The Deforestation and Biodiversity Risks of Power Plant Projects in Southeast Asia: A Big Data Spatial Analytical Framework

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Abstract

Ecosystem destruction and biodiversity loss are now widespread, extremely rapid, and among the top global anthropogenic risks both in terms of likelihood and overall impact. Thorough impact evaluation of these environmental abuses—essential for conservation and future project planning—requires good analysis of local ecological and environmental data in addition to social and economic impacts. We characterized the deforestation and biodiversity impacts of energy investments in Southeast Asia using multiple geospatial data sources related to forest cover and loss data from 2000 to 2018, other landcover data, and the location, type, and characteristics of energy investments. This study paid particular attention to different types of power plants and financing sources. We identified critical buffer zones and forest structures impacted by these projects in accordance with IUCN criteria and spatial ecology. The paper introduces a novel, replicable analytical framework that goes beyond earlier studies in which all forests are treated as equivalent. It characterizes forests based on spatial morphological structures such as core forest, edges, islands, and bridges, allowing for a more nuanced understanding of deforestation and its impacts on biodiversity. Preliminary findings suggest that projects financed by Chinese development banks pose different risks compared to non-Chinese financing. The study also reveals significant differences in biodiversity impacts based on the type of energy source, be it coal or hydro. The study offers critical insights into the trade-offs between energy development and biodiversity conservation. It provides actionable metrics and strategies for policymakers, conservationists, and development banks to prioritize forest and habitat preservation in Southeast Asia and globally.

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Ma, Y., Gopal, S., Ma, X., Gallagher, K., Koch, M., & Kaufman, L. (2023). The Deforestation and Biodiversity Risks of Power Plant Projects in Southeast Asia: A Big Data Spatial Analytical Framework. Sustainability (Switzerland), 15(19). https://doi.org/10.3390/su151914461

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