Potential climate change induced modifications in mangrove ecosystems: a case study in Benin, West Africa

Corine Bitossessi Laurenda Sinsin (), Kolawolé Valère Salako, Adandé Belarmain Fandohan, Konan Edouard Kouassi, Brice Augustin Sinsin and Romain Glèlè Kakaï
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Corine Bitossessi Laurenda Sinsin: Université d’Abomey-Calavi
Kolawolé Valère Salako: Université d’Abomey-Calavi
Adandé Belarmain Fandohan: Université d’Abomey-Calavi
Konan Edouard Kouassi: Université Félix Houphouët-Boigny
Brice Augustin Sinsin: Université d’Abomey-Calavi
Romain Glèlè Kakaï: Université d’Abomey-Calavi

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2022, vol. 24, issue 4, No 19, 4917 pages

Abstract: Abstract Mangroves are one of the most threatened ecosystems globally. Likewise, they benefit many restoration efforts. However, these efforts have often disregarded potential effects of climate change on selected species and foreseen changes in physico-chemical conditions of mangrove ecosystems. This study aimed to model current and future climatic and physico-chemical conditions in occupied mangroves’ niche, in order to derive implications for successful long-term restorations. Presence records of mangroves’ indicator species and corresponding physico-chemical variables were collected. Bioclimatic data were obtained from Africlim. Kruskal–Wallis and Nemenyi pairwise tests for multiple comparisons were used to test the among sites (spatial) variations of climatic and physico-chemical variables within mangroves’ niche. Multiple linear regression (MLR) and artificial neural network (ANN) were used to build predictive models of salinity, dissolved oxygen, and conductivity; using most meaningful climatic variables to tropical mangroves—potential evapotranspiration, temperature seasonality, mean temperature of the warmest quarter, moister index of the moist quarter, and moister index of the driest quarter as predictors. Results showed that there are strong spatial variations of climatic and physico-chemical variables within mangroves’ niche. ANN outperformed MLR and was then used to predict trends in salinity, dissolved oxygen, and conductivity by year 2055. Based on foreseen trend in bioclimatic variables, conductivity, salinity, and dissolved oxygen will experiment significant changes under Representative Concentration Pathways 4.5 and 8.5, with most severe changes in case the later scenario occurs. Foreseen salinization of sites may be at the advantage of Avicennia germinans but to the prejudice of Rhizophora spp.

Keywords: Avicennia germinans; Rhizophora spp; Restoration; Representative concentration pathways; Physico-chemical; Predictive models (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10668-021-01639-y

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