Predicting Climate Change Impacts on Candelilla (Euphorbia antisyphilitica Zucc.) for Mexico: An Approach for Mexico’s Primary Harvest Area

Candelilla (Euphorbia antisyphilitica Zucc.) is a non-timber forest resource of ecological and economic importance in the arid zones of Mexico due to the commercialization of its wax for industrial purposes. The objectives of this study were (i) to delimit areas of current and projected future candelilla habitat suitability in Mexico and in the state of Coahuila, (ii) to determine the most important variables that define candelilla habitat, and (iii) to propose areas for candelilla conservation under climate change conditions in Coahuila. Records of candelilla presence, current and future bioclimatic layers from the MPIESM-LR and HadGEM2-ES models with two scenarios RCP 4.5 and 8.5, were used to create species distribution models with soil and topographical variables. MaxEnt software was used to project current habitat suitability zones under climate change. We estimated the current surface area of candelilla in Mexico to be 79,336.87 km2, and for Coahuila 25,620.75 km2. In Coahuila, using the MPIESM-LR model for 2050, the estimate was 20,177.67 km2 and 17,079.61 km2 for RCP scenarios 4.5 and 8.5; while for 2070, the estimate was 12,487.18 km2 and 9812.94 km2 for RCP scenarios 4.5 and 8.5. For the HadGEM2-ES model for 2050, the estimate was 20,066.40 km2 and 17,079.61 km2; for 2070 it was 17,156.02 km2 and 16,073.70 km2. As proposed areas for conservation of candelilla in the face of climate change, we estimated 5435.06 km2 and 3636.96 km2. The study area was located in the northwest and center of the state of Coahuila, near the natural protected areas of Ocampo and Bajo Rio San Juan, areas that are resilient to climate change. The results obtained provide information on the environmental and site conditions for the establishment of candelilla in Mexico, as well as the geographical areas, such as Sierra y Cañon de Jimulco, Tomás Garrido, 026 Bajo Río San Juan, Zapalinamé, Zapalinamé, and Cumbres de Monterrey Restoration Zones for the conservation of the species under local climate change scenarios. In addition, new areas in the northwest and center of Coahuila could be used to establish new protected areas for this economically important species.

[1]  A. R. Martínez-Sifuentes,et al.  Climate Change Impact on the Habitat Suitability of Pseudotsuga menziesii Mirb. Franco in Mexico: An Approach for Its Conservation , 2022, Sustainability.

[2]  A. Moreno-Reséndez,et al.  Distribución potencial de Euphorbia antisyphilitica Zucc. en México , 2020 .

[3]  M. Martínez-Salvador,et al.  Current and Future Potential Distribution of the Xerophytic Shrub Candelilla (Euphorbia antisyphilitica) under Two Climate Change Scenarios , 2020, Forests.

[4]  J. L. Becerra-López,et al.  Spatial modeling of the ecological niche of Pinus greggii Engelm. (Pinaceae): a species conservation proposal in Mexico under climatic change scenarios , 2020, iForest - Biogeosciences and Forestry.

[5]  C.N. Aguilar,et al.  PASADO, PRESENTE Y FUTURO DE LA CANDELILLA , 2019, Revista Mexicana de Ciencias Forestales.

[6]  Jonathan Hernández Ramos,et al.  Similaridad del nicho ecológico de Pinus montezumae y P. pseudostrobus (Pinaceae) en México: implicaciones para la selección de áreas productoras de semillas y de conservación , 2018, Acta Botánica Mexicana.

[7]  Stephen E. Fick,et al.  WorldClim 2: new 1‐km spatial resolution climate surfaces for global land areas , 2017 .

[8]  M. Lonati,et al.  Species-rich Nardus stricta grasslands host a higher vascular plant diversity on calcareous than on siliceous bedrock , 2017 .

[9]  Eduardo Estrada-Castillón,et al.  El elemento endémico de la flora vascular del Desierto Chihuahuense , 2017 .

[10]  J.G.B. Leenaars,et al.  WoSIS: providing standardised soil profile data for the world , 2016 .

[11]  G. Cruz-Cárdenas,et al.  Potential distribution model of Pinaceae species under climate change scenarios in Michoacán , 2016 .

