Add contribution lead table

README.md

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 The esrindex package is used to estimate bottom trawl survey abundance indices for Structural Epifauna, Jellyfish, Miscellaneous Benthic Fauna, and Forage Fish contributions in [Alaska Ecosystem Status Reports (ESRs)](https://apps-afsc.fisheries.noaa.gov/refm/reem/ecoweb/index.php). Time series for each taxonomic group and region are included in the package as built-in data sets. Indicator time series figures are available in [/plots/](./plots/). Indicator time series are updated in September following the finalization of catch and effort data from summer bottom trawl surveys.
 
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+### ESR contribution leads
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+| Contribution | Aleutian Islands | Gulf of Alaska | Eastern Bering Sea/Northern Bering Sea |
+|--------------|------------------|----------------|----------------------------------------|
+| Forage Fish | NA | [Megsie Siple](https://github.com/margaret-siple-noaa) | NA |
+| Jellyfish | [Ned Laman](https://github.com/ned-laman-noaa) | [Alexandra Dowlin](https://github.com/orgs/afsc-gap-products/people/AlexandraDowlin-NOAA) | [Thaddaeus Buser](https://github.com/ThaddaeusBuser-NOAA) |
+| Miscellaneous Benthic Fauna | [Sarah Friedman](https://github.com/SarahFriedman-NOAA) | [Sarah Friedman](https://github.com/SarahFriedman-NOAA) | [Thaddaeus Buser](https://github.com/ThaddaeusBuser-NOAA) | 
+| Structural Epifauna | [Christina Conrath](https://github.com/orgs/afsc-gap-products/people/Conrathcl) | [Christina Conrath](https://github.com/orgs/afsc-gap-products/people/Conrathcl) | [Thaddaeus Buser](https://github.com/ThaddaeusBuser-NOAA) |
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+
 # Methodology
 
 The esrindex package produces estimates of regional and subarea/stratum indices of abundance (biomass in kilotons) and confidence intervals for each ESR taxa by fitting a multivariate random effects model (REM) to design-based abundance index time series from individual survey strata (EBS groundfish strata) or subareas (AI or GOA INPFC subareas). Abundance indices are calculated from AFSC summer bottom trawl survey catch and effort data using the [gapindex R package](https://afsc-gap-products.github.io/gapindex/) (Oyafuso, 2024). Random effects models are fitted to abundance index time series using the [rema R package](https://afsc-assessments.github.io/rema/) (Sullivan and Balstad, 2022).