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Future projections for Mexican faunas under global climate change scenarios

Author

Listed:
  • A. Townsend Peterson

    (The University of Kansas)

  • Miguel A. Ortega-Huerta

    (The University of Kansas)

  • Jeremy Bartley

    (The University of Kansas)

  • Victor Sánchez-Cordero

    (Universidad Nacional Autónoma de México)

  • Jorge Soberón

    (Universidad Nacional Autónoma de México)

  • Robert H. Buddemeier

    (The University of Kansas)

  • David R. B. Stockwell

    (University of California)

Abstract

Global climates are changing rapidly, with unexpected consequences1. Because elements of biodiversity respond intimately to climate as an important driving force of distributional limitation2, distributional shifts and biodiversity losses are expected3,4. Nevertheless, in spite of modelling efforts focused on single species2 or entire ecosystems5, a few preliminary surveys of fauna-wide effects6,7, and evidence of climate change-mediated shifts in several species8,9, the likely effects of climate change on species' distributions remain little known, and fauna-wide or community-level effects are almost completely unexplored6. Here, using a genetic algorithm and museum specimen occurrence data, we develop ecological niche models for 1,870 species occurring in Mexico and project them onto two climate surfaces modelled for 2055. Although extinctions and drastic range reductions are predicted to be relatively few, species turnover in some local communities is predicted to be high (>40% of species), suggesting that severe ecological perturbations may result.

Suggested Citation

  • A. Townsend Peterson & Miguel A. Ortega-Huerta & Jeremy Bartley & Victor Sánchez-Cordero & Jorge Soberón & Robert H. Buddemeier & David R. B. Stockwell, 2002. "Future projections for Mexican faunas under global climate change scenarios," Nature, Nature, vol. 416(6881), pages 626-629, April.
    • Handle: RePEc:nat:nature:v:416:y:2002:i:6881:d:10.1038_416626a
    DOI: 10.1038/416626a
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    Cited by:

