Connecting local ecological knowledge and Earth system models: Comparing three participatory approaches

In this article we analyze participatory approaches used in three research studies where local ecological knowledge (LEK) and Earth system models (ESMs) were combined to deepen our understanding of human-environment systems and produce usable data tools for decision making. In all three cases, the combination of these complimentary types of knowledge produced richer data about the environmental conditions being studied. In the first, participants used LEK to identify ways that an ESM-produced fire simulation differs from usual seasonal patterns. In the second, participants used LEK to adapt and apply regional climate projections to the specifics of local microclimates. And in the third, participants’ ecological knowledge identified important local ecosystem processes that were not currently represented in ESMs, including the distinct roles of various vegetation in local hydrology, as well as fuel loading conditions for predicting wildfire intensity. Although all three cases demonstrate how combining LEK and ESM data improves collaborative understandings of human-environment processes, we also found that key differences in the participatory approaches we used, particularly as regards timing and type of participation from local communities, produced three different sets of outcomes. Specifically, as our cases move from less (first case) to more (third case) participation and knowledge integration, the outcomes move beyond combining ESM and LEK knowledge and toward changing the design and configuration of ESMs themselves with insights from LEK. However, we simultaneously find that these deeper levels of integration require multiyear relationships between researchers and communities, agreements on data sovereignty for communities, and community’s involvement in designing and instigating the project, which are not necessary to achieve lower levels of integration. In all three cases, we found that communities are willing to participate in this work when relationships of trust have been built, data privacy and sovereignty is agreed upon and carefully protected, and epistemic differences are respected.