IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i16p12320-d1216102.html
   My bibliography  Save this article

Eco-Geography of Dioscorea composita (Hemsl.) in México and Central America under the Influence of Climate Change

Author

Listed:
  • Jocelyn M. Velázquez-Hernández

    (Departamento de Producción Sustentable, Universidad de Guadalajara, Zapopan 45110, Jalisco, Mexico)

  • José Ariel Ruíz-Corral

    (Departamento de Ciencias Ambientales, Universidad de Guadalajara, Zapopan 45110, Jalisco, Mexico)

  • Noé Durán-Puga

    (Departamento de Producción Sustentable, Universidad de Guadalajara, Zapopan 45110, Jalisco, Mexico)

  • Diego R. González-Eguiarte

    (Departamento de Producción Sustentable, Universidad de Guadalajara, Zapopan 45110, Jalisco, Mexico)

  • Fernando Santacruz-Ruvalcaba

    (Departamento de Producción Agrícola, Universidad de Guadalajara, Zapopan 45110, Jalisco, Mexico)

  • Giovanni Emmanuel García-Romero

    (Dirección del Medio Ambiente del Municipio de Guadalajara, Guadalajara 44638, Jalisco, Mexico)

  • Jesús Germán de la Mora-Castañeda

    (Facultad de Ciencias Biológicas y Agropecuarias, Universidad de Colima, Tecomán 28100, Colima, Mexico)

  • Carlos Félix Barrera-Sánchez

    (Departamento de Ciencias Ambientales, Universidad de Guadalajara, Zapopan 45110, Jalisco, Mexico)

  • Agustín Gallegos-Rodríguez

    (Departamento de Producción Forestal, Universidad de Guadalajara, Zapopan 45110, Jalisco, Mexico)

Abstract

Dioscorea composita is a plant with historical recognition for the production of secondary metabolites of pharmaceutical importance, including diosgenin, and with great nutritional and ethnobotanical value in its center of origin (México and Central America). Furthermore, it is considered a promising therapeutic agent against cancer. Currently, México is one of the two most important countries producing this yam; however, climate change is altering the environmental conditions of its natural habits, threatening its preservation and productivity. This is why this research was focused on characterizing the eco-geography of D. composita and predicting its potential geographic distribution under climate change scenarios in México-Central America. A collection of 408 geo-referenced accessions was used to determine its climatic adaptation, ecological descriptors, and the current and future potential geographic distribution, which was modeled with the MaxEnt model through the Kuenm R-package. For future climate scenarios, an ensemble of the GCMs HadGEM-ES and CCSM4 was used. Results showed that D. composita adapts to warm and humid and very humid agro-climates and, the most contributing variables for its presence are annual and seasonal moisture availability indices, the seasonal photoperiod, annual thermal range, and Bio14 and Bio11. The current potential distribution (692,123 km 2 ) of D. composita might decrease by the year 2050 RCP4.5 (365,680 km 2 ) and might increase by 2050 under the scenario RCP8.5 (763,589 km 2 ), showing this plant could be a good crop option for this climate change scenario. The findings obtained provide valuable information that will allow for the effective utilization of this plant, both in terms of developing new pharmaceutical products and implementing appropriate conservation strategies.

