OOS 3-5 - Enhancing ecological forecasting through Indigenous research and data governance

Background/Question/Methods
As our societies face exceedingly complex social-ecological challenges, such as extreme climate variability and environmental justice issues, we require a comprehensive dataset to inform effective decision-making now and into the future. Yet most scientists work with incomplete datasets heavily skewed from biases born from colonial historical legacies. Our current legacy issue involves the long-standing neglect of Indigenous data, including data relationships and data responsibilities, held within diverse and dynamic Indigenous knowledge and value systems informed by centuries of observation of Earth’s ecological systems. Our Indigenous Land & Data Stewards Lab and partners at the Collaboratory for Indigenous Data Governance work to support Indigenous research and data governance. In doing so we draw from an Indigenous data sovereignty framework which honors the inherent rights of Indigenous peoples and nations to govern data concerning their communities, lands, and natural resources as a pathway towards addressing these colonial legacies and enhancing meaningful and ethical opportunities for engaging diverse ways of knowing in the sciences.

Results/Conclusions
This session includes key findings from a global systematic review assessing levels of Indigenous community engagement and decision-making authority in 140 climate field studies, and findings from an ongoing analysis of 32 Indigenous ethics guidelines, codes, and protocols which can serve to support training and leadership opportunities for Indigenous data stewards working on ecological forecasting initiatives. These are framed within seven core principles, including: 1) Grounding in Indigenous worldviews, 2) Holding cultural responsiveness, 3) Nurturing reciprocal relationships, 4) Honoring rights, 5) Maintaining ethics for balance, 6) Centering Indigenous governance, and 7) Being a good ancestor. This session will also highlight mechanisms for Indigenous research and data governance relevant for ecological forecasting, such as the CARE Principles for Indigenous Data Governance (Collective Benefit, Authority to Control, Responsibility, and Ethics), which extend and complement the FAIR Guiding Principles for scientific data management and stewardship, and resources for those stewarding Indigenous data (such as traditional ecological knowledge) within data collections and digital repositories.