Non-stationary spatial model for the distribution of Xylella fastidiosa in Alicante
Describing the effect of climatic and spatial factors on the geographic distribution of the plant pathogenic bacterium Xylella fastidiosa has been the main aim since the moment that it was discovered its presence in Alicante (Spain). This work started with the analysis of the presence/absence data o...
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
Servicio Editorial de la Universidad del País Vasco
2022
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| Acceso en línea: | http://hdl.handle.net/20.500.11939/8193 |
| _version_ | 1855492442935001088 |
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| author | Cendoya, Martina Hubel, Ana Vicent, Antonio Conesa, David |
| author2 | Irigoien, Itziar |
| author_browse | Cendoya, Martina Conesa, David Hubel, Ana Irigoien, Itziar Vicent, Antonio |
| author_facet | Irigoien, Itziar Cendoya, Martina Hubel, Ana Vicent, Antonio Conesa, David |
| author_sort | Cendoya, Martina |
| collection | ReDivia |
| description | Describing the effect of climatic and spatial factors on the geographic distribution of the plant pathogenic bacterium Xylella fastidiosa has been the main aim since the moment that it was discovered its presence in Alicante (Spain). This work started with the analysis of the presence/absence data of the pathogen using Bayesian hierarchical models through the integrated nested Laplace approximation methodology and the stochastic partial differential equation approach. Spatial models usually assume stationarity, however, this may be not applicable when physical barriers are present in the study area. Taking into account the
irregularities of the terrain and what this may entail in the spread of the disease, higher altitude areas have been considered as possible barriers in the area of interest. The results show that the spatial effect had a strong effect in the model and also that there was no great influence of the barriers due to their reduced extension. Future work will be focused in using these barriers models
with theoretical phytosanitary barriers. |
| format | Objeto de conferencia |
| id | ReDivia8193 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Servicio Editorial de la Universidad del País Vasco |
| publisherStr | Servicio Editorial de la Universidad del País Vasco |
| record_format | dspace |
| spelling | ReDivia81932025-04-25T14:53:28Z Non-stationary spatial model for the distribution of Xylella fastidiosa in Alicante Cendoya, Martina Hubel, Ana Vicent, Antonio Conesa, David Irigoien, Itziar INLA SPDE Barriers Alicante Bayesian hierarchical models U10 Mathematical and statistical methods H20 Plant diseases Xylella fastidiosa Describing the effect of climatic and spatial factors on the geographic distribution of the plant pathogenic bacterium Xylella fastidiosa has been the main aim since the moment that it was discovered its presence in Alicante (Spain). This work started with the analysis of the presence/absence data of the pathogen using Bayesian hierarchical models through the integrated nested Laplace approximation methodology and the stochastic partial differential equation approach. Spatial models usually assume stationarity, however, this may be not applicable when physical barriers are present in the study area. Taking into account the irregularities of the terrain and what this may entail in the spread of the disease, higher altitude areas have been considered as possible barriers in the area of interest. The results show that the spatial effect had a strong effect in the model and also that there was no great influence of the barriers due to their reduced extension. Future work will be focused in using these barriers models with theoretical phytosanitary barriers. 2022-06-03T08:54:46Z 2022-06-03T08:54:46Z 2020 conferenceObject Cendoya, M., Hubel, A., Vicent, A. & Conesa D. (2021). Non-stationary spatial model for the distribution of Xylella fastidiosa in Alicante. Proceedings of the 35th International Workshop on Statistical Modelling. 35-38. 978-84-1319-267-3 http://hdl.handle.net/20.500.11939/8193 en 2020-07-20 Proceedings of the 35th International Workshop on Statistical Modelling Bilbao, Basque Country, Spain The present work has received funding from the European Unions Horizon 2020 research and innovation programme under Grant Agreement No. 727987 - XF-ACTORS. The present work has received funding from Project E-RTA 2017-00004- C06-01 FEDER INIA-AEI Ministerio de Ciencia, Innovación y Universidades and Organización Interprofesional del Aceite de Oliva Español, Spain. The present work has received funding from grants MTM2016-77501-P TEC2016-81900-REDT from the Spanish Ministry of Science, Innovation and Universities State Research Agency. Atribución-NoComercial-SinDerivadas 3.0 España http://creativecommons.org/licenses/by-nc-nd/3.0/es/ openAccess Servicio Editorial de la Universidad del País Vasco electronico |
| spellingShingle | INLA SPDE Barriers Alicante Bayesian hierarchical models U10 Mathematical and statistical methods H20 Plant diseases Xylella fastidiosa Cendoya, Martina Hubel, Ana Vicent, Antonio Conesa, David Non-stationary spatial model for the distribution of Xylella fastidiosa in Alicante |
| title | Non-stationary spatial model for the distribution of Xylella fastidiosa in Alicante |
| title_full | Non-stationary spatial model for the distribution of Xylella fastidiosa in Alicante |
| title_fullStr | Non-stationary spatial model for the distribution of Xylella fastidiosa in Alicante |
| title_full_unstemmed | Non-stationary spatial model for the distribution of Xylella fastidiosa in Alicante |
| title_short | Non-stationary spatial model for the distribution of Xylella fastidiosa in Alicante |
| title_sort | non stationary spatial model for the distribution of xylella fastidiosa in alicante |
| topic | INLA SPDE Barriers Alicante Bayesian hierarchical models U10 Mathematical and statistical methods H20 Plant diseases Xylella fastidiosa |
| url | http://hdl.handle.net/20.500.11939/8193 |
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