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projak vs spmR

Technical Comparison Notes

2026-09-30

1 Purpose

These notes describe the earlier version 0.3.0 architecture. In version 0.4.1, new spmR ADMB runs require explicit format-2 metadata for recruitment and population weights. New RTMB runs are blocked while the prototype awaits population dynamics; archived output remains readable.

1.1 Current split-sex input requirements

For spmR 0.4.1 ADMB projections, add spm_metadata.json alongside spm.dat and the species files; tacpar.dat is no longer required. Split-sex species files place wt_M immediately after wt_F. Declare recruitment_basis as "total" or "per_sex" and supply female and male population weights with matching age labels and units. The engine converts the complete recruitment history to totals before calculation and splits each projected total equally between sexes once. Population weights determine total biomass; the positional spawning and fishery weights retain their separate roles. Missing male population weights require an explicit, recorded substitute before a split-sex run can proceed.

The runnable split-sex migration guide documents the metadata, starting-year boundary, executable compatibility check, and output provenance. The comparison below describes the earlier architecture and retains that historical scope.

  • projak (Ben Williams, v0.0.0.9000): pure-R package for NPFMC projection scenarios (1-7) downstream of an RTMB assessment; accepts a report object as input.
  • spmR (Jim Ianelli, v0.3.0): Standard Projection Model wrapper around the legacy ADMB spm executable with an experimental RTMB path; reads .dat inputs (ADMB-style).

2 Architecture

Component projak spmR
Input RTMB report object spm.dat plus species files
Compiled code None (pure R) ADMB spm.tpl plus partial RTMB stub
Multi-species support Single-species Multi-species natively (nspp)
Scenario coverage 1-7 fully implemented Alternatives 1-5 (RTMB path is a stub)
Maturity Early development (0.0.0.9000) More complete (tests, vignettes, pkgdown)

3 Recruitment

Both projects implement inverse-Gaussian recruitment, but with different parameterization paths:

  • projak: takes arithmetic and harmonic means directly from report$recruits.
  • spmR RTMB path: derives CV from the harmonic-to-arithmetic ratio, then samples recruitment.

4 Tier and Harvest Control Rule Logic

  • projak includes a full get_tier_f() implementation with Amendment 56 ramp logic, SSL protection, and scenario-specific F rules.
  • spmR RTMB path (runSPM_rtmb) currently stubs the scenario loop; SSB, catch, and F are placeholder means rather than forward age-structured projections.

5 Key Gap

runSPM_rtmb() in spmR is currently a scaffold: recruitment draws are implemented, but age-structured population dynamics are not. In contrast, projak::project_step() performs full age-structured projection (survival, catch-at-age, plus-group dynamics, and SSB updates).

6 Dependencies

  • projak: data.table, tidytable, magrittr
  • spmR: dplyr, ggplot2, ggthemes, patchwork, readr, stringr, tibble, tidyr

7 Summary

projak is effectively a focused, RTMB-native replacement for the projection component, with complete harvest control rule logic and lighter dependencies. spmR remains broader infrastructure (data I/O, multi-species SPM workflow, ADMB wrapper, and visualization), but its RTMB path still needs substantial development to match projak projection fidelity.