Current and Future Potential Distribution of the Xerophytic Shrub Candelilla (Euphorbia antisyphilitica) under Two Climate Change Scenarios

被引:16
作者
Vargas-Piedra, Gonzalo [1 ]
Valdez-Cepeda, Ricardo David [2 ]
Lopez-Santos, Armando [1 ]
Flores-Hernandez, Arnoldo [1 ]
Hernandez-Quiroz, Nathalie S. [3 ]
Martinez-Salvador, Martin [3 ]
机构
[1] Univ Autonoma Chapingo, Unidad Reg Univ Zonas Aridas, Apdo Postal 8, Durango 35230, Mexico
[2] Univ Autonoma Chapingo, Ctr Reg Univ Norte Ctr, Apartado Postal 196, Zacatecas 98001, Zacatecas, Mexico
[3] Univ Autonoma Chihuahua, Fac Zootecnia & Ecol, Perifer Francisco R Almada Km 1, Chihuahua 31453, Chihuahua, Mexico
来源
FORESTS | 2020年 / 11卷 / 05期
关键词
species distribution; environmental change scenarios; candelilla spatial analysis; SPECIES DISTRIBUTION; MODELS; PREDICTION; MAXENT; WILDLIFE; HABITAT; IMPROVE; WAX; L;
D O I
10.3390/f11050530
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Candelilla (Euphorbia antisyphiliticaZucc.) is a shrub species distributed throughout the Chihuahuan Desert in northern Mexico and southern of the United States of America. Candelilla has an economic importance due to natural wax it produces. The economic importance and the intense harvest of the wax from candelilla seems to gradually reduce the natural populations of this species. The essence of this research was to project the potential distribution of candelilla populations under different climate change scenarios in its natural distribution area in North America. We created a spatial database with points of candelilla presence, according to the Global Biodiversity Information Facility (GBIF). A spatial analysis to predict the potential distribution of the species using Maxent software was performed. Thirteen of 19 variables from the WorldClim database were used for two scenarios of representative concentration pathways (RCPs) (4.5 as a conservative and 8.5 as extreme). We used climate projections from three global climate models (GCMs) (Max Planck institute, the Geophysical Fluid Dynamics Laboratory and the Met Office Hadley), each simulating the two scenarios. The final predicted distribution areas were classified in five on-site possible candelilla habitat suitability categories: none (< 19%), low (20-38%), medium (39-57%), high (58-76%) and very high (> 77%). According to the area under the curve (0.970), the models and scenarios used showed an adequate fit to project the current and future distribution of candelilla. The variable that contributed the most in the three GCMs and the two RCPs was the mean temperature of the coldest quarter with an influence of 45.7% (Jackknife test). The candelilla's distribution area for North America was predicted as approximately 19.1 million hectares under the current conditions for the high habitat suitability; however, the projection for the next fifty years is not promising because the GCMs projected a reduction of more than 6.9 million hectares using either the conservative or extreme scenarios. The results are useful for conservation of the species in the area with vulnerable wild populations, as well as for the selection of new sites suitable for the species growth and cultivation while facing climate change.
引用
收藏
页数:15
相关论文
共 64 条
  • [11] Species Distribution Models: Ecological Explanation and Prediction Across Space and Time
    Elith, Jane
    Leathwick, John R.
    [J]. ANNUAL REVIEW OF ECOLOGY EVOLUTION AND SYSTEMATICS, 2009, 40 : 677 - 697
  • [12] Potential distribution and abundance of candelilla (Euphorbia antisyphilitica) in northern Zacatecas, Mexico
    Enrique Banuelos-Revilla, Jose
    Palacio-Nunez, Jorge
    Felipe Martinez-Montoya, Juan
    Olmos-Oropeza, Genaro
    Alberto Flores-Cano, Jorge
    [J]. MADERA Y BOSQUES, 2019, 25 (01):
  • [13] Fernandez-Eguiarte A., 2010, ATLAS CLIMATICO DIGI, V1, P2
  • [14] A review of methods for the assessment of prediction errors in conservation presence/absence models
    Fielding, AH
    Bell, JF
    [J]. ENVIRONMENTAL CONSERVATION, 1997, 24 (01) : 38 - 49
  • [15] Flores-del Angel ML, 2013, PHYTON-INT J EXP BOT, V82, P161
  • [16] Garcia E., 2004, MODIFICACIONES SISTE, V1
  • [17] Modelling species distributions with penalised logistic regressions: A comparison with maximum entropy models
    Gaston, Aitor
    Garcia-Vinas, Juan I.
    [J]. ECOLOGICAL MODELLING, 2011, 222 (13) : 2037 - 2041
  • [18] GBIF, 2019, OCC DOWNL
  • [19] Giordani L., 2008, ROLE GOATS GERMINATI, V1, P24
  • [20] Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5
    Giorgetta, Marco A.
    Jungclaus, Johann
    Reick, Christian H.
    Legutke, Stephanie
    Bader, Juergen
    Boettinger, Michael
    Brovkin, Victor
    Crueger, Traute
    Esch, Monika
    Fieg, Kerstin
    Glushak, Ksenia
    Gayler, Veronika
    Haak, Helmuth
    Hollweg, Heinz-Dieter
    Ilyina, Tatiana
    Kinne, Stefan
    Kornblueh, Luis
    Matei, Daniela
    Mauritsen, Thorsten
    Mikolajewicz, Uwe
    Mueller, Wolfgang
    Notz, Dirk
    Pithan, Felix
    Raddatz, Thomas
    Rast, Sebastian
    Redler, Rene
    Roeckner, Erich
    Schmidt, Hauke
    Schnur, Reiner
    Segschneider, Joachim
    Six, Katharina D.
    Stockhause, Martina
    Timmreck, Claudia
    Wegner, Joerg
    Widmann, Heinrich
    Wieners, Karl-H
    Claussen, Martin
    Marotzke, Jochem
    Stevens, Bjorn
    [J]. JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS, 2013, 5 (03) : 572 - 597