IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v12y2022i5p644-d805656.html
   My bibliography  Save this article

Effects of Seasonality and Climate on the Propagule Deposition Patterns of the Chestnut Blight Pathogen Cryphonectria parasitica in Orchards of the Alpine District of North Western Italy

Author

Listed:
  • Guglielmo Lione

    (Department of Agricultural, Forest and Food Sciences (DISAFA), University of Torino, Largo Paolo Braccini 2, I-10095 Grugliasco, Italy
    Chestnut R&D Center, Regione Gambarello 23, I-12013 Chiusa di Pesio, Italy)

  • Francesca Brescia

    (Department of Agricultural, Forest and Food Sciences (DISAFA), University of Torino, Largo Paolo Braccini 2, I-10095 Grugliasco, Italy
    Current address: National Research Council-Institute for Sustainable Plant Protection (CNR-IPSP), Strada delle Cacce, 73, I-10135 Torino, Italy.)

  • Luana Giordano

    (Department of Agricultural, Forest and Food Sciences (DISAFA), University of Torino, Largo Paolo Braccini 2, I-10095 Grugliasco, Italy
    Chestnut R&D Center, Regione Gambarello 23, I-12013 Chiusa di Pesio, Italy
    Current address: Laboratory of Lombardy Plant Health Service, c/o Fondazione Minoprio, Viale Raimondi 54, I-22070 Vertemate con Minoprio (CO), Italy.)

  • Paolo Gonthier

    (Department of Agricultural, Forest and Food Sciences (DISAFA), University of Torino, Largo Paolo Braccini 2, I-10095 Grugliasco, Italy
    Chestnut R&D Center, Regione Gambarello 23, I-12013 Chiusa di Pesio, Italy)

Abstract

Chestnut blight is the major disease of chestnuts ( Castanea spp.) cultivated worldwide for the production of edible nuts. The disease is caused by the pathogenic fungus Cryphonectria parasitica , which infects trees by means of airborne propagules penetrating through fresh wounds on stems and branches. The aims of this study were to (I) assess the temporal propagule deposition patterns of C. parasitica in the Alpine district of North Western Italy, (II) test and model the effects of seasonality and climate on the above patterns, and (III) investigate the spatial distribution of propagule deposition at the within-site scale. A two-year-long spore trapping experiment was conducted in three chestnut orchards. Approximately 1300 samples were collected and processed with a species-specific qPCR assay to quantitatively assess the propagule deposition of C. parasitica . Results showed that C. parasitica can release propagules all over the year, though with significant seasonal peaks in the spring and fall ( p < 0.05). Large propagule loads were significantly correlated ( p < 0.05) with an increasing number of rainy days of the week (days providing 1–10 mm/day of water). Models predicting periods at high risk of infection based on climate and seasonality were fitted and successfully validated ( p < 0.05).

