Conservation and land use planning applications in Gabon, Central Africa

Thesis

Spatial prioritization and systematic conservation planning methods are designed to improve land use decisions and conservation outcomes, yet remain underutilized in many biologically-rich places that need them most. This thesis applies the theory and methods developed in the discipline of spatial prioritization to conservation and land use decisions in the Central African country of Gabon. Creating a spatial information base of priority species, habitats and land uses in a region that is notoriously data-poor, I reveal that many features important for both conservation and natural resource production are highly localized; their coincidence has important implications for management. Setting conservation targets for species and habitats, I find that representation in existing protected areas is relatively low, and identify a number of near-optimal solutions that meet all targets, with minimal impact on land used for local livelihoods. I distill these solutions down to a handful of critical biodiversity sites that are top priority to protect, and make management actions explicit for the species and habitats they contain. To make the work more widely applicable, I also develop a novel method to identify where field surveys are most likely to improve decisions about protected area expansion, providing decision-makers with more options of places that could be protected to achieve conservation goals. This study contributes to the research, development and practice of conservation prioritization and spatial planning, particularly in data-poor contexts like Gabon, which still have a wealth of biodiversity, and need to carefully plan for its conservation alongside development.

Authors: Lee, M

• Publication date: 2014
• DOI: 10.5287/ora-xoqz0bopx
• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: Oxford University, UK
• Language: English
• Keywords: land use; conservation planning; Spatial prioritization
• Subjects: Biodiversity; Africa; Decision science; Ecology (zoology)