Document Type: Original Article

Authors

1 Agronomy Faculty, Autonomous University of Sinaloa, Sinaloa, Mexico

2 Agriculture and Livestock Department (DAG), University of Sonora, Bahía Kino Highway Km 18.5. 83000 Hermosillo, Sonora, México

3 Geomatics Lab., National Institute of Research for Forestry Agricultural and Livestock (INIFAP). Zinacantepec 51350, Mexico

4 Department of Environmental Sciences, Faculty of Agriculture and Natural Resources, Arak University, Arak, Iran

Abstract

Based on different climatic scenarios, the distribution of the Olneya tesota A. Gray (Ironwood) has been modeled using MaxEnt modeling approach in the Sonora State of Mexico. Maximum Entropy species Distribution Modeling was used to predict distribution probability. 71,168 presence data and BIO1 to BIO19 variables of Worldclim BIOCLIM dataset for the present time, 2050 and 2070 used for modeling. The model performed with an acceptable range of sensitivity for training data (AUC=0.927) and random prediction (AUC=0.5). The results demonstrated that the high contributed variable on the presence of the O. tesota A. Gray is BIO17  Precipitation of Driest Quarter (48.3%) and the low contributed variable is BIO2=Mean Diurnal Range (Mean of monthly (max temp - min temp)) (0.9%). This means that the presence of the species is highly depended on dry months precipitation of which doesn’t have high fluctuations according to the used climate change scenario. Temperature fluctuations have not affected O. tesota A. Gray presence as it is known as a resistant species for extremely high temperatures. Therefore the probability of the presence of the species shows a significant increase on high altitudes mountains on the north-east of the Sonora state. Finally, the study concludes that the climate change will affect the distribution of the O. tesota A. Gray as an extinction risk and the same time will help the expansion of the species presence probability on the region. And it has been encountered new regions to recommend this valuable species as a reforestation alternative for conservation and management strategy like Soyopa, Aguaprieta and Sahuaripa municipalities among the others.

Keywords

Barja I. Silván G. Rosellini S. Piñeiro A. Araújo M. B., Pearson R.G., Thuiller W., Erhard M. 2005. Validation of species – climate impact models under climate change. Global Change Biology 11(9):1504–1513.

Austin M. 2007. Species distribution models and ecological theory: A critical assessment and some possible new approaches. Ecological Modelling 200(1-2), pp.1–19.

Cole K.L. 1986. The lower Colorado River Valley: A Pleistocene desert. Quaternary Research 25(3): 392–400.

Elia J.D., Haig M.S., Johnson Matthew., Marcot G.B., Young R., 2015. Activity-specific ecological niche models for planning reintroductions of California condors (Gymnogyps californianus). Biological Conservation 184: 90–99.

Elith J., Phillips S.J., Hastie T., Dudík M., Chee Y.E., Yates C.J. 2011. A statistical explanation of MaxEnt for ecologists. Diversity and Distributions 17(1): 43–57.

Khanum R., Mumtaz A.S. Kumar S. 2013. Predicting impacts of climate change on medicinal Asclepiades of Pakistan using MaxEnt modeling. Acta Oecologica 49: 23–31.

Leão T.C.C., Fonesca R.C., Peres A.C., Tabarelli M. 2014. Predicting extinction risk of Brazilian Atlantic forest angiosperms. Conservation Biology 1(1): 1–11.

Martin C.A., Mcdowell L.B. 1999. Seasonal Effects on Growth of O. tesota following Root Pruning 337 Determining Suitable Chilling Conditions for Deciduous Fruit Trees in Iraq. Horticulture science 34(3).

Martínez-Yrízar A., Núñez S., Búrquez A. 2007. Leaf litter decomposition in a southern Sonoran Desert ecosystem, northwestern Mexico: Effects of habitat and litter quality. Acta Oecologica 32(3): 291–300

Matyukhina D.S., Miquelle G.D., Murzin AA., Pikunov G.D., Aramilev V.V., Litvinov N.M., Salkina P.G., Seryodkin V.I., Nikolaev G.I., Kostyria V.A., Gaponov V.V., Yudin G.V., Dunishenko M.Y., Smirnov N.E., Korkishko G.V., Marino J. 2015. Assessing the Influence of Environmental Parameters on Amur Tiger Distribution in the Russian Far East Using a MaxEnt Modeling Approach. Achievements in the Life Sciences, Available at: http://www.sciencedirect.com/science/article/pii/.

