iForest - Biogeosciences and Forestry


Spatial modeling of the ecological niche of Pinus greggii Engelm. (Pinaceae): a species conservation proposal in Mexico under climatic change scenarios

Aldo Rafael Martínez-Sifuentes (1), José Villanueva-Díaz (1)   , Ulises Manzanilla-Quiñones (2), Jorge Luis Becerra-López (3), José Antonio Hernández-Herrera (4), Juan Estrada-Ávalos (1), Adín Helbert Velázquez-Pérez (5)

iForest - Biogeosciences and Forestry, Volume 13, Issue 5, Pages 426-434 (2020)
doi: https://doi.org/10.3832/ifor3491-013
Published: Sep 16, 2020 - Copyright © 2020 SISEF

Research Articles

Pinus greggii is a species of socio-economic importance in terms of wood production and environmental services in Mexico, though it is restricted by particular environmental conditions to the Sierra Madre Occidental. Species distribution models are geospatial tools widely used in the identification and delineation of species’ distribution areas and zones susceptible to climate change. The objectives of this study were to: (i) model and quantify the environmentally suitable area for Pinus greggii in Mexico, and possible future distributions under four different scenarios of climate change; (ii) identify the most relevant environmental variables that will possibly drive changes in future distribution; and (iii) to propose adequate zones for the species’ conservation in Mexico. Some 438 records of Pinus greggii from several national and international databases were obtained, and duplicates were discarded to avoid overestimations in the models. Climatic, edaphic, and topographic variables were used and 100 distribution models for current and future scenarios were generated using the Maxent software. The best model had an area under the curve (AUC) of 0.88 and 0.93 for model training and validation, respectively, a partial ROC of 1.94, and a significant Z test (p<0.01). The current estimated suitable area of Pinus greggii in Mexico was 617.706.04 ha. The most relevant environmental variables for current distribution were annual mean temperature, mean temperature of coldest quarter, and slope. For the 2041-2060 models, annual mean temperature, precipitation of coldest quarter, and slope were the most important drivers. The use of climatic models allowed to predict a future decrease in suitable habitat for the species by 2041-2060, ranging from 48.403.85 (7.8% - HadGEM2-ES RCP 8.5 model) to 134.680.17 ha (21.8% - CNRM-CM5 RCP 4.5). Spatial modeling of current and future ecological niche of Pinus greggii also allowed to delineate two zones for in situ conservation and restoration purpose in northeastern (Nuevo Leon) and central (Hidalgo) Mexico.


Conservation, Climate Change, MaxEnt, Sierra Madre Oriental, Pinus greggii

Authors’ address

Aldo Rafael Martínez-Sifuentes 0000-0002-1157-8647
José Villanueva-Díaz
Juan Estrada-Ávalos 0000-0001-5345-459X
Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, Centro Nacional de Investigación Disciplinaria en Relación Agua, Suelo, Planta, Atmósfera, Gómez Palacio, Durango (México)
Ulises Manzanilla-Quiñones 0000-0001-9988-7577
Facultad de Ciencias Forestales, Universidad Autónoma de Nuevo León, Linares, Nuevo León (México)
Jorge Luis Becerra-López 0000-0003-4510-5052
Facultad de Ciencias Biológicas, Universidad Juárez del Estado de Durango, Gómez Palacio, Durango (México)
José Antonio Hernández-Herrera 0000-0002-1664-3380
Universidad Autónoma Agraria Antonio Narro, Unidad Saltillo, Saltillo, Coahuila (México)
Adín Helbert Velázquez-Pérez 0000-0002-0596-2706
Facultad de Ciencias Forestales. Colegio de Postgraduados, Montecillos, Texcoco (México)

Corresponding author

José Villanueva-Díaz


Martínez-Sifuentes AR, Villanueva-Díaz J, Manzanilla-Quiñones U, Becerra-López JL, Hernández-Herrera JA, Estrada-Ávalos J, Velázquez-Pérez AH (2020). Spatial modeling of the ecological niche of Pinus greggii Engelm. (Pinaceae): a species conservation proposal in Mexico under climatic change scenarios. iForest 13: 426-434. - doi: 10.3832/ifor3491-013

Academic Editor

Maurizio Marchi

Paper history

Received: May 04, 2020
Accepted: Jul 08, 2020

First online: Sep 16, 2020
Publication Date: Oct 31, 2020
Publication Time: 2.33 months

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