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Modern and past grass-dominated biomes distribution recorded by phytoliths and stable carbon isotopes; calibration and modelling


Nowadays grasslands are the most widespread continental floral associations. They were more abundant than today during the different past glaciations. Although proxy indicators of past environments can be derived from fossil records, the reconstruction of grass-dominated biomes is difficult as pollen cannot distinguish between grass subfamilies. The main objective of this project is focused on the Quaternary dynamics of grass-dominated biomes in South America and Colombia in particular, in order to better u nderstand the relationships between climate change and vegetation dynamics (e.g. C3/C4 grass distribution) in tropical areas. For this purpose, quantitative data and vegetation models will be coupled. Calibration of statistical relationships between modern phytolith assemblages, stable carbon isotopic signatures of modern soil derived organic carbon, botanical statements for several grassland biomes and climate data will be performed. Regression equations between climate parameters, the quantitative phytoli th and d13C proxy of C3/C4 grasslands will be estimated. In a second stage, we will apply the calibrated relationships to several soil profiles from several elevation transects where the change in C3/C4 grass dominance over the last 10,000 years has been r ecorded. Finally, the reconstructed vegetation and climate parameters will be compared with several scenarios derived from two vegetation models (BIOME 3 and LPJ-GUESS). This process of data-model comparison will include investigating changes in precipitat ion, temperature and atmospheric CO2 concentrations. The comparison between simulation and data enables in turn, by inversion of the model, to reconstruct the parameters best as coherent as possible with the data. The application and development of the phy tolith proxy in tropical South America will also allow comparison with recent synthesis studies that have primarily focused on pollen data alone.

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University Road
United Kingdom

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