Medeiros A.S., Drezner T.D. 2012. Vegetation, Climate, and Soil Relationships Across the Sonoran Desert. Ecoscience 19(2), 148–160.

Meza-Rangel E., Tafoya F., Lindig-Cisneros R., Jesús Sigala-Rodríguez J., Pérez-Molphe-Balch, E. 2024. Distribución actual y potencial de las cactáceas Ferocactus histrix, Mammillaria bombycina y M. perezdelarosae en el estado de Aguascalientes, México. Acta Botanica Mexicana 108: 67–80.

Pearson R.G., Stanton J.C., Shoemaker K.T., Aiello-Lammens M.E., Ersts P.J., Horning N.F., Damien A.R., Ryu J.Ch., Yeong H., Jason M., Resit H.A. 2014. Life history and spatial traits predict extinction risk due to climate change. Nature Climate Change, 4(3): 217–221.

Peterson AT., Soberón J., Krishtalka L. 2015. A global perspective on decadal challenges and priorities in biodiversity informatics. BMC Ecology 15(1).

Peterson A.T., Ortega-Huerta M.A., Bartley J., Sanchez-Cordero V., Soberon J., Buddemeier R. H., Stockwell D.R.B. 2002. Future projections for Mexican faunas under global climate change scenarios. Nature 416(6881): 626–629.

Phillips S.J., Anderson R.P., Schapire R.E. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modeling 190(3–4): 231–259.

Salvador M.M., Rojas D.E. H., Saúl A., Guerrero M., Amparan J.A.P. (n.d.). Potencial productivo y zonificación para el uso y manejo de especies forestales de zonas aridas.

Shupe S.M. 2005. Multivariate characterization of Sonoran Desert vegetation in southwest Arizona using US Army field data. Plant Ecology 176(2): 215–235.

Shupe S.M., Marsh S.E. 2004. Cover and density-based vegetation classifications of the Sonoran Desert using Landsat TM and ERS-1 SAR imagery. Remote Sensing of Environment 93(1–2): 131–149.

Suzán H., Nabhan G.P., Patten, D. T. (1996). The importance of O. tesota as a nurse plant in the Sonoran Desert. Journal of Vegetation Science 7(5): 635–644.

Suzán H., Patten D.T., Nabhan G.P. 1997. Exploitation and conservation of Ironwood

(O. tesota) in the Sonoran desert. Ecological Applications 7(3): 948–957.

Suzan-Azpiri H.  1994.  Ecological   effects  of exploitation on O. tesota Gray and associated species in the Sonoran Desert. ProQuest Dissertations and Theses.

Suzán-Azpiri H. Sosa V.J. 2006. Comparative performance of the giant cardon cactus (Pachycereus pringlei) seedlings under two leguminous nurse plant species. Journal of Arid Environments 65(3): 351–362.

Thomas C.D., Cameron A., Green R.E., Bakkenes M., Beaumont L.J., Collingham Y.C., Erasmus B.F.N., Ferreira de Siqueira M., Grainger A., Hannah L., Hughes L., Huntley B., Van Jaarsveld A.S., Midgley G.F., Miles L., Ortega-Huerta, M.A. Townsend Peterson A., Philips O.L. and Williams S.E. 2004. Climate change and extinction risk, Nature 427(6970): 145–148.

Vásquez-méndez R., Ventura-ramos E., Domínguez-cortázar M.A. 2008. Soil Erosion Processes in Semiarid Areas Book The Importance of Native Vegetation.

Verónica S., Humberto S. 2014. Análisis de la distribución espacial del muérdago (Phoradendron californicum) en el sur del Desierto Sonorense. Cact suc Mex 59(1):11–28.

Walker S. 2014. Applying Extinction Risk Modelling to Develop Global Conservation Priorities for Bulbous Monocots. Thesis, 65p Imperial College London University library.

Zuñiga-Tovar B., Suzán-Azpiri H. 2010. Comparative population analysis of desert ironwood (Olneya tesota) in the Sonoran Desert. Journal of Arid Environments 74(2): 173–178.