecurity practices on farms. Model sensitivity and specificity were assessed, and an overall accuracy of 92% was obtained. The
model was applied to 33 farms located in the tick-infested area. For one farm, the probability of introduction of R. microplus was 1%; for three farms, the probability was between 21% and 34%; for seven farms, it was between 66% and 76%; and for 22 farms, the probability was greater than 83%. This model was useful for estimating the
probability of the introduction of R. microplus into farms, making it possible to assess the impact that the evaluated biosecurity measures have on the probability of introduction and, thus, guiding more objective decision making about the control or elimination of R. microplus from farms. MenosAttempts to eliminate Rhipicephalus microplus from Uruguay have been unsuccessful, and, currently, the country is divided into two areas: a tick-free area and a tick-infested area. In the tick-infested area, different farms face different situations. Some farms are in regions where, due to environmental conditions or a lack of infrastructure, it is difficult to eliminate R. microplus, and the only option is to control it. In contrast, other farms can attempt complete removal. Before deciding whether a farmer should attempt to eliminate R. microplus, the probability of reintroduction must be evaluated. The objective of this study was to develop a probabilistic model
based on a Bayesian Belief Network (BBN) to assess the likelihood of a farm becoming infested with R. microplus via the introduction of tick-infested cattle. Only the tick-infested area was considered in the development of this model. Nine variables related to environmental conditions and biosecurity measures, with a focus on cattle
movement, were considered. Three different sources of data were used to populate the BBN model: data from the literature; a representative national survey from 2016; and a survey developed to identify biosecurity practices on farms. Model sensitivity and specificity were assessed, and an overall accuracy of 92% was obtained. The
model was applied to 33 farms located in the tick-infested area. For one farm, the probability of introduction of R. microplus was 1%; for three farms, the pro... Presentar Todo |
|
Palabras claves : |
BAYESIAN BELIEF NETWORK; CATTLE TICK ELIMINATI; RHIPICEPHALUS MICROPLUS; RISK ASSESSMENT. |
|
Thesagro : |
PLAGAS DE ANIMALES. |
|
Asunto categoría : |
L72 Plagas de los animales |
|
Marc : |
LEADER 02862naa a2200265 a 4500
001 1059731
005 2019-04-22
008 2019 bl uuuu u00u1 u #d
024 7 $a10.1016/j.ttbdis.2019.04.009$2DOI
100 1 $aMIRABALLES, C.
245 $aProbability of Rhipicephalus microplus introduction into farms by cattle movement using a Bayesian Belief Network.$h[electronic resource]
260 $c2019
500 $aHistory Article: Received 1 October2018 // Received in revisedform 19March 2019 // Accepted 10April 2019.
520 $aAttempts to eliminate Rhipicephalus microplus from Uruguay have been unsuccessful, and, currently, the country is divided into two areas: a tick-free area and a tick-infested area. In the tick-infested area, different farms face different situations. Some farms are in regions where, due to environmental conditions or a lack of infrastructure, it is difficult to eliminate R. microplus, and the only option is to control it. In contrast, other farms can attempt complete removal. Before deciding whether a farmer should attempt to eliminate R. microplus, the probability of reintroduction must be evaluated. The objective of this study was to develop a probabilistic model based on a Bayesian Belief Network (BBN) to assess the likelihood of a farm becoming infested with R. microplus via the introduction of tick-infested cattle. Only the tick-infested area was considered in the development of this model. Nine variables related to environmental conditions and biosecurity measures, with a focus on cattle movement, were considered. Three different sources of data were used to populate the BBN model: data from the literature; a representative national survey from 2016; and a survey developed to identify biosecurity practices on farms. Model sensitivity and specificity were assessed, and an overall accuracy of 92% was obtained. The model was applied to 33 farms located in the tick-infested area. For one farm, the probability of introduction of R. microplus was 1%; for three farms, the probability was between 21% and 34%; for seven farms, it was between 66% and 76%; and for 22 farms, the probability was greater than 83%. This model was useful for estimating the probability of the introduction of R. microplus into farms, making it possible to assess the impact that the evaluated biosecurity measures have on the probability of introduction and, thus, guiding more objective decision making about the control or elimination of R. microplus from farms.
650 $aPLAGAS DE ANIMALES
653 $aBAYESIAN BELIEF NETWORK
653 $aCATTLE TICK ELIMINATI
653 $aRHIPICEPHALUS MICROPLUS
653 $aRISK ASSESSMENT
700 1 $aRIET-CORREA, F.
700 1 $aSAPORITI, T.
700 1 $aLARA, S.
700 1 $aPARODI, P.
700 1 $aSÁNCHEZ, J.
773 $tTicks and Tick-borne Diseases, 2019.
Descargar
Esconder MarcPresentar Marc Completo |
|
Registro original : |
INIA Tacuarembó (TBO) |
|
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
| Expresión de búsqueda válido. Check! |
|
|
