Climate change may favor the expansion of Adenium obesum in arid and semi-arid regions?

Keywords: Apocynaceae; invasive species; ecological niche modeling; desert rose.

Abstract

Future climate change may affect in the environmental suitability, which refers to the set of conditions necessary for a species to establish itself in a given ecosystem. The species Adenium obesum has a native distribution in desert regions, suggesting its adaptation to hot and arid climates. Thus, this study aimed to model the species environmental suitability for hot and dry climates, considering the premise of global temperature increase and the consequent possibility of expanding its distribution area. Occurrence data for Adenium obesum were obtained from the Global Biodiversity Information Facility (GBIF), while climate variables were sourced from the WorldClim database (version 2.1), with a spatial resolution of 5 arc-minutes. The modeling process employed the following algorithms: BRT, GAM, GLMPoly, MARS, MaxEnt, RF, and RPart. The models were evaluated using statistical metrics, considering those with AUC > 0.9 as potentially useful. For the True Skill Statistic (TSS) method, values above 0.7 were classified as good. To quantify, in km², the difference between the species' current potential distribution and the environmentally suitable areas projected for the future, the results were binarized, allowing the calculation of expansion, contraction, stability, and absence percentages. The future projections indicate an expansion of Adenium obesum, confirming the hypothesis that, due to its ecological and environmental characteristics, the species may achieve greater success in colonizing new areas under future climatic conditions characterized by higher temperatures and lower precipitation.

Downloads

Download data is not yet available.

References

Abreu, M. C. R. de, Valadares, N. R., Possobom, C. C. F., Mendes, R. B., & Nietsche, S. (2023). Selection of desert rose accessions with high ornamental potential. Ornamental Horticulture, 29(4), 481–489. https://doi.org/10.1590/2447-536X.v29i4.2668

Almeida, T. S., Almeida, R. P. S., & Fabricante, J. R. (2021). Climatic variables influence the richness, composition, and distribution of exotic invasive plants? Scientia Plena, 17(7), 1–17. https://doi.org/10.14808/sci.plena.2021.072401

Anselmetto, N., Weisberg, P. J., & Garbarino, M. (2024). Global change in the European Alps: A century of post-abandonment natural reforestation at the landscape scale. Landscape and Urban Planning, 243, 104973. https://doi.org/10.1016/j.landurbplan.2023.104973

Bedair, H., Shaltout, K., & Halmy, M. W. A. (2023). Stacked machine learning models for predicting species richness and endemism for Mediterranean endemic plants in the Mareotis subsector in Egypt. Plant Ecology, 224(11), 1113–1126. https://doi.org/10.1007/s11258-023-01366-6

Brown, S. H. (2012). Adenium obesum. University of Florida, IFAS Extension, Lee County. https://sfyl.ifas.ufl.edu/media/sfylifasufledu/lee/plant-selection/Adenium-obesum.pdf

Calcerrada, J. R., Chano, V., Matías, L., Hidalgo-Gálvez, M. D., Cambrollé, J., & Pérez-Ramos, I. M. (2022). Three years of warming and rainfall reduction alter leaf physiology but not relative abundance of an annual species in a Mediterranean savanna. Journal of Plant Physiology, 275, 153761. https://doi.org/10.1016/j.jplph.2022.153761

Cartereau, M., Leriche, A., Médail, F., & Baumel, A. (2023). Tree biodiversity of warm drylands is likely to decline in a drier world. Global Change Biology, 29(13), 3707–3722. https://doi.org/10.1111/gcb.16722

Cavalcante, A. M. B., Fernandes, P. H. C., & Silva, E. M. (2020). Opuntia ficus-indica (L.) Mill. and climate change: An analysis based on species distribution modeling in the Caatinga biome. Revista Brasileira de Meteorologia, 35(3), 375–385. https://doi.org/10.1590/0102-7786353001

Colombo, C. R., Cruz, M. A., Carvalho, D. U., Hoshino, R. T., Alves, G. A. C., & Faria, R. T. (2018). Adenium obesum as a new potted flower: Growth management. Ornamental Horticulture, 24(3), 197–205. https://doi.org/10.14295/oh.v24i3.1226

Díaz, S., Settele, J., Brondízio, E. S., Ngo, H. T., Agard, J., Arneth, A., Balvanera, P., Brauman, K. A., Butchart, S. H. M., Chan, K. M. A., Garibaldi, L. A., Ichii, K., Liu, J., Subramanian, S. M., Midgley, G. F., Miloslavich, P., Molnár, Z., Obura, D., Pfaff, A., Polasky, S., … & Zayas, C. (2019). Pervasive human-driven decline of life on Earth points to the need for transformative change. Science, 366(6471), eaax3100. https://doi.org/10.1126/science.aax3100

Fick, S. E., & Hijmans, R. J. (2017). WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37(12), 4302–4315. https://doi.org/10.1002/joc.5086

Giannini, T. C. (2012). Desafios atuais da modelagem preditiva de distribuição de espécies. Rodriguésia, 63(3), 733–749. https://doi.org/10.1590/S2175-78602012000300017

Henderson, A. F., Santoro, J. A., & Kremer, P. (2023). Impacts of spatial scale and resolution on species distribution models of American chestnut (Castanea dentata) in Pennsylvania, USA. Forest Ecology and Management, 529, 120741. https://doi.org/10.1016/j.foreco.2022.120741

Intergovernmental Panel on Climate Change (IPCC). (2023). Technical Summary. In Climate Change 2022 – Impacts, Adaptation and Vulnerability: Working Group II Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 37–118). Cambridge University Press.