Suggested Citation

  • Guglielmo Lione & Francesca Brescia & Luana Giordano & Paolo Gonthier, 2022. "Effects of Seasonality and Climate on the Propagule Deposition Patterns of the Chestnut Blight Pathogen Cryphonectria parasitica in Orchards of the Alpine District of North Western Italy," Agriculture, MDPI, vol. 12(5), pages 1-24, April.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:5:p:644-:d:805656
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/12/5/644/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/12/5/644/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Piñeiro, Gervasio & Perelman, Susana & Guerschman, Juan P. & Paruelo, José M., 2008. "How to evaluate models: Observed vs. predicted or predicted vs. observed?," Ecological Modelling, Elsevier, vol. 216(3), pages 316-322.
    2. Hui, Wallace & Gel, Yulia R. & Gastwirth, Joseph L., 2008. "lawstat: An R Package for Law, Public Policy and Biostatistics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 28(i03).
    3. Zeileis, Achim & Leisch, Friedrich & Hornik, Kurt & Kleiber, Christian, 2002. "strucchange: An R Package for Testing for Structural Change in Linear Regression Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 7(i02).
    4. Baddeley, Adrian & Turner, Rolf, 2005. "spatstat: An R Package for Analyzing Spatial Point Patterns," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 12(i06).
    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. Maria Lourdes Ordoñez Olivo & Zoltán Lakner, 2023. "Shaping the Knowledge Base of Bioeconomy Sectors Development in Latin American and Caribbean Countries: A Bibliometric Analysis," Sustainability, MDPI, vol. 15(6), pages 1-18, March.
    2. Arii, Ken & Caspersen, John P. & Jones, Trevor A. & Thomas, Sean C., 2008. "A selection harvesting algorithm for use in spatially explicit individual-based forest simulation models," Ecological Modelling, Elsevier, vol. 211(3), pages 251-266.
    3. Magdalena Mikolajek-Gocejna, 2021. "Estimation, Instability, and Non-Stationarity of Beta Coefficients for Twenty-four Emerging Markets in 2005-2021," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 370-395.
    4. Jiao Jieying & Hu Guanyu & Yan Jun, 2021. "A Bayesian marked spatial point processes model for basketball shot chart," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 17(2), pages 77-90, June.
    5. Akaev, Askar & Devezas, Tessaleno & Ichkitidze, Yuri & Sarygulov, Askar, 2021. "Forecasting the labor intensity and labor income share for G7 countries in the digital age," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    6. Booth, Shawn & Walters, William J & Steenbeek, Jeroen & Christensen, Villy & Charmasson, Sabine, 2020. "An Ecopath with Ecosim model for the Pacific coast of eastern Japan: Describing the marine environment and its fisheries prior to the Great East Japan earthquake," Ecological Modelling, Elsevier, vol. 428(C).
    7. Frank Davenport, 2017. "Estimating standard errors in spatial panel models with time varying spatial correlation," Papers in Regional Science, Wiley Blackwell, vol. 96, pages 155-177, March.
    8. Leandro, Camila & Jay-Robert, Pierre & Mériguet, Bruno & Houard, Xavier & Renner, Ian W., 2020. "Is my sdm good enough? insights from a citizen science dataset in a point process modeling framework," Ecological Modelling, Elsevier, vol. 438(C).
    9. Grün, Bettina & Kosmidis, Ioannis & Zeileis, Achim, 2012. "Extended Beta Regression in R: Shaken, Stirred, Mixed, and Partitioned," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i11).
    10. Du, Xiaodong & Yu, Cindy L. & Hayes, Dermot J., 2011. "Speculation and volatility spillover in the crude oil and agricultural commodity markets: A Bayesian analysis," Energy Economics, Elsevier, vol. 33(3), pages 497-503, May.
    11. Luca Piciullo & Vittoria Capobianco & Håkon Heyerdahl, 2022. "A first step towards a IoT-based local early warning system for an unsaturated slope in Norway," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(3), pages 3377-3407, December.
    12. Les Oxley & Chris Price & William Rea & Marco Reale, 2008. "A New Procedure to Test for H Self-Similarity," Working Papers in Economics 08/16, University of Canterbury, Department of Economics and Finance.
    13. Mensi, Walid & Lee, Yun-Jung & Al-Yahyaee, Khamis Hamed & Sensoy, Ahmet & Yoon, Seong-Min, 2019. "Intraday downward/upward multifractality and long memory in Bitcoin and Ethereum markets: An asymmetric multifractal detrended fluctuation analysis," Finance Research Letters, Elsevier, vol. 31(C), pages 19-25.
    14. Ruggieri, Eric & Antonellis, Marcus, 2016. "An exact approach to Bayesian sequential change point detection," Computational Statistics & Data Analysis, Elsevier, vol. 97(C), pages 71-86.
    15. Patrik Nosil & Zachariah Gompert & Daniel J. Funk, 2024. "Divergent dynamics of sexual and habitat isolation at the transition between stick insect populations and species," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    16. Vijay Rajagopal & Gregory Bass & Cameron G Walker & David J Crossman & Amorita Petzer & Anthony Hickey & Ivo Siekmann & Masahiko Hoshijima & Mark H Ellisman & Edmund J Crampin & Christian Soeller, 2015. "Examination of the Effects of Heterogeneous Organization of RyR Clusters, Myofibrils and Mitochondria on Ca2+ Release Patterns in Cardiomyocytes," PLOS Computational Biology, Public Library of Science, vol. 11(9), pages 1-31, September.
    17. Christoph Lambio & Tillman Schmitz & Richard Elson & Jeffrey Butler & Alexandra Roth & Silke Feller & Nicolai Savaskan & Tobia Lakes, 2023. "Exploring the Spatial Relative Risk of COVID-19 in Berlin-Neukölln," IJERPH, MDPI, vol. 20(10), pages 1-22, May.
    18. Liao, Jinbao & Li, Zhenqing & Quets, Jan J. & Nijs, Ivan, 2013. "Effects of space partitioning in a plant species diversity model," Ecological Modelling, Elsevier, vol. 251(C), pages 271-278.
    19. Abdollah Jalilian, 2017. "Modelling and classification of species abundance: a case study in the Barro Colorado Island plot," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(13), pages 2401-2409, October.
    20. Zeileis, Achim, 2006. "Implementing a class of structural change tests: An econometric computing approach," Computational Statistics & Data Analysis, Elsevier, vol. 50(11), pages 2987-3008, July.

    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:gam:jagris:v:12:y:2022:i:5:p:644-:d:805656. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.