Bridging the Gap: {ecosystemom} for Integrating Climate and Ecosystem Information into Single-Species Fisheries Management Advice

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.title[
# Bridging the Gap: {ecosystemom} for <br> Integrating Climate and Ecosystem <br> Information into Single-Species Fisheries <br> Management Advice
]
.author[
### <b>Bai Li</b><sup>1</sup>, Kelli Johnson<sup>2</sup>
]
.author[
### <sup>1</sup>Contractor with ECS Federal LLC in support of <br> NOAA Fisheries Office of Science and Technology
]
.author[
### <sup>2</sup>NOAA Fisheries Office of Science and Technology
]
.institute[
### ICES Annual Science Conference 2026 | Session F
]
.date[
### 2026/09/17
]

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.footnote[U.S. Department of Commerce | National Oceanic and Atmospheric Administration | National Marine Fisheries Service]

---
# Outline

- Single-Species Advice in Dynamic Ecosystems
- Overview of {ecosystemom}
- End-to-End Simulation Case Study
- Lessons Learned: Surveys, Natural Mortality, and Environmental Drivers
- Future Directions

---
# Single-Species Advice in Dynamic Ecosystems

- Single-species assessments remain central to tactical fisheries management worldwide
- Current testing may suggest robust performance when using single-species operating models (OMs)
- Real-world fish stocks inhabit dynamic oceans driven by environmental forcing and changing trophic interactions
- The key gap is integration: connecting ecosystem models to tactical stock assessment tools

.footnote[
Figure generated by Gemini 3.6, Google, September 2026
]
---

# Overview of {ecosystemom}

.pull-left-75[

- Build a flexible ecosystem-to-stock-assessment simulation framework within the open-source .hyperlink-style[[NOAA Fisheries Integrated Modeling System](https://noaa-fims.github.io/)] (FIMS)

- 🧪 Test FIMS using ecosystem models as OMs

- 🔍 Explore ecosystem-informed stock assessment approaches

- 🤝 Create interdisciplinary research and collaboration opportunities
  
- Current and planned ecosystem modeling platform support

<div style="display: flex; align-items: flex-end; justify-content: space-evenly; text-align: center; margin-top: 20px;">
  
  
  <div style="display: flex; flex-direction: column; align-items: center;">
    <img src="https://upload.wikimedia.org/wikipedia/commons/thumb/d/d6/EwE6Logo_Transparent.png/250px-EwE6Logo_Transparent.png" height="90px" alt="EwE Logo" />
    <span style="margin-top: 10px; font-weight: bold;">Ecopath with Ecosim (EwE)</span>
  </div>

<div style="display: flex; flex-direction: column; align-items: center;">
    <img src="https://avatars.githubusercontent.com/u/43390982?s=200&v=4" height="90px" alt="Atlantis Logo" />
    <span style="margin-top: 10px; font-weight: bold;">Atlantis</span>
  </div>

<div style="display: flex; flex-direction: column; align-items: center;">
    <img src="https://noaa-edab.github.io/Rpath/logo.png" height="90px" alt="Rpath Logo" />
    <span style="margin-top: 10px; font-weight: bold;">Rpath</span>
  </div>

</div>
  
]

.pull-right-25[
<img src="static/FIMS_hexlogo.png" width="70%" style="display: block; margin: auto;" />
]

.clear[]

.footnote[
[1] .hyperlink-style[[FIMS Website: https://noaa-fims.github.io/FIMS/](https://noaa-fims.github.io/FIMS/)]<br>
[2] .hyperlink-style[[ecosystemom Website: https://noaa-fims.github.io/ecosystemom/](https://noaa-fims.github.io/ecosystemom/)]
]
---

# Overview of {ecosystemom}

- `load_model()`: Import and standardize outputs from ecosystem OMs

- `get_truth()`: Extract “true” population quantities from OMs

- `sample_*()`: Generate sampled observations from OM outputs for use in fisheries stock assessment models such as FIMS

- `create_dsem_inputs()`: Prepare environmental covariates or diet composition data from the OM to support candidate model specifications for dynamic structural equation models (DSEMs)

