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Using worldwide edaphic data to model plant species niches: An assessment at a continental extent

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  • Santiago José Elías Velazco
  • Franklin Galvão
  • Fabricio Villalobos
  • Paulo De Marco Júnior

Abstract

Ecological niche modeling (ENM) is a broadly used tool in different fields of plant ecology. Despite the importance of edaphic conditions in determining the niche of terrestrial plant species, edaphic data have rarely been included in ENMs of plant species perhaps because such data are not available for many regions. Recently, edaphic data has been made available at a global scale allowing its potential inclusion and evaluation on ENM performance for plant species. Here, we take advantage of such data and address the following main questions: What is the influence of distinct predictor variables (e.g. climatic vs edaphic) on different ENM algorithms? and what is the relationship between the performance of different predictors and geographic characteristics of species? We used 125 plant species distributed over the Neotropical region to explore the effect on ENMs of using edaphic data available from the SoilGrids database and its combination with climatic data from the CHELSA database. In addition, we related these different predictor variables to geographic characteristics of the target species and different ENM algorithms. The use of different predictors (climatic, edaphic, and both) significantly affected model performance and spatial complexity of the predictions. We showed that the use of global edaphic plus climatic variables generates ENMs with similar or better accuracy compared to those constructed only with climate variables. Moreover, the performance of models considering these different predictors, separately or jointly, was related to geographic properties of species records, such as number and distribution range. The large geographic extent, the variability of environments and the different species’ geographical characteristics considered here allowed us to demonstrate that global edaphic data adds useful information for plant ENMs. This is particularly valuable for studies of species that are distributed in regions where more detailed information on soil properties is poor or does not even exist.

Suggested Citation

  • Santiago José Elías Velazco & Franklin Galvão & Fabricio Villalobos & Paulo De Marco Júnior, 2017. "Using worldwide edaphic data to model plant species niches: An assessment at a continental extent," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-24, October.
    • Handle: RePEc:plo:pone00:0186025
    DOI: 10.1371/journal.pone.0186025
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    1. Pimenta, Mayra & Andrade, André Felipe Alves de & Fernandes, Fernando Hiago Souza & Amboni, Mayra Pereira de Melo & Almeida, Renata Silva & Soares, Ana Hermínia Simões de Bello & Falcon, Guth Berger &, 2022. "One size does not fit all: Priority areas for real world problems," Ecological Modelling, Elsevier, vol. 470(C).
    2. John M. Humphreys & Robert B. Srygley & David H. Branson, 2022. "Geographic Variation in Migratory Grasshopper Recruitment under Projected Climate Change," Geographies, MDPI, vol. 2(1), pages 1-19, January.
    3. Ebrahim Jahanshiri & Nur Marahaini Mohd Nizar & Tengku Adhwa Syaherah Tengku Mohd Suhairi & Peter J. Gregory & Ayman Salama Mohamed & Eranga M. Wimalasiri & Sayed N. Azam-Ali, 2020. "A Land Evaluation Framework for Agricultural Diversification," Sustainability, MDPI, vol. 12(8), pages 1-19, April.
    4. Ingrid Lana Lima de Morais & Alexandra Amaro de Lima & Ivinne Nara Lobato dos Santos & Carlos Meneses & Rogério Freire da Silva & Ricardo Lopes & Santiago Linorio Ferreyra Ramos & Ananda Virginia de A, 2024. "Climate Change Impact on the Distribution of Forest Species in the Brazilian Amazon," Sustainability, MDPI, vol. 16(8), pages 1-15, April.
    5. Dany A. Cotrina Sánchez & Elgar Barboza Castillo & Nilton B. Rojas Briceño & Manuel Oliva & Cristóbal Torres Guzman & Carlos A. Amasifuen Guerra & Subhajit Bandopadhyay, 2020. "Distribution Models of Timber Species for Forest Conservation and Restoration in the Andean-Amazonian Landscape, North of Peru," Sustainability, MDPI, vol. 12(19), pages 1-20, September.
    6. Munroe, Samantha & Guerin, Greg & Saleeba, Tom & Martín-Forés, Irene & Blanco-Martin, Bernardo & Sparrow, Ben & Tokmakoff, Andrew, 2020. "ausplotsR: An R package for rapid extraction and analysis of vegetation and soil data collected by Australia’s Terrestrial Ecosystem Research Network," EcoEvoRxiv 25phx, Center for Open Science.

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