EGU2020-9054
https://doi.org/10.5194/egusphere-egu2020-9054
EGU General Assembly 2020
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Quantitative land-cover change in West Africa over the Holocene: case study in Cameroon

Esther Githumbi1, Marie-Jose Gaillard1, Anne-Marie Lezine2, Gaston Achoundong3, Christelle Hély4, Judicael Lebamba5, Laurent Marquer6, Florence Mazier7, and Shinya Sugita8
Esther Githumbi et al.
  • 1Linnaeus University, Department of Biology and Environmental Science, Sweden (esther.githumbi@lnu.se)
  • 2Laboratoire d’Océanographie et du Climat, Expérimentation et Approche Numérique/IPSL, Sorbonne Université, CNRS-IRD-MNHN, Paris, France
  • 3National Herbarium, IRAD, Yaoundé, Cameroon
  • 4Institut des Sciences de l'Evolution de Montpellier, Université de Montpellier, France
  • 5Département de Biologie, Université des Sciences et Techniques de Masuku, Franceville, Gabon
  • 6Research Group for Terrestrial Palaeoclimates, Max Planck Institute for Chemistry, Mainz, Germany
  • 7GEODE, UMR-CNRS 5602, Labex DRIIHM (OHM Pyrénées Haut Vicdessos), Université Toulouse Jean Jaurès, France
  • 8Institute of Ecology, Tallinn University, Estonia

Currently interaction between climate and land-cover change in the past across the globe, and whether drivers are anthropogenic or natural are among the biggest debates. The impacts of climate and land-cover change are having significant consequences on biodiversity and ecosystems. Wide ranging palaeoenvironmental methods have contributed to this debate by providing long-term records of both climate and land-cover change. This provide the context for evaluating the effect of land-cover change on climate.  Inferred past land-cover and climate change from palaeoecological proxies therefore need to be quantified to provide reliable estimates of change; there are several methods of quantifying land-cover change in the past of which the Landscape Reconstruction Algorithm (LRA)  can estimate past land-cover change quantitatively at both regional and local spatial scales using fossil pollen records. The LRA includes two models (REVEALS and LOVE) and has already been tested and validated in Europe, North America, and China.

In this study, we apply the LRA on Holocene pollen records in Cameroon to estimate past land-cover change. This is the first pollen-based, quantitative land-cover reconstruction using LRA in Africa.  It will provide a comparison with land-cover change described from raw pollen data and useful information for climate modelling. The first phase involved the estimation of relative pollen productivity (RPP) for 13 taxa using the pollen-vegetation relationship described by the ERV model. The second phase involves the application of LRA using the RPPs from the 13 taxa.

 

 Acknowledgements: We thank the French ANR (National Research Agency; projects C3A ANR-09-PEXT-001 and VULPES ANR-15-MASC-0003) and the Belgian project BR/132/A1/AFRIFORD for financial support, IRD (France) and the Ministry of Research and National Herbarium of Cameroon for research facilities and authorizations, and A. Vincens, J.-P. Cazet, G. Buchet, L. Février, and K. Lemonnier (CNRS) for laboratory and field assistance. The study is a contribution to PAGES LandCover6k (www.pastglobalchanges.org/ini/wg/landcover6k/intro).

How to cite: Githumbi, E., Gaillard, M.-J., Lezine, A.-M., Achoundong, G., Hély, C., Lebamba, J., Marquer, L., Mazier, F., and Sugita, S.: Quantitative land-cover change in West Africa over the Holocene: case study in Cameroon, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9054, https://doi.org/10.5194/egusphere-egu2020-9054, 2020.

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