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| Acceso al texto completo restringido a Biblioteca INIA La Estanzuela. Por información adicional contacte bib_le@inia.org.uy. |
Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
Fecha : |
19/07/2022 |
Actualizado : |
20/07/2022 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Autor : |
LEADLEY, P.; GONZALEZ, A.; OBURA, D.; KRUG, C.B.; LONDOÑO-MURCIA, M.C.; MILLETTE, K.L.; RADULOVICI, A.; RANKOVIC, A.; SHANNON, L.J.; ARCHER, E.; ATO ARMAH, F.; NIC BAX, N,; CHAUDHARI, K.; COSTELLO, M.J.; DÁVALOS, L.M.; ROQUE, F DE O; DECLERCK, F.; DEE, L.E.; ESSL, F.; FERRIER, S.; GENOVESI, P.; GUARIGUATA, M.R.; HASHIMOTO, S.; IFEJIKA SPERANZA, CH.; ISBELL, F.; KOK, M.; LAVERY, S.D.; LECLÈRE, D.; LOYOLA, R.; LWASA, S.; MCGEOCH, M.; MORI, A.S.; NICHOLSON, E.; OCHOA, J.M.; ÖLLERER, K.; POLASKY, S.; RONDININI, C.; SCHROER, S.; SELOMANE, O.; SHEN, X.; STRASSBURG, B.; RASHID SUMAILA, U.; TITTENSOR, D.P.; TURAK, E.; URBINA, L.; VALLEJOS, M.; VÁZQUEZ-DOMÍNGUEZ, E.; VERBURG, P.H.; VISCONTI, P.; WOODLEY, S.; XU, J. |
Afiliación : |
PAUL LEADLEY, Laboratoire d’Ecologie Syste´ matique Evolution, Universite´ Paris-Saclay, CNRS, AgroParisTech, Paris, France.; ANDREW GONZALEZ, Department of Biology, Quebec Centre for Biodiversity Science, McGill University, Montreal, QC, Canada.; DAVID OBURA, Coastal Oceans Research and Development (CORDIO) East Africa, Mombasa, Kenya.; CORNELIA B. KRUG, Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.; MARIA CECILIA LONDOÑO-MURCIA, Scopus Research Institute of Biological Resources Alexander von Humboldt, Bogotá, Colombia.; KATIE L. MILLETTE, Group on Earth Observations Biodiversity Observation Network (GEO BON), McGill University, Montreal, QC, Canada.; ADRIANA RADULOVICI, Group on Earth Observations Biodiversity Observation Network (GEO BON), McGill University, Montreal, QC, Canada.; ALEKSANDAR RANKOVIC, Paris Institute of Political Studies, Paris, France.; LYNNE J. SHANNON, Department of Biological Sciences, University of Cape Town, Rondebosch, South Africa.; EMMA ARCHER, Department of Geography, Geoinformatics, and Meteorology, University of Pretoria, Pretoria, South Africa.; FREDERICK ATO ARMAH, Scopus Department of Environmental Science, School of Biological Sciences, University of Cape Coast, Cape Coast, Ghana.; NIC BAX, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Canberra, NSW, Australia.; KALPANA CHAUDHARI, Institute for Sustainable Development and Research (ISDR), Mumbai, India.; MARK JOHN COSTELLO, Faculty of Biosciences and Aquaculture, Nord University, Bodø, Norway.; LILIANA M. DÁVALO, Department of Ecology and Evolution, Consortium for Inter-disciplinary Environmental Research, Stony Brook University, Stony Brook, NY, USA.; FABIO DE OLIVEIRA ROQUE, Universidade Federal de Mato Grosso do Sul, Pioneiros, MS, Brazil.; FABRICE DECLERCK, Alliance of Bioversity International and CIAT, Montpellier, France.; LAURA E. DEE, Ecology and Evolutionary Biology, University of Colorado, Boulder, CO, USA.; FRANZ ESSL, Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria.; SIMON FERRIER, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Canberra, NSW, Australia.; PIERO GENOVESI, Italian National Institute for Environmental Protection and Research (ISPRA), Rome, Italy.; MANUEL R. GUARIGUATA, Center for International Forestry Research (CIFOR) and World Agroforestry (ICRAF), Lima, Peru,; SHIZUKA HASHIMOTO, Scopus Graduate School of Agriculture and Life Sciences, University of Tokyo, Tokyo, Japan.; CHINWE IFEJIKA SPERANZA, Institute of Geography, University of Bern, Bern, Switzerland.; FOREST ISBELL, Department of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MN, USA.; MARCEL KOK, PBL Netherlands Environmental Assessment Agency, the Hague, the Netherlands.; SHANE D. LAVERY, School of Biological Sciences and Institute of Marine Science University of Auckland, Auckland, New Zealand.; DAVID LECLÈRE, Biodiversity and Natural Resources Program (BNR), International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria.; RAFAEL LOYOLA, International Institute for Sustainability, Rio de Janeiro, RJ, Brazil.; SHUAIB LWASA, Makerere University, Kampala, Uganda.; MELODIE MCGEOCH, Department of Ecology, Evolution, and Environment, La Trobe University, Melbourne, VIC, Australia.; AKIRA S. MORI, Research Center for Advanced Science and Technology, University of Tokyo, Tokyo, Japan.; EMILY NICHOLSON, Centre for Integrative Ecology, School of Life and Environmental Science, Deakin University, Melbourne, VIC, Australia.; JOSE M. OCHOA, Coral Reef Ecosystems Lab, School of Biological Sciences, University of Queensland, Brisbane, QLD, Australia.; KINGA ÖLLERER, Centre for Ecological Research, Vácrátót, Hungary.; STEPHEN POLASKY, Department of Applied Economics and Department of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MN, USA.; CARLO RONDININI, Department of Biology and Biotechnologies, Sapienza University of Rome, Rome, Italy.; SIBYLLE SCHROER, Leibniz Institute of Freshwater Ecology and Inland Fisheries, Berlin, German.; ODIRILWE SELOMANE, Centre for Sustainability Transitions, Stellenbosch University, Stellenbosch, South Africa.; XIAOLI SHEN, State key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.; BERNARDO STRASSBURG, International Institute for Sustainability, Rio de Janeiro, RJ, Brazi.; USSIF RASHID SUMAILA, Institute for the Oceans and Fisheries, University of British Columbia, Vancouver, BC, Canada.; DEREK P. TITTENSOR, Department of Biology, Dalhousie University, Halifax, NS, Canada.; EREN TURAK, New South Wales Department of Planning, Industry, and Environment, Parramatta, NSW, Australia.; LUIS URBINA, Coral Reef Ecosystems Lab, School of Biological Sciences, University of Queensland, Brisbane, QLD, Australia.; MARÍA VALLEJOS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay./Facultad de Agronomía, Universidad de Buenos Aires, Buenos Aires, Argentina.; ELLA VÁZQUEZ-DOMÍNGUEZ, Scopus Departamento de Ecología de la Biodiversidad, Instituto de Ecología, Universidad Nacional Autónoma de México, Mexico City, Mexico.; PETER H. VERBURG, Institute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.; PIERO VISCONTI, Biodiversity and Natural Resources Program (BNR), International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria.; STEPHEN WOODLEY, International Union for Conservation of Nature World Commission on Protected Areas (IUCN WCPA), Chelsea, QC, Canada.; JIANCHU XU, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China. |
Título : |
Achieving global biodiversity goals by 2050 requires urgent and integrated actions. |
Fecha de publicación : |
2022 |
Fuente / Imprenta : |