Suggested Citation

  • Jocelyn M. Velázquez-Hernández & José Ariel Ruíz-Corral & Noé Durán-Puga & Diego R. González-Eguiarte & Fernando Santacruz-Ruvalcaba & Giovanni Emmanuel García-Romero & Jesús Germán de la Mora-Castañe, 2023. "Eco-Geography of Dioscorea composita (Hemsl.) in México and Central America under the Influence of Climate Change," Sustainability, MDPI, vol. 15(16), pages 1-15, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:16:p:12320-:d:1216102
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/16/12320/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/16/12320/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. H. Oğuz Çoban & Ömer K. Örücü & E. Seda Arslan, 2020. "MaxEnt Modeling for Predicting the Current and Future Potential Geographical Distribution of Quercus libani Olivier," Sustainability, MDPI, vol. 12(7), pages 1-17, March.
    3. Emmanuel Junior Zuza & Kadmiel Maseyk & Shonil A Bhagwat & Kauê de Sousa & Andrew Emmott & William Rawes & Yoseph Negusse Araya, 2021. "Climate suitability predictions for the cultivation of macadamia (Macadamia integrifolia) in Malawi using climate change scenarios," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-20, September.
    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. Kalthum O. Radha & Nabaz R. Khwarahm, 2022. "An Integrated Approach to Map the Impact of Climate Change on the Distributions of Crataegus azarolus and Crataegus monogyna in Kurdistan Region, Iraq," Sustainability, MDPI, vol. 14(21), pages 1-31, November.
    2. 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.
    3. 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.
    4. 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).
    5. Feng Dong & Chih-Ming Hung & Shou-Hsien Li & Xiao-Jun Yang, 2021. "Potential Himalayan community turnover through the Late Pleistocene," Climatic Change, Springer, vol. 164(1), pages 1-10, January.
    6. Christophe Botella & Alexis Joly & Pascal Monestiez & Pierre Bonnet & François Munoz, 2020. "Bias in presence-only niche models related to sampling effort and species niches: Lessons for background point selection," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-18, May.
    7. Dana H. Mills & Michael L. McKinney, 2024. "Climate Change and Jump Dispersal Drive Invasion of the Rosy Wolfsnail ( Euglandina rosea ) in the United States," Sustainability, MDPI, vol. 16(5), pages 1-14, February.
    8. Zeng, Yiwen & Low, Bi Wei & Yeo, Darren C.J., 2016. "Novel methods to select environmental variables in MaxEnt: A case study using invasive crayfish," Ecological Modelling, Elsevier, vol. 341(C), pages 5-13.
    9. Schartel, Tyler E. & Cao, Yong, 2024. "Background selection complexity influences Maxent predictive performance in freshwater systems," Ecological Modelling, Elsevier, vol. 488(C).
    10. Van Eupen, Camille & Maes, Dirk & Herremans, Marc & Swinnen, Kristijn R.R. & Somers, Ben & Luca, Stijn, 2021. "The impact of data quality filtering of opportunistic citizen science data on species distribution model performance," Ecological Modelling, Elsevier, vol. 444(C).
    11. 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.
    12. 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).
    13. 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.
    14. Siyuan Xie & He Si & Hongxia Sun & Qian Zhao & Xiaodong Li & Shiqiang Wang & Junfeng Niu & Zhezhi Wang, 2023. "Predicting the Potential Distribution of the Endangered Plant Eucommia ulmoides in China under the Background of Climate Change," Sustainability, MDPI, vol. 15(6), pages 1-23, March.
    15. 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.
    16. 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.
    17. Marsh, Charles J. & Gavish, Yoni & Kuemmerlen, Mathias & Stoll, Stefan & Haase, Peter & Kunin, William E., 2023. "SDM profiling: A tool for assessing the information-content of sampled and unsampled locations for species distribution models," Ecological Modelling, Elsevier, vol. 475(C).
    18. Dimitra-Lida Rammou & Christos Astaras & Despina Migli & George Boutsis & Antonia Galanaki & Theodoros Kominos & Dionisios Youlatos, 2022. "European Ground Squirrels at the Edge: Current Distribution Status and Anticipated Impact of Climate on Europe’s Southernmost Population," Land, MDPI, vol. 11(2), pages 1-18, February.
    19. Robin Lines & Dimitrios Bormpoudakis & Panteleimon Xofis & Joseph Tzanopoulos, 2021. "Modelling Multi-Species Connectivity at the Kafue-Zambezi Interface: Implications for Transboundary Carnivore Conservation," Sustainability, MDPI, vol. 13(22), pages 1-15, November.
    20. 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).

    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:jsusta:v:15:y:2023:i:16:p:12320-:d:1216102. 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.