Mon, Aug 15, 2022: 2:00 PM-2:15 PM
520C
Background/Question/MethodsEcological forecasts are predictions about the future state of ecological systems that account for the joint information from diverse data and process understanding. Traditional ecological knowledge (TEK) is the body of observations, practices, and beliefs emerging developed by Indigenous communities to promote sustainable stewardship of natural resources. These definitions, taken from the joint sponsors of this session, are completely compatible, and yet ecological forecasting and TEK are rarely explicitly integrated in ecological prediction and planning. Here, I report early results from a collaboration between the Ecological Forecasting initiative, the Geoscience Alliance, and several colleges to develop curricular models for integrating TEK and forecasting and data-science and to leverage these models to facilitate collaboration between tribal governments and U.S. governmental agencies. We ask: What does ecological forecasting have to offer Indigenous communities and what does TEK offer basic and applied ecology?
Results/ConclusionsOpportunities: The values of TEK can be incorporated at many phases of the forecasting process. Diverse prior beliefs can be incorporated via Bayesian priors; Alternative process models can incorporate TEK into models of ecosystem structure and function; And adaptive management can reflect TEK in decision making. We applied these principles in a classroom exercise integrating TEK into a scenario of water quality management. Challenges: Tribal sovereignty over data and the imperative of protecting the privacy and autonomy of decision-making within Indigenous communities must be balanced with the values of open-data and transparency. For example, the location of culturally important sites on tribal land could usefully contribute to EPA water quality reports, but must remain private to tribes. Solutions: Facilitating access to the analytical tools of forecasting for Indigenous researchers is an efficient way to overcome these challenges. Developing forecasting training tools with Indigenous students/instructors/managers facilitates this training effectively. Such training opportunities facilitate larger research programs including Indigenous voices in the design, analysis, application, and publication of ecological forecasts. This integration of forecasting and TEK will both empower Indigenous communities and improve academic ecology by expanding its scope and broadening perspectives within the field.
Results/ConclusionsOpportunities: The values of TEK can be incorporated at many phases of the forecasting process. Diverse prior beliefs can be incorporated via Bayesian priors; Alternative process models can incorporate TEK into models of ecosystem structure and function; And adaptive management can reflect TEK in decision making. We applied these principles in a classroom exercise integrating TEK into a scenario of water quality management. Challenges: Tribal sovereignty over data and the imperative of protecting the privacy and autonomy of decision-making within Indigenous communities must be balanced with the values of open-data and transparency. For example, the location of culturally important sites on tribal land could usefully contribute to EPA water quality reports, but must remain private to tribes. Solutions: Facilitating access to the analytical tools of forecasting for Indigenous researchers is an efficient way to overcome these challenges. Developing forecasting training tools with Indigenous students/instructors/managers facilitates this training effectively. Such training opportunities facilitate larger research programs including Indigenous voices in the design, analysis, application, and publication of ecological forecasts. This integration of forecasting and TEK will both empower Indigenous communities and improve academic ecology by expanding its scope and broadening perspectives within the field.