IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v505y2025ics0304380025001012.html
   My bibliography  Save this article

Forecasting the risk of Phytophthora cinnamomi related-decline in Mediterranean forest ecosystems under climate change scenarios

Author

Listed:
  • Cidre-González, Adrián
  • Ruiz-Gómez, Francisco José
  • Bonet, Francisco Javier
  • González-Moreno, Pablo

Abstract

P. cinnamomi is an invasive pathogen which threatens the evergreen oak and sweet chestnut ecosystems in the Mediterranean Basin. Understanding the distribution of this forest pathogen remains uncertain due to the challenges in accurately assessing their presence until symptoms become apparent, making it challenging to anticipate its occurrence. In this study, we investigated the distribution and suitability of P. cinnamomi in France, Italy, Portugal, and Spain implementing a hybrid model (i.e. correlative and process-based) with the validation of a total of 527 recorded occurrences. We used a correlative model incorporating two categories of abiotic environmental variables: edaphic and topographic. Additionally, we utilized three process-based models accounting for key climate factors and considering earth observation data with high temporal resolution. Specifically, we estimated survival under extreme minimum and maximum temperatures, as well as growth risk during the growing season as a proxy of the severity of the pathogen. The combination of these four models yielded a more reliable estimation of the pathogen's distribution. Our findings revealed that higher probability of P. cinnamomi presence currently stem from acidic and less nutrient rich soils. Among the process-based models, the spring growth risk model displayed the most significant variation across the study area, with an expected increase over time. Nevertheless, the survival of P. cinnamomi during summer is predicted to limit its presence in certain areas of the Iberian Peninsula in the long term, particularly under higher emissions scenarios. Interestingly, the results also indicate a potential enhancement in the growth of P. cinnamomi in some regions, while simultaneously noting a decrease in summer survival in those same areas. These observations underscore the complexity and dynamic nature of pathogen distribution and emphasize the importance of considering multiple factors to gain a comprehensive understanding of its potential impact.

Suggested Citation

  • Cidre-González, Adrián & Ruiz-Gómez, Francisco José & Bonet, Francisco Javier & González-Moreno, Pablo, 2025. "Forecasting the risk of Phytophthora cinnamomi related-decline in Mediterranean forest ecosystems under climate change scenarios," Ecological Modelling, Elsevier, vol. 505(C).
  • Handle: RePEc:eee:ecomod:v:505:y:2025:i:c:s0304380025001012
    DOI: 10.1016/j.ecolmodel.2025.111115
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380025001012
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2025.111115?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Sillero, Neftalí & Arenas-Castro, Salvador & Enriquez‐Urzelai, Urtzi & Vale, Cândida Gomes & Sousa-Guedes, Diana & Martínez-Freiría, Fernando & Real, Raimundo & Barbosa, A.Márcia, 2021. "Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling," Ecological Modelling, Elsevier, vol. 456(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Díaz-Vallejo, Mauricio & Peña-Peniche, Alexander & Mota-Vargas, Claudio & Piña-Torres, Javier & Valencia-Rodríguez, Daniel & Rangel-Rivera, Coral E. & Gaviria-Hernández, Juliana & Rojas-Soto, Octavio, 2024. "Analyses of the variable selection using correlation methods: An approach to the importance of statistical inferences in the modelling process," Ecological Modelling, Elsevier, vol. 498(C).
    2. Marchetto, Elisa & Da Re, Daniele & Tordoni, Enrico & Bazzichetto, Manuele & Zannini, Piero & Celebrin, Simone & Chieffallo, Ludovico & Malavasi, Marco & Rocchini, Duccio, 2023. "Testing the effect of sample prevalence and sampling methods on probability- and favourability-based SDMs," Ecological Modelling, Elsevier, vol. 477(C).
    3. Broussin, Joséphine & Mouchet, Maud & Goberville, Eric, 2024. "Generating pseudo-absences in the ecological space improves the biological relevance of response curves in species distribution models," Ecological Modelling, Elsevier, vol. 498(C).
    4. Sillero, Neftalí & Campos, João Carlos & Arenas-Castro, Salvador & Barbosa, A.Márcia, 2023. "A curated list of R packages for ecological niche modelling," Ecological Modelling, Elsevier, vol. 476(C).
    5. Barker, Justin R. & MacIsaac, Hugh J., 2022. "Species distribution models applied to mosquitoes: Use, quality assessment, and recommendations for best practice," Ecological Modelling, Elsevier, vol. 472(C).
    6. Hang Zhang & Nurguli Abdusuli, 2024. "Ecological niche measurement and high-quality development of "the Belt and Road" core area," PLOS ONE, Public Library of Science, vol. 19(5), pages 1-19, May.
    7. Fernandez, Marc & Sillero, Neftali & Yesson, Chris, 2022. "To be or not to be: the role of absences in niche modelling for highly mobile species in dynamic marine environments," Ecological Modelling, Elsevier, vol. 471(C).
    8. Simon, Alois & Katzensteiner, Klaus & Wallentin, Gudrun, 2023. "The integration of hierarchical levels of scale in tree species distribution models of silver fir (Abies alba Mill.) and European beech (Fagus sylvatica L.) in mountain forests," Ecological Modelling, Elsevier, vol. 485(C).
    9. Diana Koldasbayeva & Polina Tregubova & Mikhail Gasanov & Alexey Zaytsev & Anna Petrovskaia & Evgeny Burnaev, 2024. "Challenges in data-driven geospatial modeling for environmental research and practice," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    10. G. Hounsou‐Dindin & R. Idohou & M. T. Donou Hounsode & A. C. Adomou & A. E. Assogbadjo & R. Glèlè Kakaï, 2024. "Climate change effects on desert date Balanites aegyptiaca (L.) Delile in Benin: Implications for conservation and domestication," Natural Resources Forum, Blackwell Publishing, vol. 48(1), pages 3-15, February.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:505:y:2025:i:c:s0304380025001012. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.