Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy)
The plant-pathogenic bacterium Xylella fastidiosa was first reported in Europe in 2013, in the province of Lecce, Italy, where extensive areas were affected by the olive quick decline syndrome, caused by the subsp. pauca. In Alicante, Spain, almond leaf scorch, caused by X. fastidiosa subsp. multipl...
| Autores principales: | , , , , , , , |
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| Formato: | publishedVersion |
| Lenguaje: | Inglés |
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Frontiers
2020
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.11939/6576 https://doi.org/10.3389/fpls.2020.01204 https://www.frontiersin.org/articles/10.3389/fpls.2020.01204/full |
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| author | Cendoya, Martina Martínez-Minaya, Joaquín Dalmau, Vicente Ferrer, Amparo Saponari, Maria Conesa, David López-Quílez, Antonio Vicent, Antonio |
| author_browse | Cendoya, Martina Conesa, David Dalmau, Vicente Ferrer, Amparo López-Quílez, Antonio Martínez-Minaya, Joaquín Saponari, Maria Vicent, Antonio |
| author_facet | Cendoya, Martina Martínez-Minaya, Joaquín Dalmau, Vicente Ferrer, Amparo Saponari, Maria Conesa, David López-Quílez, Antonio Vicent, Antonio |
| author_sort | Cendoya, Martina |
| collection | ReDivia |
| description | The plant-pathogenic bacterium Xylella fastidiosa was first reported in Europe in 2013, in the province of Lecce, Italy, where extensive areas were affected by the olive quick decline syndrome, caused by the subsp. pauca. In Alicante, Spain, almond leaf scorch, caused by X. fastidiosa subsp. multiplex, was detected in 2017. The effects of climatic and spatial factors on the geographic distribution of X. fastidiosa in these two infested regions in Europe were studied. The presence/absence data of X. fastidiosa in the official surveys were analyzed using Bayesian hierarchical models through the integrated nested Laplace approximation (INLA) methodology. Climatic covariates were obtained from the WorldClim v.2 database. A categorical variable was also included according to Purcell’s minimum winter temperature thresholds for the risk of occurrence of Pierce’s disease of grapevine, caused by X. fastidiosa subsp. fastidiosa. In Alicante, data were presented aggregated on a 1 km grid (lattice data), where the spatial effect was included in the model through a conditional autoregressive structure. In Lecce, data were observed at continuous locations occurring within a defined spatial domain (geostatistical data). Therefore, the spatial effect was included via the stochastic partial differential equation approach. In Alicante, the pathogen was detected in all four of Purcell’s categories, illustrating the environmental plasticity of the subsp. multiplex. Here, none of the climatic covariates were retained in the selected model. Only two of Purcell’s categories were represented in Lecce. The mean diurnal range (bio2) and the mean temperature of the wettest quarter (bio8) were retained in the selected model, with a negative relationship with the presence of the pathogen. However, this may be due to the heterogeneous sampling distribution having a confounding effect with the climatic covariates. In both regions, the spatial structure had a strong influence on the models, but not the climatic covariates. Therefore, pathogen distribution was largely defined by the spatial relationship between geographic locations. This substantial contribution of the spatial effect in the models might indicate that the current extent of X. fastidiosa in the study regions had arisen from a single focus or from several foci, which have been coalesced. |
| format | publishedVersion |
| id | ReDivia6576 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | Frontiers |
| publisherStr | Frontiers |
| record_format | dspace |
| spelling | ReDivia65762025-04-25T14:47:24Z Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy) Cendoya, Martina Martínez-Minaya, Joaquín Dalmau, Vicente Ferrer, Amparo Saponari, Maria Conesa, David López-Quílez, Antonio Vicent, Antonio hierarchical Bayesian models integrated nested Laplace approximation stochastic partial differential equation Xylella fastidiosa species distribution models olive quick decline almond leaf scorch H20 Plant diseases The plant-pathogenic bacterium Xylella fastidiosa was first reported in Europe in 2013, in the province of Lecce, Italy, where extensive areas were affected by the olive quick decline syndrome, caused by the subsp. pauca. In Alicante, Spain, almond leaf scorch, caused by X. fastidiosa subsp. multiplex, was detected in 2017. The effects of climatic and spatial factors on the geographic distribution of X. fastidiosa in these two infested regions in Europe were studied. The presence/absence data of X. fastidiosa in the official surveys were analyzed using Bayesian hierarchical models through the integrated nested Laplace approximation (INLA) methodology. Climatic covariates were obtained from the WorldClim v.2 database. A categorical variable was also included according to Purcell’s minimum winter temperature thresholds for the risk of occurrence of Pierce’s disease of grapevine, caused by X. fastidiosa subsp. fastidiosa. In Alicante, data were presented aggregated on a 1 km grid (lattice data), where the spatial effect was included in the model through a conditional autoregressive structure. In Lecce, data were observed at continuous locations occurring within a defined spatial domain (geostatistical data). Therefore, the spatial effect was included via the stochastic partial differential equation approach. In Alicante, the pathogen was detected in all four of Purcell’s categories, illustrating the environmental plasticity of the subsp. multiplex. Here, none of the climatic covariates were retained in the selected model. Only two of Purcell’s categories were represented in Lecce. The mean diurnal range (bio2) and the mean temperature of the wettest quarter (bio8) were retained in the selected model, with a negative relationship with the presence of the pathogen. However, this may be due to the heterogeneous sampling distribution having a confounding effect with the climatic covariates. In both regions, the spatial structure had a strong influence on the models, but not the climatic covariates. Therefore, pathogen distribution was largely defined by the spatial relationship between geographic locations. This substantial contribution of the spatial effect in the models might indicate that the current extent of X. fastidiosa in the study regions had arisen from a single focus or from several foci, which have been coalesced. 2020-08-19T12:35:55Z 2020-08-19T12:35:55Z 2020 publishedVersion Cendoya, M., Martínez-Minaya, J., Dalmau, V., Ferrer, A., Saponari, M., Conesa, D., López-Quílez, A. and Vicent, A. (2020) Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy). Front. Plant Sci. 11:1204. 1664-462X http://hdl.handle.net/20.500.11939/6576 https://doi.org/10.3389/fpls.2020.01204 https://www.frontiersin.org/articles/10.3389/fpls.2020.01204/full en Info:eu-repo/grantAgreement/EC/H2020/727987 E-RTA 2017-00004-C06-01 XF-ACTORS no. 727987 Organización Interprofesional del Aceite de Oliva Español Atribución 3.0 España http://creativecommons.org/licenses/by/3.0/es/ openAccess Frontiers electronico |
| spellingShingle | hierarchical Bayesian models integrated nested Laplace approximation stochastic partial differential equation Xylella fastidiosa species distribution models olive quick decline almond leaf scorch H20 Plant diseases Cendoya, Martina Martínez-Minaya, Joaquín Dalmau, Vicente Ferrer, Amparo Saponari, Maria Conesa, David López-Quílez, Antonio Vicent, Antonio Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy) |
| title | Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy) |
| title_full | Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy) |
| title_fullStr | Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy) |
| title_full_unstemmed | Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy) |
| title_short | Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy) |
| title_sort | spatial bayesian modeling applied to the surveys of xylella fastidiosa in alicante spain and apulia italy |
| topic | hierarchical Bayesian models integrated nested Laplace approximation stochastic partial differential equation Xylella fastidiosa species distribution models olive quick decline almond leaf scorch H20 Plant diseases |
| url | http://hdl.handle.net/20.500.11939/6576 https://doi.org/10.3389/fpls.2020.01204 https://www.frontiersin.org/articles/10.3389/fpls.2020.01204/full |
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