Improvement of Salmon Life-Cycle Framework Model (inSALMO)

Criterion	Explanation
General Description	An individual-based model (IBM) designed to support management of freshwater life stages of salmon—spawning through rearing and out-migration. The model is adapted from a family of IBMs that have been applied to a variety of salmonid management and research issues (see www.humboldt.edu/ecomodel/instream.htm).
Model Domain	Model domain is flexible
Developer	Developed by Lang, Railsback and Associates (LRA) and USDA Forest Service, Pacific Southwest Research Station, for the US Bureau of Reclamation and US Fish and Wildlife Service.
Hardware computing requirements	Windows OS
Code language	Objective C
Original application	In the work funded in 2004, the Central Valley Chinook IBM was dubbed inSALMO version 0.5. One deliverable of that project was a statement of future information and research needs. This statement concluded that the original concept of a single management model for all parts of the Chinook life cycle has a fundamental problem: because salmon have a very complex life cycle and occupy many habitats, a model that tried to capture the entire life cycle in sufficient detail to solve many kinds of management problems would be extremely large and too complex to calibrate and use. Conversely, version 0.5 of inSALMO was kept simple and, consequently, lacked the detail needed to solve management problems. The original concept of a "virtual salmon population" of the Sacramento River basin that could be used to evaluate all kinds of management actions does not appear feasible. Instead, inSALMO was envisioned as a framework inside of which detailed models of specific, limited management problems are built.
Public/proprietary and cost	This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.
Physically or empirically based	Physical and empirical
Mathematical methods used	Simulated fish select and respond to 2D habitat representation (cells of several square meters) based on numerous behavioral rules and parameters. Fish parameters are functions of time, fish length, temperature, flow, depth, turbidity, etc. These relationships take many different functional forms including linear, logistic, exponential, and power.
Input data requirements	Daily mean temperature, flow, and turbidity. Cell geometry based on bed topography and field observations of habitat (including cover variables as well as depth and velocity). The cell boundaries were manually placed using a geographic information system (GIS). Hydraulic input provides the depth and velocity in each cell, at a number of flows covering the range occurring in the flow input. These inputs are used by inSALMO each simulated day to interpolate depth and velocity from daily flow. Shear stress parameters. The number, characteristics, and timing of adult salmon arriving to spawn. Numerous fish parameters related to temperature tolerance, fecundity, swimming behavior, predation risk, etc.
Outputs	Outmigration timing, total number of live outmigrants by body length, habitat characteristics, growth rates, and survival probabilities for each fish.
Pre-processing and post-processing tools	A custom QGIS plugin "Ungenerate" converts the grid shape file into the format inSALMO requires (https://plugins.qgis.org/plugins/Ungenerate/). Model GUI includes processing tools (e.g., Limiting Factor Tool, View Results Tool).
Representation of uncertainty	The LFT addresses its objective by implementing a sensitivity analysis approach. It includes built-in experiments for habitat variables that (a) likely have—or are often believed to have— strong effects on the salmon life stages represented in version 1.0 of inSALMO, and (b) potentially could be changed via management actions. Each LFT experiment runs the model repeatedly using a wide range of values for one factor. The tool then computes and compares the degree to which the model's key output—the number of relatively large outmigrating juveniles—responds to each factor. Results of the limiting factors experiments depend on the values used for inSALMO's parameters, and these parameters are uncertain. The LFT therefore explicitly addresses how robust its results are with respect to parameter uncertainty. Each experiment is executed multiple times using combinations of several parameters which are particularly important and uncertain, and the results analysis considers how consistent the importance of factors is among these multiple executions.
Prevalence	Model used in at least two peer-reviewed publications. Used in Lower Clear Creek Flood Plain Restoration Project. Under consideration for use within WRLCM.
Ease of use for public entities	Extensive documentation and GUI makes the model accessible.
Ease of obtaining information and availability of technical support	No user group or commercial help desk
Source code availability	Source code for model and GUI are available on GitHub.
Status of model development	Model is apparently stable and not under active development.
Challenges for integration	The model already integrates a 2D hydraulic model with a fish model. The numerous fish parameters in the model might make application to a new system challenging.

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