Javeed, B., Ridwan, Q., Huang, D., Wani, Z. A., Siddiqui, S., Yassin, H. M., & Othman, G. A. M. (2024). Ecological niche modelling: A global assessment based on bibliometric analysis. Frontiers in Environmental Science, 12, 1376213. https://doi.org/10.3389/fenvs.2024.1376213

Konowalik, K., & Nosol, A. (2021). Evaluation metrics and validation of presence-only species distribution models based on distributional maps with varying coverage. Scientific Reports, 11(1), 1482. https://doi.org/10.1038/s41598-020-80062-1

Kufa, C. A., Bekele, A., & Atickem, A. (2022). Impacts of climate change on predicted habitat suitability and distribution of Djaffa Mountains Guereza (Colobus guereza gallarum, Neumann 1902) using MaxEnt algorithm in Eastern Ethiopian Highland. Global Ecology and Conservation, 35, e02094. https://doi.org/10.1016/j.gecco.2022.e02094

Lemos, R. P. M., Matielo, C. B. D., Marques Jr, A. S., Santos, M. G., Rosa, V. G., Sarzi, D. S., Rosa, J. V. S., & Stefenon, V. M. (2019). Ecological niche modeling of Schinus molle reveals the risk of invasive species expansion into biodiversity hotspots. Anais da Academia Brasileira de Ciências, 91(4), e20181047. https://doi.org/10.1590/0001-3765201920181047

Li, F., Hao, Q., Cui, X., Lin, R., Luo, B., & Ma, J. (2024). Global invasive alien plant management list: Assessing current practices and adapting to new demands. Plant Diversity. Advance online publication. https://doi.org/10.1016/j.pld.2024.11.002

Marco Júnior, P. de, & Nóbrega, C. C. (2018). Evaluating collinearity effects on species distribution models: An approach based on virtual species simulation. PLOS ONE, 13(9), e0202403. https://doi.org/10.1371/journal.pone.0202403

Menezes, I. S., Rocha, D. S. B., Funch, R. R., Couto-Santos, A. P. L., & Funch, L. S. (2021). Identification of priority areas for Eschweilera tetrapetala (Lecythidaceae) conservation in response to climate change. Rodriguésia, 72, 1–15. https://doi.org/10.1590/2175-7860202172073

Naimi, B. (2023). Package usdm: Uncertainty Analysis for Species Distribution Models (Version 2.1-7) [Software]. https://cran.r-project.org/web/packages/usdm/usdm.pdf

Oliveira, H. R., & Cassemiro, F. A. S. (2013). Potenciais efeitos das mudanças climáticas futuras sobre a distribuição de um anuro da Caatinga Rhinella granulosa (Anura, Bufonidae). Iheringia. Série Zoologia, 103(3), 272–279. https://doi.org/10.1590/S0073-47212013000300010

Osland, M. J., Chivoiu, B., Feher, L. C., Dale, L. L., Lieurance, D., Daniel, W. M., & Spencer, J. E. (2023). Plant migration due to winter climate change: Range expansion of tropical invasive plants in response to warming winters. Biological Invasions, 25(1), 2813–2830. https://doi.org/10.1007/s10530-023-03075-7

Oyen, L. P. A. (2006). Adenium obesum (Forssk.) Roem. & Schult. In G. H. Schmelzer & A. Gurib-Fakim (Eds.), Plant Resources of Tropical Africa (PROTA). PROTA Foundation. http://www.prota4u.org/

Parreira, M. R., Nabout, J. C., Tessarolo, G., Lima-Ribeiro, M. S., & Teresa, F. B. (2019). Disentangling uncertainties from niche modeling in freshwater ecosystems. Ecological Modelling, 391, 1–8. https://doi.org/10.1016/j.ecolmodel.2018.10.024

Pshegusov, R., Tembotava, F., Chadaeva, V., Sablirova, Y., Mollaeva, M., & Akhomgotov, A. (2022). Ecological niche modeling of the main forest-forming species in the Caucasus. Forest Ecosystems, 9, 100019. https://doi.org/10.1016/j.fecs.2022.100019

