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Title: Investigating the interactions between fluvial processes and floodplain forest ecology in the Amazon Basin
Author: Buckley, Simon
ISNI:       0000 0004 5364 9241
Awarding Body: University of Exeter
Current Institution: University of Exeter
Date of Award: 2014
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Amazonian tropical forests account for 20-50% of global primary productivity and up to 40% of carbon stored in terrestrial biomass (Phillips et al., 1998). The Amazon is also home to the Earth’s largest river system, accounting for approximately 20% of the world’s total river discharge (Richey et al., 1989). Despite the clear global significance of the Amazon basin, substantial uncertainties remain in terms of both aboveground wood biomass and carbon storage within its extensive forests (Houghton et al., 2001), and the functioning of its river systems, particularly in terms of floodplain inundation (Wilson et al., 2007). This thesis addresses the aforementioned uncertainties through providing new insight into the interaction between fluvial processes and Amazonian floodplain varzea forests, for the Beni floodplain in north east Bolivia. Flood inundation dynamics for the Beni floodplain are quantified through application of a 1D-2D hydraulic model code, with topographical forcing provided through bare earth DEMs derived from the SRTM global elevation dataset (Farr and Kobrick, 2000). Subsequently, in the final part of the thesis, aboveground wood biomass estimates are generated for the Beni floodplain, through extrapolation of plot scale inventory measurements with respect to spatially distributed remote sensing datasets. These estimates are subsequently integrated with modelled flood inundation and maps depicting Beni river channel migration, in order to explore the influence which fluvial processes exert upon aboveground wood biomass storage in varzea forest stands. Overall, results presented within this thesis quantitatively demonstrate that fluvial processes, specifically flood inundation and lateral channel migration, exert significant impacts upon aboveground biomass storage within Beni floodplain forests. Furthermore, as a result of these influences, aboveground wood biomass storage within Beni floodplain forests is substantially lower than would be expected based upon published estimates for varzea forests across the Amazon (Baker et al., 2004; Saatchi et al., 2007). This implies that systematic overestimation of aboveground wood biomass storage for Amazonian varzea forests may constitute a significant source of uncertainty in basin scale biomass estimates.
Supervisor: Nicholas, Andrew; Aragao, Luiz; Aalto, Rolf Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Amazon ; Biomass ; Flooding ; Remote Sensing ; Hydraulic Modelling