SPASAM.MSE

What SPASAM-MSE does

SPASAM.MSE provides a flexible spatial operating model and an end-to-end workflow to test management procedures under realistic spatial structure and movement. It is designed for research and method development where spatial processes can drive estimation bias and management risk.

• Simulate spatial population structure, mixing, and connectivity (including natal homing and metapopulation dynamics).
• Generate fishery-dependent and fishery-independent data under alternative spatial sampling designs.
• Fit alternative estimation models with different spatial structures and compare against operating-model truth across scenarios and replicates.
• Evaluate trade-offs and risk across regions and stocks under closed-loop feedback.

Core capabilities

• Closed-loop MSE: OM -> data -> EM -> projections -> HCR -> implementation uncertainty -> feedback.
• Spatial control: spatial heterogeneity in population biology and fishing dynamics across regions, with explicit connectivity linking regions.
• Flexible EM spatial structure: evaluate estimation models with alternative spatial assumptions (e.g., spatial aggregation, region/fleet structure, and movement simplifications).
• Movement scenarios: bidirectional vs unidirectional connectivity, natal homing and metapopulation structure, movement trends, and optional environmental covariate effects on movement.
• State-space structure: WHAM-based design that treats key biological and fishery processes as random effects (time- and/or age-varying) in both OM and EM.
• Performance evaluation: bias/precision, status metrics, risk of overfishing/overfished, and spatial trade-offs in catch, SSB, and F.
• Parallel simulations: scalable pipelines for multi-scenario experiments.
• Automated reporting: PNG/HTML/PDF outputs for large simulation studies.