Wood Jam Dynamics Database and Assessment Model (WooDDAM): A framework to measure and understand wood jam characteristics and dynamics

摘要

Wood jams in rivers and on floodplains play an essential role in shaping valley bottoms, and their dynamics regulate the ecology and morphology of river systems. Although wood jams are commonly used to regulate fluvial geomorphic processes and provide habitat, our inability to predict how wood jams change through time hampers wood restoration efforts. We present the Wood Jam Dynamics Database and Assessment Model (WooDDAM) to improve understanding and management of natural and anthropogenic wood jams in rivers. WooDDAM is composed of a field data collection protocol, an open database of wood jam characteristics and dynamics, machine learning statistical models for predicting wood jam dynamics during high flows, and an online user interface to facilitate collaborative data collection and use. Here, we provide the background and guidance necessary to utilize WooDDAM to make predictions of and contribute to the database describing wood jam dynamics. We present tests of interoperator variability to justify database variable selection. To refine model predictions and improve predictive power, we encourage users to follow simple resurvey procedures and submit observations of wood jam dynamics. WooDDAM provides a management and monitoring tool for the retention or reintroduction of wood jams in rivers and facilitates further research into the interactions between wood jam dynamics and fluvial or ecological processes.