Boyle, T. H. & Anderson, E. in Cacti: Biology and Uses (ed. Nobel, P. S.) 125–141 (Univ. California Press, 2002).
Gibson, A. C. & Nobel, P. S. The Cactus Primer (Harvard Univ. Press, 1986).
Bravo Hollis, H. & Sánchez Mejorada, H. Las Cactáceas de México (Univ. Nacional Autónoma de México, 1978).
Goettsch, B. et al. High proportion of cactus species threatened with extinction. Nat. Plants 1, 15142 (2015).
Google Scholar
Benavides, E., Breceda, A. & Anadón, J. D. Winners and losers in the predicted impact of climate change on cacti species in Baja California. Plant Ecol. 222, 29–44 (2021).
Nobel, P. S. Responses of some North American CAM plants to freezing temperatures and doubled CO2 concentrations: implications of global climate change for extending cultivation. J. Arid. Environ. 34, 187–196 (1996).
Reyes-García, C. & Andrade, J. L. Crassulacean acid metabolism under global climate change. N. Phytol. 181, 754–757 (2009).
Smith, S. D., Didden-Zopfy, B. & Nobel, P. S. High-temperature responses of North American cacti. Ecology 65, 643–651 (1984).
Larios, E., González, E. J., Rosen, P. C., Pate, A. & Holm, P. Population projections of an endangered cactus suggest little impact of climate change. Oecologia 192, 439–448 (2020).
Google Scholar
Esparza-Olguı́n, L., Valverde, T. & Vilchis-Anaya, E. Demographic analysis of a rare columnar cactus (Neobuxbaumia macrocephala) in the Tehuacan Valley, Mexico. Biol. Conserv. 103, 349–359 (2002).
Seal, C. E. et al. Thermal buffering capacity of the germination phenotype across the environmental envelope of the Cactaceae. Glob. Change Biol. 23, 5309–5317 (2017).
Huang, J., Yu, H., Guan, X., Wang, G. & Guo, R. Accelerated dryland expansion under climate change. Nat. Clim. Change 6, 166–171 (2016).
Gurvich, D. E. et al. Combined effect of water potential and temperature on seed germination and seedling development of cacti from a mesic Argentine ecosystem. Flora 227, 18–24 (2017).
Nuzhyna, N., Baglay, K., Golubenko, A. & Lushchak, O. Anatomically distinct representatives of Cactaceae Juss. family have different response to acute heat shock stress. Flora 242, 137–145 (2018).
Andrade, J. L. & Nobel, P. S. Microhabitats and water relations of epiphytic cacti and ferns in a lowland neotropical forest. Biotropica 29, 261–270 (1997).
Williams, D. G., Hultine, K. R. & Dettman, D. L. Functional trade-offs in succulent stems predict responses to climate change in columnar cacti. J. Exp. Bot. 65, 3405–3413 (2014).
Google Scholar
Aragón-Gastélum, J. L. et al. Induced climate change impairs photosynthetic performance in Echinocactus platyacanthus, an especially protected Mexican cactus species. Flora Morphol. Distrib. Funct. Ecol. Plants 209, 499–503 (2014).
Martorell, C., Montañana, D. M., Ureta, C. & Mandujano, M. C. Assessing the importance of multiple threats to an endangered globose cactus in Mexico: cattle grazing, looting and climate change. Biol. Conserv. 181, 73–81 (2015).
Dávila, P., Téllez, O. & Lira, R. Impact of climate change on the distribution of populations of an endemic Mexican columnar cactus in the Tehuacán-Cuicatlán Valley, Mexico. Plant Biosyst. 147, 376–386 (2013).
Conver, J. L., Foley, T., Winkler, D. E. & Swann, D. E. Demographic changes over >70 yr in a population of saguaro cacti (Carnegiea gigantea) in the northern Sonoran Desert. J. Arid. Environ. 139, 41–48 (2017).
Carrillo-Angeles, I. G., Suzán-Azpiri, H., Mandujano, M. C., Golubov, J. & Martínez-Ávalos, J. G. Niche breadth and the implications of climate change in the conservation of the genus Astrophytum (Cactaceae). J. Arid. Environ. 124, 310–317 (2016).
de Cavalcante, A. M. B. & de Duarte, A. S. Modeling the distribution of three cactus species of the Caatinga biome in future climate scenarios. Int. J. Ecol. Environ. Sci. 45, 191–203 (2019).
de Cavalcante, A. M. B., de Duarte, A. S. & Ometto, J. P. H. B. Modeling the potential distribution of Epiphyllum phyllanthus (L.) Haw. under future climate scenarios in the Caatinga biome. An. Acad. Bras. Cienc. 92, 351–358 (2020).
