InSTREAM 7: Instream flow assessment and management model for stream trout

Mechanistic, individual-based simulation models have been used for >25 years to overcome well-known limitations of habitat suitability models. InSTREAM 7 is the latest of our individual-based models for predicting the effects of flow and temperature regimes on stream salmonid populations. Unlike PHABSIM (or other methods based on habitat quality, e.g., as net rate of energy intake), inSTREAM mechanistically represents specific effects of flow and temperature on all life stages, and how those effects combine into testable predictions of population measures such as abundance, relative abundance of multiple trout species, and persistence. InSTREAM 7 is the first version to also represent the daily light cycle (dawn, day, dusk, and night) and how feeding, predation risk, and individual behavior vary among light phases. An example assessment illustrates the importance of inSTREAM's multiple mechanisms: predicted trout population response to flow and temperature regimes depended on the effects of sub-lethal temperatures on feeding behavior and effects of temperature on egg survival and development, as well as how depth and velocity affected growth and predation risk. While its input data requirements are comparable to PHABSIM's, inSTREAM provides a more comprehensive framework for thinking about and predicting specific, well-known effects of flow and temperature. It has also proven useful for designing and evaluating restoration projects and for prioritizing alternative management actions. InSTREAM 7 is free, open-source, completely updated with recent literature, and implemented in the popular NetLogo software platform that makes customization easy.

Automated summary

InSTREAM 7 is an individual-based simulation model used to predict the effects of flow and temperature on stream salmonid populations. Unlike other methods, InSTREAM mechanistically represents the specific effects of flow and temperature on all life stages and combines them into testable predictions of population measures. The model also considers the daily light cycle and how feeding, predation risk, and individual behavior vary among different light phases.