[12]  Juan Manuel Ortega-Rodríguez,et al.  Pinus leiophylla suitable habitat for 1961-1990 and future climate , 2015 .

[13]  Kenton O'Hara,et al.  Scientists and software – surveying the species distribution modelling community , 2015 .

[14]  J. C. de Almeida,et al.  Concluding Remarks , 2015, Clinical practice and epidemiology in mental health : CP & EMH.

[15]  Robert A. Boria,et al.  ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models , 2014 .

[16]  S. Varela,et al.  Macroecología y ecoinformática: sesgos, errores y predicciones en el modelado de distribuciones , 2014 .

[17]  Robert P. Anderson,et al.  Estimating optimal complexity for ecological niche models: A jackknife approach for species with small sample sizes , 2013 .

[18]  Matthew J. Smith,et al.  Protected areas network is not adequate to protect a critically endangered East Africa Chelonian: Modelling distribution of pancake tortoise, Malacochersus tornieri under current and future climates , 2013, bioRxiv.

[19]  Chun-Ho Cho,et al.  Climate change in the 21st century simulated by HadGEM2-AO under representative concentration pathways , 2013, Asia-Pacific Journal of Atmospheric Sciences.

[20]  B. Stevens,et al.  Climate and carbon cycle changes from 1850 to 2100 in MPI‐ESM simulations for the Coupled Model Intercomparison Project phase 5 , 2013 .

[21]  M. Mandujano,et al.  The Consequences of Harvesting on Regeneration of a Non-timber Wax Producing Species (Euphorbia antisyphilitica Zucc.) of the Chihuahuan Desert , 2013, Economic Botany.

[22]  C. Jones,et al.  The HadGEM2 family of Met Office Unified Model climate configurations , 2011 .

[23]  A. Peterson Ecological niche conservatism: a time‐structured review of evidence , 2011 .

[24]  Dan L Warren,et al.  Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria. , 2011, Ecological applications : a publication of the Ecological Society of America.

[25]  M. A. Inzunza-Ibarra,et al.  Producción de plántulas de Candelilla (Euphorbia antisyphilitica Zucc.) mediante estacas , 2010 .

[26]  Cristóbal N. Aguilar,et al.  Edible film based on candelilla wax to improve the shelf life and quality of avocado , 2009 .

[27]  Miroslav Dudík,et al.  Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation , 2008 .

[28]  R. Real,et al.  AUC: a misleading measure of the performance of predictive distribution models , 2008 .

[29]  A. Peterson,et al.  Environmental data sets matter in ecological niche modelling: an example with Solenopsis invicta and Solenopsis richteri. , 2007 .

[30]  A. Townsend Peterson,et al.  Novel methods improve prediction of species' distributions from occurrence data , 2006 .

[31]  Robert P. Anderson,et al.  Maximum entropy modeling of species geographic distributions , 2006 .

[32]  A. Peterson,et al.  INTERPRETATION OF MODELS OF FUNDAMENTAL ECOLOGICAL NICHES AND SPECIES' DISTRIBUTIONAL AREAS , 2005 .

[33]  David R. B. Stockwell,et al.  Effects of sample size on accuracy of species distribution models , 2002 .

[34]  J. Rzedowski Diversidad y orígenes de la flora fanerogámica de México. , 1991 .

[35]  M. Maccracken,et al.  The Use of General Circulation Models to Predict Regional Climatic Change , 1991 .

[36]  Patricia Illoldi-Rangel,et al.  Ecological niche modeling under climate change to select shrubs for ecological restoration in Central Mexico , 2015 .

[37]  R. R. Chilpa,et al.  Productos forestales no maderables en México: Aspectos económicos para el desarrollo sustentable , 2008 .

[38]  J. Flores,et al.  GERMINATION AND EARLY GROWTH TRAITS OF 14 PLANT SPECIES NATIVE TO NORTHERNMEXICO , 1998 .

[39]  G. Webster Synopsis of the Genera and Suprageneric Taxa of Euphorbiaceae , 1994 .

[40]  Trevor H. Booth,et al.  Niche analysis and tree species introduction , 1988 .