Abstract :
Eichhornia crassipes (water hyacinth) is one of the world’s most invasive aquatic plants, causing severe ecological and socio-economic impacts in freshwater ecosystems, including those of Côte d’Ivoire. This study aimed to assess the current and future distribution of E. crassipes in the wetlands of Côte d’Ivoire. Species occurrence data were compiled, and future distribution projections were generated under two Shared Socioeconomic Pathways (SSPs): SSP2-4.5 (intermediate stabilization scenario) and SSP5-8.5 (high greenhouse gas emission scenario) for the 2050 and 2070 time horizons. The results indicate that climate change is expected to substantially promote the expansion of E. crassipes across Côte d’Ivoire. Rising minimum temperatures (Bio6), identified as the primary determinant of the species’ distribution, together with changes in precipitation patterns, are projected to create highly suitable environmental conditions over most of the country by 2070. Depending on the climate scenario, the species’ potential suitable habitat could increase by a factor of 11 to 21, with no projected loss of currently suitable habitats. These findings highlight the urgent need to implement proactive prevention, monitoring, and management strategies, particularly in the central and northern regions of the country, which are currently free from invasion.
Keywords :
climate change, Côte d’Ivoire, Eichhornia Crassipes, species distribution, wetlandsReferences :
- Soubeyran, Y. 2008. Espèces exotiques envahissantes dans les collectivités françaises d’outre-mer -Etat des lieux et recommandations. Collection Planète Nature. Comité français de l’UICN, Paris, France, 2008, pp. 13.
- Bellard, C., Thuiller, W., Leroy, B., Genovesi, P., Bakkenes, M. and Courchamp, F. Will climate change promote future invasions? Global Change Biology, 19(12), 2013, pp. 3740-3748.
- Holm, L. G., Plucknett, D. L., Pancho, J. V. and Herberger, J. P. The world’s worst weeds: distribution and biology. University Press of Hawaii, Honolulu, 1977, pp. 609.
- Akinyeiji, A. The water hyacinth in the ecology of African aquatic systems. Aquatic Botany, 29(1), 1987, pp. 45-60.
- Harley, K. L. S. The potential for biological control of water hyacinth in Africa. Biological Control, 3(3), 1994, pp. 34-40.
- Yao, A. F., Amen, N. Y., Djala-lou-Dine, M., Achile, A. S. and Francois, T. A. Gestion de Eichhornia crassipes et leurs impacts sur la commu-nauté riveraine de Lomé au Togo. Revue Éco-systèmes et Paysages, 5(1), 2025, pp. 1-10. doi:https://doi.org/10.59384/recopays.tg5109
- Sucharit, S., Harinasuta, C., Deesin, T. and Vutikes, S. 1981. Studies of aquatic plants and grasses as breeding hosts for mosquitoes. Southeast Asian J Trop Med Public Health, 12, 1981, pp. 464-465.
- Dagno, K., Lahlali, R., Friel, D., Bajji, M. and Jijakli, M. H. Synthèse bibliographique : problématique de la jacinthe d’eau, Eichhornia crassipes, dans les régions tropicales et subtropicales du monde, notamment son éradication par la lutte biologique au moyen des phytopathogènes. Biotechnol. Agron. Soc. Environ., 11 (4), 2007, pp. 299-311.
- Lowe, S., Browne, M., Boudjelas, S. and De Poorter, M. 100 of the world’s worst invasive alien species: a selection from the Global Invasive Species Database. Invasive Species Specialist Group (ISSG), IUCN, 2000, pp. 12.
- Neuba, D. F. R., Malan, D. F., Koné, M., Kouadio, Y. L. Inventaire préliminaire des plantes envahissantes de la Côte d’Ivoire. Journal of Animal &Plant Sciences, 22 (2), 2014, pp. 3439-3445.
- org. GBIF Occurrence Download. https://www.gbif.org, 2024.
- Nicole, M., Egnankou, W. M. and Schmidt, M. Les zones humides côtières de Côte d’Ivoire. UICN, Gland, Suisse (ORSTOM–CI Nature/Univ. CI–UICN), 1987, pp. 73.
- Egnankou, W. M. Les végétaux aquatiques envahissants observés en Côte d’Ivoire. Document de Synthèse CIAPOL, 1995, pp. 10.
- Egnankou, W. M. Flore et végétation des zones humides du sud-est de la Côte d’Ivoire : problèmes de pollution et méthodes de lutte contre les Végétaux Aquatiques Envahissants (VAE). Thèse de Doctorat unique en Botanique, Université Félix Houphouet Boigny, Abidjan, Côte d’Ivoire, 235 p, 2015.
- Adou, L. M. D., Egnankou, W. M, Komoe, K., Adou Yao, C. Y., N’Guessan, K. E. Hydrophytes macrophytes de l’Est et du Sud-Est de la Côte d’Ivoire: Inventaire et quelques notes ethnobotaniques. Afri. Science, 12(4), 2016, pp. 282-291.
- Noba, K., Bassene, C., Ngom, A. et al. Invasive Plants of West Africa: Concepts, Overviews and Sustainable Management. Advances in Recycling & Waste Management, 2, 2017, pp. 121.
