Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.794179
Title: Primary forest degradation and secondary re-growth dynamics in the Brazilian Amazon
Author: Wang, Yunxia
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2019
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Abstract:
The Amazon rainforest is a vital biome that is of central importance for the provision of significant ecosystem services locally, regionally and globally. Brazil contains two-thirds of remaining Amazonian rainforests and is responsible for the majority of Amazonian forest loss. Over 0.7 million km^2 of primary forest area in the Brazilian Amazon has been deforested, of which ~20% are under secondary forest regeneration. However, the fate of secondary forests and the extent of degradation of the remaining primary forests (referred to as old growth forests in this thesis) are still unclear. In this thesis, I present: (1) the first large-scale analysis of secondary forest loss over 14 years (2000-2014) using recently released high resolution (30 m) post-deforestation land use datasets (TERRACLASS); (2) a novel machine learning classification method to map tropical forest disturbances using multi-decadal Landsat time-series imagery; and (3) first estimates of the historical degradation of remaining old growth forests using this newly-developed classification method. Our results show an accelerated loss of secondary forests across the entire Brazilian Amazon over our study period, in contrast to primary forest loss. Over 2000-2014, the proportion of total forest loss accounted for by secondary forests rose from (37 ± 3) % in 2000 to (72 ± 5) % in 2014. We developed a multi-decadal Landsat time-series imagery and machine learning random forest classification algorithm, which we found to be an efficient and accurate approach to map tropical disturbed forests. This approach allows me to map the historical degradation of old growth forests from 1984 to 2014. Until 2014, over 246,845 km^2 area of old-growth forests in the Brazilian Amazon (moist forest ecoregion) were degraded, accounted for approximately 10% of total area of old growth forests in the region. However, this approach may have underestimated the actual degradation of old growth forests as it did not detect the low intensity selective logging. In conclusion, the accelerated loss of secondary forests and extensive degradation of old growth forests in the Brazilian Amazon which we report have provided new insights into land use change dynamics in Amazonia. Both of these processes have important implications for carbon storage and biodiversity and sustainable management of forest resources in the Brazilian Amazon.
Supervisor: Galbraith, David ; Ziv, Guy ; Baker, Timothy Sponsor: China Scholarship Council ; University of Leeds ; Google Earth Engine
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.794179  DOI: Not available
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