Spatial Processes and Stock Assessment Methods – Management Strategy Evaluation
🌐 SPASAM.MSE Website • 💻 GitHub Repo • ⚙️ WHAM • ✉️ Contact
SPASAM.MSE is a spatially explicit, closed-loop Management Strategy Evaluation (MSE) framework built on WHAM (Woods Hole Assessment Model). It is designed to test how spatial heterogeneity—driven by population biology, fishing dynamics, and movement/connectivity—can shape:
- stock assessment performance (bias, precision, robustness under misspecification)
- management outcomes (catch, biomass, fishing mortality)
- risk (overfishing / overfished probabilities)
- spatial trade-offs across regions and stocks
At its core, SPASAM.MSE links the full end-to-end pipeline:
Operating model → data generation → estimation model → projections → harvest control rules → implementation error → feedback
By leveraging WHAM’s state-space platform, SPASAM.MSE can treat key biological and fishery processes as random effects (as configured) in both operating and estimation models—making it ideal for controlled experiments on model misspecification, spatial structure, and management robustness.
- Multi-stock, multi-region population structure
- Spatial heterogeneity in biology and fishing dynamics
- Explicit connectivity among regions via movement
- Bidirectional and unidirectional movement
- Metapopulation and natal homing dynamics
- Age- and/or year-varying movement
- Monotonic movement patterns (e.g., increasing/decreasing connectivity through time)
- Optional environmental covariate effects on movement
- Movement parameterized with fixed or random effects across age, year, season, stock, and region
- Fishery-dependent data (e.g., catch, effort, composition)
- Fishery-independent data (e.g., survey indices and composition)
- Configurable observation error and sampling design to explore:
- data quality & coverage
- spatial sampling structure
- fleet / survey configurations
- Fit spatial or non-spatial estimation models to simulated data
- Deliberately test robustness under misspecification (movement, spatial structure, process error assumptions)
- Optional aggregation to match EM spatial resolution (e.g., OM regions → coarser EM)
- Generates assessment outputs used for management advice, projections, and evaluation
- Full feedback loop with flexible controls for:
- projection length & assessment update frequency
- averaging windows for biological/fishery inputs
- harvest control rules (e.g., F₄₀%SPR, FMSY, hockey-stick rules)
- fishing mortality or catch specification during projection
- propagation of recruitment/process/movement uncertainty
- optional continuation of random effects and environmental covariates
Implementation uncertainty supported (e.g., deviations between advised and realized catch/F).
- Bias/precision for SSB, F, recruitment, catch
- Probability-based metrics (overfishing / overfished)
- Spatial trade-offs across regions/stocks
- Automated reporting outputs (PNG / HTML / PDF)
SPASAM.MSE leverages WHAM’s state-space design to represent processes as fixed or random effects (as configured) in both OM and EM, enabling realistic uncertainty propagation and controlled tests of misspecification.
WHAM-based random effects can be configured for:
- Recruitment and numbers-at-age
- Fishing selectivity
- Natural mortality
- Fishing mortality
- Survey catchability
- Movement
WHAM is a general state-space, age-structured stock assessment framework designed to incorporate environmental effects and time- and/or age-varying process error. WHAM is actively developed and applied in research and assessment contexts at NOAA NEFSC.
WHAM can be configured as:
- SCAA with recruitment as fixed effects
- SCAA with recruitment as random effects
- Fully state-space models with abundance-at-age as random effects
WHAM resources
- Website & documentation: https://timjmiller.github.io/wham/
- Vignettes: https://timjmiller.github.io/wham/articles
- Overview presentation (Jan 8, 2021): https://www.youtube.com/watch?v=o8vJvbIaOdE
SPASAM.MSE extends WHAM by embedding it within a spatially explicit MSE framework, enabling systematic and reproducible testing of spatial assessment and management strategies under controlled simulation experiments.
👉 Project website (docs & vignettes): https://lichengxue.github.io/SPASAM.MSE
Install the development version from GitHub:
remotes::install_github("lichengxue/SPASAM.MSE", dependencies = TRUE)