- Ouattara, M. S., Tiébré, M. S. and N’Guessan, K. E. Étude de la végétation d’un canal artificiel de navigation soumis aux pressions anthropiques, la rivière Assinie, Côte d’Ivoire. Afri. Science, 13(5), 2017, pp. 130-149.
- Almoustapha, O., Millogo-Rasolodimby, J. and Kenfack, S. Production de biogaz et de compost à partir de la jacinthe d’eau pour un développement durable en Afrique sahélienne. VertigO, 8(1), 2008, pp. 1-13.
- Villamagna, A. M. and Murphy, B. R. Ecological and socio-economic impacts of invasive water hyacinth (Eichhornia crassipes): a review. Freshwater biology, 55(2), 2010, pp. 282-298.
- Guiral, D. and Etien, N. Les macrophytes aquatiques des berges lagunaires. J. Ivolr. Océanol. IJmnol, 1(2), 1991, pp. 25-40.
- Etien, N. and Arfi, R. Macrophytes aquatiques dans les eaux continentales ivoiriennes. J. Ivoir. Océanol. Limnol, XV(2), 1996, pp. 19-38.
- Kouamé, K. V., Yapoga, S., Kouadio, K. N., Tidou, A. S. and Atsé, B. C. Phytoremédiation de la toxicité des eaux usées à l’aide de jacinthe d’eau (Eichhornia crassipes) et de laitue d’eau (Pistia stratiotes). Journal international de phytoremédiation, 18 (10), 2016, pp. 949-955. https://doi.org/10.1080/15226514.2016.1183567
- Nongbe, M. C., Kone, M., Diarra, M., Zamble, B. K. V. and Naki, G. J. Experimental assessment and modeling of heavy metal bioaccumulation by Eichhornia crassipes in mining-polluted waters of Côte d’Ivoire. Nature Environment and Pollution Technology, 25(2), 2026, pp. D1864. https://doi.org/10.46488/NEPT.2026.v25i02.D1864
- Kouamé, M. K., Dietoa, M. Y., Edia, E. O., Da Costa, S. K., Ouattara, A. and Gourène G. Macroinvertebrate communities associated with macrophyte habitats in a tropical man-made lake (Lake Taabo, Côte d’Ivoire). Knowledge and Management of Aquatic Ecosystems, 400, 2011, pp. 03. DOI: 10.1051/kmae/2010035
- Traore, K., Djaha, K. and Koffi, N. A. 2019. Analyse de la flore aquatique envahissante dans les plans d’eau de la ville de Daloa (Centre Ouest de la Côte d’Ivoire). J. Appl. Biosci., 142, 2019, pp. 14509-14518.
- Kriticos, D. J. and Brunel, Assessing and managing the current and future pest risk from water hyacinth (Eichhornia crassipes), an invasive aquatic plant threatening the environment and water security. PLoS ONE, 11(8), 2016, pp. e0120054.
- Recensement Général de la Population et de l’Habitat. Institut National de Statistique (INS). Rapport d’exécution et présentation des principaux résultats, Côte d’Ivoire, 2014, pp. 49.
- Eldin, M. 1971. Le climat de la Côte d’Ivoire. In : Le milieu naturel de Côte d’Ivoire. Mémoires ORSTOM, 50, Paris (France), 1971, pp. 73-108.
- Peel, M. C., Finlayson, B. L. and McMahon, T. A. Updated world map of the Köppen-Geiger climate classification. Hydrology and Earth System Sciences, 11(5), 2007, pp. 1633-1644.
- Perraud, A. Les sols. In : Le milieu naturel de la Côte d’Ivoire. Mémoire ORSTOM, Paris (France), 1971, pp. 57-263.
- A.O. World reference base for soil resources. A framework for international classification, correlation and communication. World soil resources reports 103, 2006.
- Zizka, A., Silvestro, D., Andermann, T. et al. CoordinateCleaner: Standardized cleaning of occurrence records from biological collection databases. Methods in Ecology and Evolution, 10(5), 2019, pp. 744-751.
- Aiello-Lammens, M. E., Boria, R. A., Radosavljevic, A., Vilela, B. and Anderson, R. P. SpThin: an R package for spatial thinning of species occurrence records for use in ecological niche models. Ecography, 38(5), 2015, pp. 541-545.
- Barbet-Massin, M., Jiguet, F., Albert, C. H. and Thuiller, W. Selecting pseudo-absences for species distribution models: how, where and how many? Methods in Ecology and Evolution, 3(2), 2012, pp. 327-338.
- Fick, S. E. and Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37(12), 2017, pp. 4302-4315.
- O’Donnell, M. S. and Ignizio, D. A. Bioclimatic predictors for supporting ecological applications in the conterminous United States. U.S. Geological Survey Data Series 691, 2012, pp. 10.
- Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. and Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25(15), 2005, pp. 1965-1978.
- Poggio, L., de Sousa, L. M., Batjes, N. H., Heuvelink, G. B. M., Kempen, B., Ribeiro, E. and Rossiter, D. SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty. Soil, 7(1), 2021, pp. 217-240.
