A Field Guide to Corralling the Chaos: A Planning Framework for Using Models to Guide Opportunistic Field Studies of Natural Disturbances

Abstract

Watersheds regulate biogeochemical processes and provide ecosystem services to human societies, but disturbances can fundamentally alter these processes across space and time. Determining when and where to sample to capture disturbance impacts in watersheds remains a central challenge. Manipulation studies and long‐term monitoring are often constrained by scope, and opportunistic studies often lack pre‐disturbance data needed to statistically determine disturbance impacts. We identify a persistent knowledge gap: the absence of a clear, transferable framework to guide opportunistic disturbance research where pre‐disturbance data collection is not a feasible option. To address this gap, we present a planning framework that intentionally integrates numerical modeling and empirical observation in an iterative, stepwise model–experiment workflow for opportunistic disturbance research. We demonstrate its application through two contrasting case studies: wildfire impacts on headwater streams using a pre‐disturbance preparedness approach, and saltwater flooding impacts on coastal forests using an post‐disturbance study approach. From these applications, we assess strengths, limitations, and the critical role of team science for transferability across disturbance types and study designs. Broadly, this framework offers a scalable path toward more rigorous, timely, and actionable disturbance science that can inform watershed management, hazard risk reduction, and ecosystem resilience. While this framework is illustrated with watershed examples, the framework is broadly applicable wherever studying responses to unpredictable natural events requires rapid, hypothesis‐driven research design.