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

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  • 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
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    References listed on IDEAS

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    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.
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