- Naimi, B., Hamm, N. A. S., Groen, T. A., Skidmore, A. K., Toxopeus, A. G. 2014. Where is positional uncertainty a problem for species distribution modelling? Ecography, 37(2), 2014, pp. 191-203.
- Dormann, C. F., Elith, , Bacher, S. et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography, 36(1), 2013, pp. 27-46.
- Eyring, V., Bony, S., Meehl, G.A., Senior, C.A., Stevens, B., Stouffer, R. J. and Taylor, K. E. Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geoscientific Model Development, 9(5), 2016, pp. 1937-1958.
- Riahi, K., van Vuuren, D. P., Kriegler, E. et al. The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview. Global Environmental Change, 42, 2017, pp. 153-168.
- O’Neill, B. C., Tebaldi, C., van Vuuren, D. P. et al. The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geoscientific Model Development, 9(9), 2016, pp. 3461-3482.
- Thuiller, W., Guillera-Arroita, G., Mateo, R. G. and Araújo, M. B. Uncertainty in ensembles of global biodiversity scenarios. Nature Communications, 10(1), 2019, pp. 1146.
- Phillips, S. J., Anderson, R. P. and Schapire, R. E. Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190(3-4), 2006, pp. 231-259.
- Phillips, S. J. and Dudík, M. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography, 31(2), 2008, pp. 161-175.
- Breiman, L. Random forests. Machine Learning, 45(1), 2001, pp. 5-32.
- Liaw, A. and Wiener, M. Classification and regression by randomForest. R News, 2(3), 2002, pp. 18-22.
- Elith, J., Leathwick, J. R. and Hastie, T. A. working guide to boosted regression trees. Journal of Animal Ecology, 77(4), 2008, pp. 802-813.
- Ridgeway, G. Generalized Boosted Models: A guide to the gbm package. R package documentation, 2007, pp. 15.
- Hastie, T. J. and Tibshirani, R. J. Generalized Additive Models. Chapman & Hall, London, 1990, pp. 352.
- Wood, S. N. Generalized Additive Models: An Introduction with R (2nd ed.). Chapman and Hall/CRC, 2017, pp. 496 p.
- Thuiller, W., Lafourcade, B., Engler, R. and Araújo, M. B. BIOMOD-a platform for ensemble forecasting of species distributions. Ecography, 32(3), 2009, pp. 369-373.
- Thuiller, W., Georges, D., Gueguen, M., Engler, R., Breiner, F., Lafourcade, B. and Patin, R. biomod2: Ensemble Platform for Species Distribution Modeling. R package version 4.2., 2023.
- Araújo, M. B., New, M. 2007. Ensemble forecasting of species distributions. Trends in Ecology & Evolution, 22(1), 2007, pp. 42-47.
- Hao, T., Elith, J., Guillera-Arroita, G. and Lahoz-Monfort, J. J. A review of evidence about use and performance of species distribution modelling ensembles like BIOMOD. Diversity and Distributions, 25(5), 2019, pp. 839-852.
- Marmion, M., Parviainen, M., Luoto, M., Heikkinen, R. K. and Thuiller, W. Evaluation of consensus methods in predictive species distribution modelling. Diversity and Distributions, 15(1), 2009, pp. 59-69.
- Swets, J. A. Measuring the accuracy of diagnostic systems. Science, 240(4857), 1988, pp. 1285-1293.
- Fielding, A. H., Bell, J. F. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environmental Conservation, 24(1), 1997, pp. 38-49.
- Allouche, O., Tsoar, A. and Kadmon, R. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). Journal of Applied Ecology, 43(6), 2006, pp. 1223-1232.
- Elith, J., Ferrier, S., Huettmann, F. and Leathwick, J. The evaluation strip: a new and robust method for plotting predicted responses from species distribution models. Ecological Modelling, 186(3), 2005, pp. 280-289.
- Liu, C., White, M. and Newell, G. Selecting thresholds for the prediction of species occurrence with presence-only data. Journal of Biogeography, 40(4), 2013, pp. 778–789.
- Hijmans, R. J. Terra: Spatial Data Analysis. R package version 1.7, 2024, pp. 85.
- Pebesma, E. 2018. Simple Features for R: Standardized support for spatial vector data. The R Journal, 10(1), 2018, pp. 439-446.
- Hijmans, R. J., Phillips, S., Leathwick, J. and Elith, J. Dismo: Species Distribution Modeling. R package, 2023, pp. 100.
- Wickham, H. ggplot2: Elegant Graphics for Data Analysis (2nd ed.). Springer-Verlag, New York, 2016, pp. 211.
- Loarie, S. R., Duffy, P. B., Hamilton, H., Asner, G. P., Field, C. B. and Ackerly, D. D. The velocity of climate change. Nature, 462(7276), 2009, pp. 1052-1055.
- Hamann, A., Roberts, D. R., Barber, Q. E., Carroll, C., Nielsen, S. E. Velocity of climate change algorithms for guiding conservation and management. Global Change Biology, 21(2), 2015, pp. 997-1004.

