Bethel, M.B.; Brien, L.F.; Esposito, M.M.; Miller, C.T.; Buras, H.S.; Laska, S.B.; Philippe, R.; Peterson, K.J., and Richards, C.P., 2014. Sci-TEK: A GIS-based multidisciplinary method for incorporating traditional ecological knowledge into Louisiana's coastal restoration decision-making processes.
Making more informed coastal restoration and protection decisions has become increasingly important given limited resources available for ecosystem restoration projects and the increasing magnitude of marsh and barrier island degradation, and associated land loss, across Louisiana's coast. An interdisciplinary team of physical and social scientists, coastal restoration managers, and fishers/resource harvesters of affected coastal Louisiana communities collaborated on this study, with the goal of enhancing restoration decision making by engaging local ecosystem knowledge holders in the process. Together they investigated the feasibility and benefits of integrating the traditional ecological knowledge (TEK) of a coastal population with geospatial technology and scientific data sets to assess how the resulting knowledge might inform project planning and implementation for coastal restoration. The primary goal was to provide coastal resource managers with a more comprehensive and transferrable method of assessing localized stakeholder priorities and translating that information into a format compatible with or comparable to products of existing coastal restoration decision-support tools for Louisiana. Through the Sci-TEK process, TEK is recorded in a natural, egalitarian setting and is converted into geographic information system (GIS) models that can facilitate incorporation into the existing restoration-planning process. This is achieved by using remote sensing, science-based data sets, and GIS to produce mapping products that represent the local fishers' and harvesters' TEK. The collaborative team developed a method for effective stakeholder engagement and a process for producing mapping products to aid in restoration location prioritization using information derived and prioritized with TEK. The current model of engagement via public meetings can generate extensive transcripts of public opinion, but it is limited in terms of scope and stakeholder representation. The information obtained with this model is also difficult to incorporate into the scientific toolbox used to make decisions about restoration. By mapping TEK we translated this knowledge into a usable data set layer that incorporates quality control and can be confidently used in combination with existing data sets. Moreover the researchers used the stakeholder engagement process to help address the general lack of understanding by physical scientists and managers/decision makers of the value of TEK, and to illustrate how this participatory process helps to bridge the communication gap that typically exists between scientists and traditional knowledge holders.