dia: An R package for the National Oceanic and Atmospheric Administration dam impact analysis
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dia: An R package for the National Oceanic and Atmospheric Administration dam impact analysis

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  • Journal Title:
    Journal of Open Source Software
  • Personal Author:
  • NOAA Program & Office:
  • Description:
    Populations of anadromous (sea-run) fishes such as Atlantic salmon Salmo salar have experienced severe global declines as a result of pollution, overfishing, and construction of dams (Limburg & Waldman, 2009). Life-history-based simulation models are commonly used for planning and implementing fisheries recovery activities for many diadromous species (Barber et al., 2018; e.g., Nieland et al., 2013; Stich et al., 2019; Zydlewski et al., 2021). Before open-source tools became prevalent, many institutionalized decision-support tools utilizing such models relied on closed-source or paid software. For example, the National Oceanic and Atmospheric Administration (NOAA) Dam Impact Analysis (DIA) was originally created as a stochastic life cycle model for Atlantic salmon in the @RISK add-in within Microsoft Excel (Nieland et al., 2013). This tool differs from those hosted in similar R packages for non-salmonid species (e.g. Stich et al., 2019; Zydlewski et al., 2021) in that it incorporates homing behavior (probability of adults returning to natal streams or straying to others) and integrates results of physical modeling to inform population dynamics (Nieland et al., 2013; Nieland & Sheehan, 2020). This class of tools, in general, provides advantages for decision making related to anadromous species because it allows integration of geographically and temporally explicit stock dynamics (e.g., influences of dams) that are not readily implemented in classical fisheries stock assessment tools such as those available in existing R packages (Erickson et al., 2022; e.g. Kell et al., 2007; Ogle et al., 2022). We created the dia package (Stich et al., 2021) for the R programming language (R Core Team, 2024) as a freely accessible, open-source implementation of these tools that will promote transparency in planning and decision making.
  • Source:
    Journal of Open Source Software, 10(105), 7475
  • DOI:
  • ISSN:
    2475-9066
  • Format:
    PDF
  • Publisher:
    The Open Journal
  • Document Type:
    Journal Article
  • License:
  • Rights Information:
    CC BY
  • Compliance:
    Submitted
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  • Download URL:
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