A framework tool that applies weight-of-evidence integration to the analysis of existing datasets to guide freshwater conservation
The overarching issue we address here is how to extract clear and actionable ecological and management insights from real-world field data that often do not satisfy traditional statistical assumptions. Toward this goal, we developed a general 12+6 step adaptive management framework tool. We applied this framework tool to existing biodiversity monitoring data to create a proof-of-concept result that addresses the overarching question of “ why might a specific native stream fish taxon be present or absent at specific locations? ” Our multi-step framework tool links established steps and steps that are unique to our framework through weight-of evidence (WOE) integration, an approach that combines quantitative results from multiple visualization and statistical procedures. The systematic use of all steps in our framework can provide improved conservation outcomes compared to a single analysis. Advantages accrue from our approach because our framework tool refines the overarching goal into related sub-questions, applies a specific quantitative procedure to each sub-step, combines results from all sub-questions using a WOE integration, identifies testable questions that elucidate ambiguities and gaps revealed through WOE integration, and proposes practical field methods for obtaining this clarifying information through future research and data collections. The process of considering multiple visualizations and analyses as individual pieces of a shared puzzle offers a new way to approach the use of existing data. Our team-based approach transforms the collection and analysis of existing data into a series of field tests that can guide future actions (e.g., data collection-analysis events, restoration initiatives, research). Habitat and impact regressors will vary with taxa and system, but our structured process tool has broad generality for a range of conservation issues in which freshwater systems are threatened by human impacts.