S6.3 Specht: The detection of socio-economic impacts of protected area creation
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Dr Alison Specht, Ecosystem Research Analyst, TERN
Abstract:
A fundamental concern of the science and policy agenda is the effect of global changes on the world’s ecosystems and the cascading consequences on human societies. Under this uncertain future, protected areas (PAs) can contribute directly or indirectly to socioeconomic outcomes such as food security and development opportunities for nearby human societies. This subject is being addressed in the Belmont Forum funded PARSEC project (parsecproject.org), with funding partners from France, the USA, Brazil, Japan, and associates in Australia. In this presentation we shall discuss some interim results and challenges through examples from Australia, Brazil and the USA. The approach stems from recent research demonstrating the ability to predict socioeconomic conditions using satellite imagery and deep-learning algorithms1,2. Firstly we identify areas with PAs for which we can obtain satellite images before and after their creation. We have been using the World Database for Protected Areas (WDPA) for our main source, validating this against national information. Once PAs are selected, these, and the surrounding villages and towns, will be mirrored with areas without PAs. Concurrently we have been identifying the sources of socio-economic information that will allow training of the satellite images to identify socio-economic indicators. The PARSEC project brief also includes a strong thread of data management with data scientists working alongside the research process described above. We shall briefly outline our ongoing data and digital object management approach, within which we have identified tools which assist active international collaboration as well as ensuring good data management practices. This is integral to the success of the project and enables the results (including any codes created) to be properly reported and lodged in open-access repositories.
1. Jean, N. et al. (2016) doi.org/10.1126/science.aaf7894 2. Yeh, C., et al. (2020) doi.org/10.1038/s41467-020-16185-w
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