    1. Junhua Hu & Zhigang Jiang, 2011. "Climate Change Hastens the Conservation Urgency of an Endangered Ungulate," PLOS ONE, Public Library of Science, vol. 6(8), pages 1-9, August.
    2. Weiyu Yu & Nicola A Wardrop & Robert E S Bain & Victor Alegana & Laura J Graham & Jim A Wright, 2019. "Mapping access to domestic water supplies from incomplete data in developing countries: An illustrative assessment for Kenya," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-19, May.
    3. Xiaojun Lyu & Haiqian Ke, 2022. "Dynamic Threshold Effect of Directed Technical Change Suppress on Urban Carbon Footprint in China," IJERPH, MDPI, vol. 19(9), pages 1-15, April.
    4. Iker Pardo & María P Pata & Daniel Gómez & María B García, 2013. "A Novel Method to Handle the Effect of Uneven Sampling Effort in Biodiversity Databases," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-9, January.
    5. Yañez-Arenas, Carlos & Guevara, Roger & Martínez-Meyer, Enrique & Mandujano, Salvador & Lobo, Jorge M., 2014. "Predicting species’ abundances from occurrence data: Effects of sample size and bias," Ecological Modelling, Elsevier, vol. 294(C), pages 36-41.
    6. Matt J. Michel & Huicheng Chien & Collin E. Beachum & Micah G. Bennett & Jason H. Knouft, 2017. "Climate change, hydrology, and fish morphology: predictions using phenotype-environment associations," Climatic Change, Springer, vol. 140(3), pages 563-576, February.
    7. Marco-Fondevila, Miguel & Álvarez-Etxeberría, Igor, 2023. "Trends in private sector engagement with biodiversity: EU listed companies' disclosure and indicators," Ecological Economics, Elsevier, vol. 210(C).
    8. Stankowski, Philippe A. & Parker, William H., 2011. "Future distribution modelling: A stitch in time is not enough," Ecological Modelling, Elsevier, vol. 222(3), pages 567-572.
    9. Nenzén, H.K. & Araújo, M.B., 2011. "Choice of threshold alters projections of species range shifts under climate change," Ecological Modelling, Elsevier, vol. 222(18), pages 3346-3354.
    10. Mahya Norallahi & Hesam Seyed Kaboli, 2021. "Urban flood hazard mapping using machine learning models: GARP, RF, MaxEnt and NB," 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. 106(1), pages 119-137, March.
    11. Dubravka Milić & Snežana Radenković & Dimitrije Radišić & Andrijana Andrić & Tijana Nikolić & Ante Vujić, 2019. "Stability and changes in the distribution of Pipiza hoverflies (Diptera, Syrphidae) in Europe under projected future climate conditions," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-19, September.
    12. Regina Gabriela Medina & Andrés Lira-Noriega & Ezequiel Aráoz & María Laura Ponssa, 2020. "Potential effects of climate change on a Neotropical frog genus: changes in the spatial diversity patterns of Leptodactylus (Anura, Leptodactylidae) and implications for their conservation," Climatic Change, Springer, vol. 161(4), pages 535-553, August.
    13. Acevedo, Pelayo & González-Quirós, Pablo & Prieto, José M. & Etherington, Thomas R. & Gortázar, Christian & Balseiro, Ana, 2014. "Generalizing and transferring spatial models: A case study to predict Eurasian badger abundance in Atlantic Spain," Ecological Modelling, Elsevier, vol. 275(C), pages 1-8.
    14. Growns, Ivor & West, Greg, 2008. "Classification of aquatic bioregions through the use of distributional modelling of freshwater fish," Ecological Modelling, Elsevier, vol. 217(1), pages 79-86.
    15. Edgard David Mason-Romo & Ariel A Farías & Gerardo Ceballos, 2017. "Two decades of climate driving the dynamics of functional and taxonomic diversity of a tropical small mammal community in western Mexico," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-25, December.
    16. 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.
    17. Soto-Montes-de-Oca, Gloria & Bark, Rosalind & González-Arellano, Salomón, 2020. "Incorporating the insurance value of peri-urban ecosystem services into natural hazard policies and insurance products: Insights from Mexico," Ecological Economics, Elsevier, vol. 169(C).
    18. Gobeyn, Sacha & Mouton, Ans M. & Cord, Anna F. & Kaim, Andrea & Volk, Martin & Goethals, Peter L.M., 2019. "Evolutionary algorithms for species distribution modelling: A review in the context of machine learning," Ecological Modelling, Elsevier, vol. 392(C), pages 179-195.
    19. 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.
    20. Coppée, Thomas & Paquet, Jean-Yves & Titeux, Nicolas & Dufrêne, Marc, 2022. "Temporal transferability of species abundance models to study the changes of breeding bird species based on land cover changes," Ecological Modelling, Elsevier, vol. 473(C).
    21. Cuevas-Carvajal, N. & Cortes-Ramirez, J.S. & Norato, Julian A. & Hernandez, C. & Montoya-Vallejo, M.F., 2022. "Effect of geometrical parameters on the performance of conventional Savonius VAWT: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    22. Buse, Jörn & Griebeler, Eva Maria, 2011. "Incorporating classified dispersal assumptions in predictive distribution models – A case study with grasshoppers and bush-crickets," Ecological Modelling, Elsevier, vol. 222(13), pages 2130-2141.
    23. Olivier, Frédérique & Wotherspoon, Simon J., 2008. "Nest selection by snow petrels Pagodroma nivea in East Antarctica," Ecological Modelling, Elsevier, vol. 210(4), pages 414-430.
    24. Daniel Zacarias & Rafael Loyola, 2019. "Climate change impacts on the distribution of venomous snakes and snakebite risk in Mozambique," Climatic Change, Springer, vol. 152(1), pages 195-207, January.

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