This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1016/j.oneear.2021.05.011. This is version 3 of this Preprint.
This Preprint has no visible version.
Download PreprintThis is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1016/j.oneear.2021.05.011. This is version 3 of this Preprint.
This Preprint has no visible version.
Download PreprintIn the coming months, international negotiations under the 1982 United Nations Convention on the Law of the Sea (UNCLOS) will enter their fourth and final session to establish a legally binding agreement for the conservation and sustainable use of marine biodiversity in one of our largest global commons, areas beyond national jurisdiction (BBNJ). In this context, scientists have proposed data-driven optimization algorithms (hereafter algorithmic approaches) to assist in maximizing the protection of BBNJ while considering specific economic costs and risks. Algorithmic approaches to global environmental issues are attractive and useful because of their capacity to integrate a wide scope of data and complex objectives into definitive policy suggestions. However, data-driven scientific recommendations at a global scale largely consider the costs and benefits of conservation action to only a subset of human actors, raising critical questions of equity and environmental justice that we must address as a scientific community. Here, we 1) highlight equity oversights in algorithmic approaches to BBNJ protection, including current disparities in both the data inputs and optimization targets of these approaches; and 2) propose ways in which current algorithmic approaches can be integrated into a broader and more inclusive prioritization process for the conservation and sustainable use of BBNJ. A more equitable path forward in scientific recommendations to BBNJ protection will require not only stepping away from rigid data-driven algorithmic approaches and towards approaches that integrate established social science methodologies, but also critical and continued engagement with environmental justice principles. By integrating powerful algorithmic approaches with tools from the conservation social sciences that allow for the consideration of diverse interests in this global treaty, scientists can help ensure that our greatest global commons is managed in a more equitable manner, not just for the values and benefit of a select powerful few.
https://doi.org/10.32942/osf.io/jhbuz
Biodiversity, Life Sciences
Published: 2021-02-14 19:20
Last Updated: 2021-06-01 19:19
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