Search Results - "Cendoya, Martina"

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  1. 1

    Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy) by Cendoya, Martina, Martínez-Minaya, Joaquín, Dalmau, Vicente, Ferrer, Amparo, Saponari, Maria, Conesa, David, López-Quílez, Antonio, Vicent, Antonio

    Published in Frontiers in plant science (14-08-2020)
    “…The plant-pathogenic bacterium was first reported in Europe in 2013, in the province of Lecce, Italy, where extensive areas were affected by the olive quick…”
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  2. 2

    A spatio-temporal dataset of plant pests’ first introductions across the EU and potential entry pathways by Rosace, Maria Chiara, Cendoya, Martina, Mattion, Giulia, Vicent, Antonio, Battisti, Andrea, Cavaletto, Giacomo, Marini, Lorenzo, Rossi, Vittorio

    Published in Scientific data (21-10-2023)
    “…World trade has greatly increased in recent decades, together with a higher risk of introducing non-indigenous pests. Introduction trends show no sign of…”
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  3. 3

    Impact of Xylella fastidiosa subspecies pauca in European olives by Schneider, Kevin, van der Werf, Wopke, Cendoya, Martina, Mourits, Monique, Navas-Cortés, Juan A., Vicent, Antonio, Lansink, Alfons Oude

    “…Xylella fastidiosa is the causal agent of plant diseases that cause massive economic damage. In 2013, a strain of the bacterium was, for the first time,…”
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  4. 4

    Modeling the Spatial Distribution of Xylella fastidiosa : A Nonstationary Approach with Dispersal Barriers by Cendoya, Martina, Hubel, Ana, Conesa, David, Vicent, Antonio

    Published in Phytopathology (01-05-2022)
    “…Spatial species distribution models often assume isotropy and stationarity, implying that spatial dependence is direction-invariant and uniform throughout the…”
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  5. 5

    An Individual-Based Spatial Epidemiological Model for the Spread of Plant Diseases by Cendoya, Martina, Navarro-Quiles, Ana, López-Quílez, Antonio, Vicent, Antonio, Conesa, David

    “…Abstract In the study of plant disease epidemics, the state of each individual in the population and their spatial location should be considered when modeling…”
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