<table class="table" style="font-size: 14px; margin-left: auto; margin-right: auto;">
 <thead>
  <tr>
   <th style="text-align:left;"> species_name </th>
   <th style="text-align:left;"> truth_label </th>
   <th style="text-align:left;"> truth_type </th>
   <th style="text-align:left;"> truth_time_step </th>
   <th style="text-align:left;"> truth_om </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> menhaden </td>
   <td style="text-align:left;"> biomass </td>
   <td style="text-align:left;"> index </td>
   <td style="text-align:left;"> yearly </td>
   <td style="text-align:left;"> &lt;tibble [33 × 3]&gt; </td>
  </tr>
  <tr>
   <td style="text-align:left;"> menhaden </td>
   <td style="text-align:left;"> catch </td>
   <td style="text-align:left;"> index </td>
   <td style="text-align:left;"> yearly </td>
   <td style="text-align:left;"> &lt;tibble [33 × 3]&gt; </td>
  </tr>
  <tr>
   <td style="text-align:left;"> menhaden </td>
   <td style="text-align:left;"> catch </td>
   <td style="text-align:left;"> agecomp </td>
   <td style="text-align:left;"> yearly </td>
   <td style="text-align:left;"> &lt;tibble [231 × 4]&gt; </td>
  </tr>
  <tr>
   <td style="text-align:left;"> menhaden </td>
   <td style="text-align:left;"> fishing_mortality </td>
   <td style="text-align:left;"> index </td>
   <td style="text-align:left;"> yearly </td>
   <td style="text-align:left;"> &lt;tibble [33 × 3]&gt; </td>
  </tr>
  <tr>
   <td style="text-align:left;"> menhaden </td>
   <td style="text-align:left;"> natural_mortality </td>
   <td style="text-align:left;"> agecomp </td>
   <td style="text-align:left;"> yearly </td>
   <td style="text-align:left;"> &lt;tibble [231 × 4]&gt; </td>
  </tr>
  <tr>
   <td style="text-align:left;"> menhaden </td>
   <td style="text-align:left;"> numbers </td>
   <td style="text-align:left;"> agecomp </td>
   <td style="text-align:left;"> yearly </td>
   <td style="text-align:left;"> &lt;tibble [231 × 4]&gt; </td>
  </tr>
</tbody>
</table>

---
# End-to-End Simulation Case Study

- Ecosystem: Northwest Atlantic EwE Ecosim model (Adapted from Chagaris et al., 2020)

- Focal stock: Atlantic menhaden-like species

- OM scenarios:
  - Scenario 1 (S1): base scenario without environmental forcing
  - Scenario 2 (S2): environmental forcing scenario

- Estimation model (EM): FIMS

.footnote[
.hyperlink-style[[Chagaris, D., Drew, K., Schueller, A., Cieri, M., Brito, J., and Buchheister, A. 2020. Ecological reference points for Atlantic menhaden established using <br> an ecosystem model of intermediate complexity. Frontiers in Marine Science, 7:606417. 10.3389/fmars.2020.606417.](https://doi.org/10.3389/fmars.2020.606417)]<br>
]

---
# Lessons Learned #1: Sample Size vs. Survey Types

- Increasing age composition sample size did not fix non-convergence in the EM

- Simulating a dedicated Young-of-Year survey index improved model fits and recruitment tracking

.pull-left[
<img src="static/ecosystemom_atlantic_menhaden_recruitment_without_yoy.png" width="90%" style="display: block; margin: auto;" />
]

.pull-right[
<img src="static/ecosystemom_atlantic_menhaden_recruitment_with_yoy.png" width="90%" style="display: block; margin: auto;" />
]

**{ecosystemom} provides a testbed to evaluate alternative survey designs**

---
# Lessons Learned #2: Perfectly Known Natural Mortality

- Passing the "true" time-varying and age-varying natural mortality (M) matrix from the OM (S1) yielded matching estimates

- Assuming perfectly known time-varying M is not applicable to real-world assessments

.pull-left[
<img src="static/ecosystemom_atlantic_menhaden_biomass_comparison.png" width="80%" style="display: block; margin: auto;" />
]

.pull-right[
<img src="static/ecosystemom_atlantic_menhaden_fishing_mortality_comparison.png" width="80%" style="display: block; margin: auto;" />
]

**{ecosystemom} provides a testbed to explore parameter and process misspecifications**

---
# Lessons Learned #3: Incorporating Environmental Drivers

- Implementing DSEM in FIMS is currently a work in progress

- Active environmental forcing (S2) in the OM creates parameter estimation challenges when the EM lacks explicit environmental driver incorporation

```md

⚠️ FIMS Warning ⚠️

#> Warning: ! Large condition number detected in Hessian; the matrix may be near singular.
#> ℹ Condition number of Hessian ("1.406917e+05") exceeds threshold of 1e+05.
#> ℹ This suggests the model is weakly identified and results may be unreliable.
#> ℹ Consider simplifying the model, improving data quality, or fixing poorly
#>   informed parameters.
#> ℹ The 2 largest standard error values are for parameters:
#> ℹ 1. "expected_recruitment": "8.273532e+09"
#> ℹ 2. "numbers_at_age": "8.273532e+09"
```
**{ecosystemom} provides a testbed to evaluate how to best incorporate climate and ecosystem information into stock assessment models**

---
# Future Directions

🤝 To contribute or share feedback on {ecosystemom}, visit the repository or email Bai Li at bai.li@noaa.gov.

.footnote[
Figure generated by Gemini 3.6, Google, September 2026
]

???
- Expanding {ecosystemom} to ingest spatially explicit operating models like Ecospace and Atlantis

- Simulating spatial survey sampling and index generation under shifting species distributions

- Coupling single-species assessments into closed-loop Management Strategy Evaluations to test climate-ready harvest control rules

- Continuing to build on FAIR open-science principles through transparent, community-driven development, and weekly public working sessions

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