Modeling the social drivers of environmental sustainability among Amazonian indigenous lands using Bayesian networks.

Abstract

Amazonia is an invaluable global asset for all its ecological and cultural significance. Indigenous peoples and their lands are pivotal in safeguarding this unique biodiversity and mitigating global climate change. Understanding the causal structure behind variation in the degree of environmental conservation across different indigenous lands-each with varying institutional, legal, and socioenvironmental conditions-is an essential source of information in the struggle for long-term sustainable management of Amazonian ecosystems. Here, we use data from the Instituto Socioambiental for 361 indigenous lands in the Brazilian Amazon coded for environmental integrity, territorial integrity, legal stability, indigenous governance, and threats due to infrastructure projects. Using Bayesian networks to learn the causal structure amongst these variables reveals two causal pathways leading to environmental integrity. One causal pathway starts with territorial integrity and is mediated by infrastructure projects, while the other is directly from legal stability. Hence, safeguarding indigenous lands from exploitation is best accomplished via legal land rights and stricter enforcement instead of placing the onus on indigenous governance, which is also a direct outcome of legal stability.