One Earth, 2022, Volume 5, Issue 6, Pages 597-603. doi: https://doi.org/10.1016/j.oneear.2022.05.009 |
DOI : |
10.1016/j.oneear.2022.05.009 |
Idioma : |
Inglés |
Notas : |
Artticle history: Available online 17 June 2022, Version of Record 17 June 2022. |
Contenido : |
Human impacts on the Earth's biosphere are driving the global biodiversity crisis. Governments are preparing to agree on a set of actions intended to halt the loss of biodiversity and put it on a path to recovery by 2050. We provide evidence that the proposed actions can bend the curve for biodiversity, but only if these actions are implemented urgently and in an integrated manner |
Palabras claves : |
Earth's biosphere; Global biodiversity crisis; Global biodiversity framework; Human impacts; PLATAFORMA DE INVESTIGACIÓN EN SALUD ANIMAL; PLATAFORMA SALUD ANINMAL. |
Thesagro : |
BIODIVERSIDAD. |
Asunto categoría : |
L01 Ganadería |
Marc : |
LEADER 02703naa a2200829 a 4500 001 1063438 005 2022-07-20 008 2022 bl uuuu u00u1 u #d 024 7 $a10.1016/j.oneear.2022.05.009$2DOI 100 1 $aLEADLEY, P. 245 $aAchieving global biodiversity goals by 2050 requires urgent and integrated actions.$h[electronic resource] 260 $c2022 500 $aArtticle history: Available online 17 June 2022, Version of Record 17 June 2022. 520 $aHuman impacts on the Earth's biosphere are driving the global biodiversity crisis. Governments are preparing to agree on a set of actions intended to halt the loss of biodiversity and put it on a path to recovery by 2050. We provide evidence that the proposed actions can bend the curve for biodiversity, but only if these actions are implemented urgently and in an integrated manner 650 $aBIODIVERSIDAD 653 $aEarth's biosphere 653 $aGlobal biodiversity crisis 653 $aGlobal biodiversity framework 653 $aHuman impacts 653 $aPLATAFORMA DE INVESTIGACIÓN EN SALUD ANIMAL 653 $aPLATAFORMA SALUD ANINMAL 700 1 $aGONZALEZ, A. 700 1 $aOBURA, D. 700 1 $aKRUG, C.B. 700 1 $aLONDOÑO-MURCIA, M.C. 700 1 $aMILLETTE, K.L. 700 1 $aRADULOVICI, A. 700 1 $aRANKOVIC, A. 700 1 $aSHANNON, L.J. 700 1 $aARCHER, E. 700 1 $aATO ARMAH, F. 700 1 $aNIC BAX, N, 700 1 $aCHAUDHARI, K. 700 1 $aCOSTELLO, M.J. 700 1 $aDÁVALOS, L.M. 700 1 $aROQUE, F DE O 700 1 $aDECLERCK, F. 700 1 $aDEE, L.E. 700 1 $aESSL, F. 700 1 $aFERRIER, S. 700 1 $aGENOVESI, P. 700 1 $aGUARIGUATA, M.R. 700 1 $aHASHIMOTO, S. 700 1 $aIFEJIKA SPERANZA, CH. 700 1 $aISBELL, F. 700 1 $aKOK, M. 700 1 $aLAVERY, S.D. 700 1 $aLECLÈRE, D. 700 1 $aLOYOLA, R. 700 1 $aLWASA, S. 700 1 $aMCGEOCH, M. 700 1 $aMORI, A.S. 700 1 $aNICHOLSON, E. 700 1 $aOCHOA, J.M. 700 1 $aÖLLERER, K. 700 1 $aPOLASKY, S. 700 1 $aRONDININI, C. 700 1 $aSCHROER, S. 700 1 $aSELOMANE, O. 700 1 $aSHEN, X. 700 1 $aSTRASSBURG, B. 700 1 $aRASHID SUMAILA, U. 700 1 $aTITTENSOR, D.P. 700 1 $aTURAK, E. 700 1 $aURBINA, L. 700 1 $aVALLEJOS, M. 700 1 $aVÁZQUEZ-DOMÍNGUEZ, E. 700 1 $aVERBURG, P.H. 700 1 $aVISCONTI, P. 700 1 $aWOODLEY, S. 700 1 $aXU, J. 773 $tOne Earth, 2022, Volume 5, Issue 6, Pages 597-603. doi: https://doi.org/10.1016/j.oneear.2022.05.009
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| Acceso al texto completo restringido a Biblioteca INIA Tacuarembó. Por información adicional contacte bibliotb@tb.inia.org.uy. |
Registro completo
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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.
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