Tellez-Valdes, O. & DiVila-Aranda, P. Protected areas and climate change: a case study of the cacti in the Tehuacan-Cuicatlan biosphere reserve, Mexico. Conserv. Biol. 17, 846–853 (2003).
dos Santos Simões, S., Zappi, D., da Costa, G. M., de Oliveira, G. & Aona, L. Y. S. Spatial niche modelling of five endemic cacti from the Brazilian Caatinga: past, present and future. Austral Ecol. 45, 1–13 (2019).
Gorostiague, P., Sajama, J. & Ortega-Baes, P. Will climate change cause spatial mismatch between plants and their pollinators? A test using Andean cactus species. Biol. Conserv. 226, 247–255 (2018).
Butler, C. J., Wheeler, E. A. & Stabler, L. B. Distribution of the threatened lace hedgehog cactus (Echinocereus reichenbachii) under various climate change scenarios. J. Torre. Bot. Soc. 139, 46–55 (2012).
Johnson, C. N. Species extinction and the relationship between distribution and abundance. Nature 394, 272–274 (1998).
Google Scholar
Thuiller, W., Lavorel, S. & Araújo, M. B. Niche properties and geographical extent as predictors of species sensitivity to climate change. Glob. Ecol. Biogeogr. 14, 347–357 (2005).
Enquist, B. J. Cyberinfrastructure for an integrated botanical information network to investigate the ecological impacts of global climate change on plant biodiversity. Preprint at PeerJ https://doi.org/10.7287/peerj.preprints.2615v2 (2016).
Buisson, L., Thuiller, W., Casajus, N., Lek, S. & Grenouillet, G. Uncertainty in ensemble forecasting of species distribution. Glob. Change Biol. 16, 1145–1157 (2010).
Thuiller, W., Guéguen, M., Renaud, J., Karger, D. N. & Zimmermann, N. E. Uncertainty in ensembles of global biodiversity scenarios. Nat. Commun. 10, 1446 (2019).
Google Scholar
Goettsch, B., Durán, A. P. & Gaston, K. J. Global gap analysis of cactus species and priority sites for their conservation. Conserv. Biol. 33, 369–376 (2018).
Google Scholar
Maitner, B. S. et al. The bien R package: A tool to access the Botanical Information and Ecology Network (BIEN) database. Methods Ecol. Evol. 9, 373–379 (2018).
Karger, D. N. et al. Climatologies at high resolution for the Earth’s land surface areas. Sci. Data 4, 170122 (2017).
Google Scholar
Sanderson, B. M., Knutti, R. & Caldwell, P. A representative democracy to reduce interdependency in a multimodel ensemble. J. Clim. 28, 5171–5194 (2015).
Brodzik, M. J., Billingsley, B., Haran, T., Raup, B. & Savoie, M. H. EASE-Grid 2.0: Incremental but significant improvements for Earth-gridded data sets. ISPRS Int. J. Geo-Inf. 1, 32–45 (2012).
Venter, O. et al. Global terrestrial human footprint maps for 1993 and 2009. Sci. Data 3, 160067 (2016).
Google Scholar
Phillips, S. maxnet: Fitting ‘maxent’ species distribution models with ‘glmnet’. R package version 0.1.4. https://CRAN.R-project.org/package=maxnet (2017).
Friedman, J., Hastie, T. & Tibshirani, R. Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw. 33, 1–22 (2010).
Google Scholar
Dormann, C. F. et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 27–46 (2013).
Franklin, S. B., Gibson, D. J., Robertson, P. A., Pohlmann, J. T. & Fralish, J. S. Parallel analysis: a method for determining significant principal components. J. Veg. Sci. 6, 99–106 (1995).
Roberts, D. R. et al. Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure. Ecography 40, 913–929 (2017).
Merow, C., Smith, M. J. & Silander, J. A. A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography 36, 1058–1069 (2013).
Allouche, O., Tsoar, A. & Kadmon, R. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 43, 1223–1232 (2006).
Calabrese, J. M., Certain, G., Kraan, C. & Dormann, C. F. Stacking species distribution models and adjusting bias by linking them to macroecological models. Glob. Ecol. Biogeogr. 23, 99–112 (2014).
R Core Team R: A Language and Environment for Statistical Computing Version 3.6.0 (R Foundation for Statistical Computing, 2019). https://www.R-project.org/
Source: Ecology - nature.com