Santos, M. M., Costa, R. B., Cunha, P. P., & Seleguini, A. (2015). Tecnologias para produção de mudas de rosa do deserto (Adenium obesum). Multi-Science Journal, 1(3), 79–82. https://doi.org/10.33837/msj.v1i3.124

Sillero, N., Campos, J. C., Arenas-Castro, A., & Barbosa, A. M. (2023). A curated list of R packages for ecological niche modelling. Ecological Modelling, 476, 110242. https://doi.org/10.1016/j.ecolmodel.2022.110242

Shay, J. E., Pennington, L. K., Montiel-Molina, J. A. M., Toews, D. J., Hendrickson, B. T., & Sexton, J. P. (2021). Rules of plant species ranges: Applications for conservation strategies. Frontiers in Ecology and Evolution, 9, 700962. https://doi.org/10.3389/fevo.2021.700962

Smith, S. J., Edmonds, J., Hartin, C. A., Mundra, A., & Calvin, K. (2015). Near-term acceleration in the rate of temperature change. Nature Climate Change, 5(4), 333–336. https://doi.org/10.1038/nclimate2552

Soheili, F., Heydari, M., Woodwars, S., & Naji, H. R. (2023). Adaptive mechanism in Quercus brantii Lindl. leaves under climatic differentiation: Morphological and anatomical traits. Scientific Reports, 13(1), 3580. https://doi.org/10.1038/s41598-023-30762-1

Sunny, A., Marmolejo, C., Vidal-López, R., Falcon-Briones, F. A., Cuervo-Robayo, A. P., & Bolom-Huet, R. (2025). EcoNicheS: Enhancing ecological niche modeling, niche overlap and connectivity analysis using the shiny dashboard and R package. PeerJ, 13, e19136. https://doi.org/10.7717/peerj.19136

Tiwari, S., & Talreja, S. (2023). Exploring the mysterious Adenium obesum: Its botanical appeal, ecological significance, cultivation insights, and potential medicinal applications. Journal of Population Therapeutics and Clinical Pharmacology, 30(16), 687–694. https://doi.org/10.53555/jptcp.v30i16.2534

Van Kleunen, M., Dawson, W., Essl, F., Pergl, J., Inverno, M., Weber, E., Kreft, H., Weigelt, P., Kartesz, J., Nishino, M., Antonova, L. A., Barcelona, J. F., Cabezas, F. J., Cárdenas, D., Cárdenas-Toro, J., Castaño, N., Chacón, E., Chatelain, C., Ebel, A. L., Figueiredo, E., … & Pysek, P. (2015). Global exchange and accumulation of nonnative plants. Nature, 525(7567), 100–103. https://doi.org/10.1038/nature14910

Wani, I. A., Khan, S., Verma, S., Al-Misned, F. A., Shafik, H. M., & El-Serehy, H. A. (2022). Predicting habitat suitability and niche dynamics of Dactylorhiza hatagirea and Rheum webbianum in the Himalaya under projected climate change. Scientific Reports, 12(1), 13205. https://doi.org/10.1038/s41598-022-16837-5

Wan, J. Z., & Wang, C. J. (2018). Expansion risk of invasive plants in regions of high plant diversity: A global assessment using 36 species. Ecological Informatics, 46, 8–18. https://doi.org/10.1016/j.ecoinf.2018.04.004

Yang, J., Fu, Z., Xiao, K., Dong, H., Zhou, Y., & Zhan, Q. (2023). Climate change potentially leads to habitat expansion and increases the invasion risk of Hydrocharis (Hydrocharitaceae). Plants, 12(24), 4124. https://doi.org/10.3390/plants12244124

Yoon, S., & Lee, W. (2023). Application of true skill statistics as a practical method for quantitatively assessing CLIMEX performance. Ecological Indicators, 146, 109830. https://doi.org/10.1016/j.ecolind.2022.109830

Yu, B., Dai, W., Li, S., Wu, Z., & Wang, J. (2024). A new threshold selection method for species distribution models with presence-only data: Extracting the mutation point of the P/E curve by threshold regression. Ecology and Evolution, 14(4), e11208. https://doi.org/10.1002/ece3.11208

Zanin, M., Tessarolo, G., Machado, N., & Albernaz, A. L. M. (2017). Climatically-mediated landcover change: Impacts on Brazilian territory. Anais da Academia Brasileira de Ciências, 89(2), 701–714. https://doi.org/10.1590/0001-3765201720160226

Published
2026-04-02
How to Cite
Fleck, I. M., Oliveira, S. F. de, Fleck, L., Pontara, V., & Bueno, M. L. (2026). Climate change may favor the expansion of Adenium obesum in arid and semi-arid regions?. Acta Scientiarum. Biological Sciences, 48(1), e77535. https://doi.org/10.4025/actascibiolsci.v48i1.77535

 

0.6
2019CiteScore
 
 
31st percentile
Powered by  Scopus

 

 

0.6
2019CiteScore
 
 
31st percentile
Powered by  Scopus