IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v173y2019icp524-535.html
   My bibliography  Save this article

Risk of spread of tomato yellow leaf curl virus (TYLCV) in tomato crops under various climate change scenarios

Author

Listed:
  • Ramos, Rodrigo Soares
  • Kumar, Lalit
  • Shabani, Farzin
  • Picanço, Marcelo Coutinho

Abstract

Species distribution models (SDMs) are valuable for the information they provide to reduce the potential negative effects of climatic factors on agricultural production systems. Such information may be used to prevent the entry and spread of invasive species in new areas, as well as to monitor regions with current occurrence. This is the first study of Tomato yellow leaf curl virus (TYLCV) global distribution, focusing on the risk of this disease in areas projected to be suitable for open field tomato (Solanum lycopersicum) and for whitefly (Bemisia tabaci - biotypes B and Q). TYLCV (Begomovirus) is an important virus transmitted by B. tabaci and poses a risk to S. lycopersicum cultivation worldwide. Despite the importance of TYLCV, the potential impact of climate change on the global distribution of TYLCV in agricultural crops remains unstudied. The aim of this study was to identify the invasion risk levels for TYLCV in areas optimally conducive for open field tomato cultivation and suitable for B. tabaci (biotypes B and Q) under projected climate changes for the years 2050 and 2070 using MaxEnt and the Global Climate Model (HadGEM2_ES, MIROC5 and CCSM4) under four scenarios (RCPs 2.6, 4.5, 6.0, and 8.5). Our results show that large regions are projected to be suitable for TYLCV in areas of suitability for B. tabaci and optimal for open field tomato cultivation. In the predictions, most areas with optimal conditions for S. lycopersicum and suitable for B. tabaci will be under medium suitability for TYLCV under climate change scenarios. This research may be useful to design strategies to prevent the introduction and establishment of TYLCV where the occurrence has not yet been reported.

Suggested Citation

  • Ramos, Rodrigo Soares & Kumar, Lalit & Shabani, Farzin & Picanço, Marcelo Coutinho, 2019. "Risk of spread of tomato yellow leaf curl virus (TYLCV) in tomato crops under various climate change scenarios," Agricultural Systems, Elsevier, vol. 173(C), pages 524-535.
    • Handle: RePEc:eee:agisys:v:173:y:2019:i:c:p:524-535
    DOI: 10.1016/j.agsy.2019.03.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308521X18305870
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agsy.2019.03.020?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Malte Meinshausen & S. Smith & K. Calvin & J. Daniel & M. Kainuma & J-F. Lamarque & K. Matsumoto & S. Montzka & S. Raper & K. Riahi & A. Thomson & G. Velders & D.P. Vuuren, 2011. "The RCP greenhouse gas concentrations and their extensions from 1765 to 2300," Climatic Change, Springer, vol. 109(1), pages 213-241, November.
    2. Boria, Robert A. & Olson, Link E. & Goodman, Steven M. & Anderson, Robert P., 2014. "Spatial filtering to reduce sampling bias can improve the performance of ecological niche models," Ecological Modelling, Elsevier, vol. 275(C), pages 73-77.
    3. Owens, Hannah L. & Campbell, Lindsay P. & Dornak, L. Lynnette & Saupe, Erin E. & Barve, Narayani & Soberón, Jorge & Ingenloff, Kate & Lira-Noriega, Andrés & Hensz, Christopher M. & Myers, Corinne E. &, 2013. "Constraints on interpretation of ecological niche models by limited environmental ranges on calibration areas," Ecological Modelling, Elsevier, vol. 263(C), pages 10-18.
    4. Peterson, A. Townsend & Papeş, Monica & Soberón, Jorge, 2008. "Rethinking receiver operating characteristic analysis applications in ecological niche modeling," Ecological Modelling, Elsevier, vol. 213(1), pages 63-72.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhao, Jiongchao & Wang, Chong & Shi, Xiaoyu & Bo, Xiaozhi & Li, Shuo & Shang, Mengfei & Chen, Fu & Chu, Qingquan, 2021. "Modeling climatically suitable areas for soybean and their shifts across China," Agricultural Systems, Elsevier, vol. 192(C).
    2. Lu, Yongquan & Liu, Guilin & Xian, Yuyang & Tang, Jiaqi & Zhong, Liming, 2024. "Climate change brings both opportunities and challenges to rural revitalization in China: Evidence from apple geographical indication predictions," Agricultural Systems, Elsevier, vol. 216(C).

