Engineering a prototype for a next-generation stock assessment modeling platform

Details

• Journal Title:
  Fishery Bulletin
• Personal Author:
  Brodziak, Jon ; Supernaw, Matthew ; Li, Bai ; Stawitz, Christine ; Oleynik, Haley ; A’mar, Teresa
• NOAA Program & Office:
  NMFS (National Marine Fisheries Service) ; PIFSC (Pacific Islands Fisheries Science Center) ; OST (Office of Science and Technology)
• Description:
  Environmental and anthropogenic processes have led to widespread changes in productivities and spatial distributions of marine fishery resources. As geographic distributions of fish stocks and subsequently fishing fleets shift, improved spatiotemporal data and spatial modeling will become necessary to estimate abundance and productivity. The goal of this paper is to propose a strategy for engineering a modeling platform for spatially explicit, next-generation stock assessment models. We recount our approach for developing a system prototype, the Metapopulation Assessment System (MAS), that is easy to use, modular, and extensible. The MAS prototype was designed to support complex metapopulation modeling, which includes handling multiple populations, areas, fleets, and surveys and sex differentiation. We describe the components of the software life cycle, engineering, and infrastructure design to support a spatially explicit, next-generation stock assessment system. Software infrastructure was designed and implemented with 3 components: GitHub for collaboration, version control, and code organization; the C++ language for coding fishery system dynamics and estimation modeling; and the R language for coding the input-output interface and systematic testing. Systematic testing was a key component of the MAS development life cycle and was applied to guarantee that system requirements, such as accurate estimation of quantities of interest, are successfully implemented. We conclude with a discussion of some lessons learned and future challenges for ongoing efforts to implement a next-generation stock assessment platform.
• Source:
  Fishery Bulletin (2025)
• DOI:
  https://doi.org/10.7755/FB.123.2.2
• ISSN:
  0090-0656
• Format:
  PDF
• Publisher:
  NMFS Scientific Publications Office
• Document Type:
  Journal Article
• License:
  https://creativecommons.org/publicdomain/zero/1.0/
• Rights Information:
  CC0 Public Domain
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha-512:b0b3012d5f7b3f03786d591c2d295906d29c00c727f7f701e8c689928cc37e304f0f393c1172801cb12834f8a4eb040d80ac1eccf9744a9a21933ea6a4dad203
• Download URL:
  https://repository.library.noaa.gov/view/noaa/70150/noaa_70150_DS1.pdf
• File Type:
  [PDF - 1.08 MB ]