    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. Carlos Yañez-Arenas & A. Townsend Peterson & Karla Rodríguez-Medina & Narayani Barve, 2016. "Mapping current and future potential snakebite risk in the new world," Climatic Change, Springer, vol. 134(4), pages 697-711, February.
    2. Carlos Yañez-Arenas & A. Townsend Peterson & Karla Rodríguez-Medina & Narayani Barve, 2016. "Mapping current and future potential snakebite risk in the new world," Climatic Change, Springer, vol. 134(4), pages 697-711, February.
    3. Fourcade, Yoan, 2021. "Fine-tuning niche models matters in invasion ecology. A lesson from the land planarian Obama nungara," Ecological Modelling, Elsevier, vol. 457(C).
    4. Yinglian Qi & Xiaoyan Pu & Yaxiong Li & Dingai Li & Mingrui Huang & Xuan Zheng & Jiaxin Guo & Zhi Chen, 2022. "Prediction of Suitable Distribution Area of Plateau pika ( Ochotona curzoniae ) in the Qinghai–Tibet Plateau under Shared Socioeconomic Pathways (SSPs)," Sustainability, MDPI, vol. 14(19), pages 1-23, September.
    5. Herkt, K. Matthias B. & Barnikel, Günter & Skidmore, Andrew K. & Fahr, Jakob, 2016. "A high-resolution model of bat diversity and endemism for continental Africa," Ecological Modelling, Elsevier, vol. 320(C), pages 9-28.
    6. Sutton, G.F. & Martin, G.D., 2022. "Testing MaxEnt model performance in a novel geographic region using an intentionally introduced insect," Ecological Modelling, Elsevier, vol. 473(C).
    7. Marianna V. P. Simões & Hanieh Saeedi & Marlon E. Cobos & Angelika Brandt, 2021. "Environmental matching reveals non-uniform range-shift patterns in benthic marine Crustacea," Climatic Change, Springer, vol. 168(3), pages 1-20, October.
    8. David A. Prieto-Torres & Luis A. Sánchez-González & Marco F. Ortiz-Ramírez & Jorge E. Ramírez-Albores & Erick A. García-Trejo & Adolfo G. Navarro-Sigüenza, 2021. "Climate warming affects spatio-temporal biodiversity patterns of a highly vulnerable Neotropical avifauna," Climatic Change, Springer, vol. 165(3), pages 1-20, April.
    9. Carlos Mestanza-Ramón & Robinson J. Herrera Feijoo & Cristhian Chicaiza-Ortiz & Isabel Domínguez Gaibor & Rubén G. Mateo, 2021. "Estimation of Current and Future Suitable Areas for Tapirus pinchaque in Ecuador," Sustainability, MDPI, vol. 13(20), pages 1-14, October.
    10. Ali Uğur Özcan & Javier Velázquez & Víctor Rincón & Derya Gülçin & Kerim Çiçek, 2022. "Assessment of the Morphological Pattern of the Lebanon Cedar under Changing Climate: The Mediterranean Case," Land, MDPI, vol. 11(6), pages 1-18, May.
    11. repec:hal:journl:hal-04684634 is not listed on IDEAS
    12. Gupta, Rishabh & Mishra, Ashok, 2019. "Climate change induced impact and uncertainty of rice yield of agro-ecological zones of India," Agricultural Systems, Elsevier, vol. 173(C), pages 1-11.
    13. Wiltshire, Kathryn H & Tanner, Jason E, 2020. "Comparing maximum entropy modelling methods to inform aquaculture site selection for novel seaweed species," Ecological Modelling, Elsevier, vol. 429(C).
    14. Václavík, Tomáš & Meentemeyer, Ross K., 2009. "Invasive species distribution modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions?," Ecological Modelling, Elsevier, vol. 220(23), pages 3248-3258.
    15. Wongsathit Wongloet & Prach Kongthong & Aingorn Chaiyes & Worapong Singchat & Warong Suksavate & Nattakan Ariyaraphong & Thitipong Panthum & Artem Lisachov & Kitipong Jaisamut & Jumaporn Sonongbua & T, 2023. "Genetic Monitoring of the Last Captive Population of Greater Mouse-Deer on the Thai Mainland and Prediction of Habitat Suitability before Reintroduction," Sustainability, MDPI, vol. 15(4), pages 1-22, February.
    16. Inês Silva & Matthew Crane & Pongthep Suwanwaree & Colin Strine & Matt Goode, 2018. "Using dynamic Brownian Bridge Movement Models to identify home range size and movement patterns in king cobras," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-20, September.
    17. Jiří Mikšovský & Rudolf Brázdil & Petr Štĕpánek & Pavel Zahradníček & Petr Pišoft, 2014. "Long-term variability of temperature and precipitation in the Czech Lands: an attribution analysis," Climatic Change, Springer, vol. 125(2), pages 253-264, July.
    18. Wang, Junbo & Ma, Zhenyu & Fan, Xiayang, 2023. "We are all in the same boat: The welfare and carbon abatement effects of the EU carbon border adjustment mechanism," MPRA Paper 118978, University Library of Munich, Germany.
    19. B Eugene Smith & Mark K Johnston & Robert Lücking, 2016. "From GenBank to GBIF: Phylogeny-Based Predictive Niche Modeling Tests Accuracy of Taxonomic Identifications in Large Occurrence Data Repositories," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-15, March.
    20. Tony E. Wong & Alexander M. R. Bakker & Klaus Keller, 2017. "Impacts of Antarctic fast dynamics on sea-level projections and coastal flood defense," Climatic Change, Springer, vol. 144(2), pages 347-364, September.
    21. Singh, Kuntal & McClean, Colin J. & Büker, Patrick & Hartley, Sue E. & Hill, Jane K., 2017. "Mapping regional risks from climate change for rainfed rice cultivation in India," Agricultural Systems, Elsevier, vol. 156(C), pages 76-84.

    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:agisys:v:173:y:2019:i:c:p:524-535. 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.elsevier.com/locate/agsy .

    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.