mscatch: An R package for calculating catch-at-length and age

.title[
# mscatch: <br /> An R package for <br /> calculating catch-at-length and age
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.subtitle[
## 10 October 2022
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.author[
### Andy Beet <br /> Northeast Fisheries Science Center<br /> <br /> Contributors:<br /> Sarah Gaichas, Sean Lucey, Kiersten Curti <br /> EDAB, numerous Population Dynamics Scientists
]

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## Background: Data

* Single species catch at age models require a lot of data. In the Northeast region the assessment scientist is responsible for obtaining and wrangling the data for use in their model.

*   This is time consuming 
  *   Many decisions made in the data wrangling process are not uniform across species (data availability, life history)

* Multispecies models (age and length based models) require a similar effort but for many more species.

* Interest centers on the decision making process for wrangling catch data

Goal: Facilitate a reproducible and transparent approach for wrangling multiple species catch data while incorporating many species specific decisions

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## Background: Data wrangling process

* Pull landings data and sampled fish length data

* Aggregate landings, by time, gear type, market code (based on availability of sampled fish)

* Fit length-weight relationships

* Expand the catch to length compositions

* Create age length key

* Calculate numbers at age and length
]

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## Species specific considerations: Rules

Need to recognize differences among species.

* How are market codes aggregated?

* How are landing aggregated temporally? QTR, SEMESTER, ANNUAL?

* What are the rules implemented when length samples are missing?
  * Are there a minimum number of samples required?
  * 200 mt landings for every 100 fish lengths measured?
  * Borrow length sample from which time period? 
  * Nearest neighbor? previous year? previous year same semester? within last 5 years? (based on life history?)

* Is species transient, resident, or resident in portion of the area of interest?

* Time scales for length-weight relationships and age-length keys

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class: ws

## Species specific considerations: Data

* Sources for length-weight data/parameters?
  * From survey and/or commercial?
  * Fit own relationship or use parameters pulled from internal database.
  * How many length-weight relationships are used? QTR, SEMESTER, sex, gear type?

* Sources for discard data?
  * Are length samples available?
  * Add to totals prior to length expansion?

* Sources for age data?
  * From survey and/or commercial?

* Sources of landings and length data?
  * From internal NMFS commercial fisheries database, state data, survey data

* Sources for foreign data?

* Stock area definition? Statistical areas?

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## mscatch as an R package

* Define species specific [rules](https://noaa-edab.github.io/ms-keyrun/articles/GBLandingsByLength.html#rules)
  * How to aggregate catch based on availability of length samples by time
  (Quarterly, Semi annually, Yearly)
  * Associated gear types with fleets
  * Market code relabeling
  * Data sources
  * Define length-weight relationship
  * Define age-length key

* Reproducible method

]

[https://noaa-edab.github.io/mscatch/index.html](https://noaa-edab.github.io/mscatch/index.html)

]

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## A case study: Mackerel

* All gears combined into a single gear type

* Temporal aggregation: semesters (Jan-Jun, Jul-Dec)

* Market codes: 
  * SQ, ES, SV combined to SMALL
  * MD 
  * XG, JB, LG combined into LARGE

* Missing samples: Borrow sample from previous semester within the same market category
  * 5 year average over both semesters
  * market category time series average

* Length-weight relationships: 6 (3 time intervals per semester)
  *   Fitted to bottom trawl data (after QA/QC for anomalous values)

* Age-length data: from Bottom trawl survey and Commercial data. Combine

* Age-length key: By Year
  
* Start date: 1992

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## Species Rules

[https://noaa-edab.github.io/ms-keyrun/articles/GBLandingsByLength.html](https://noaa-edab.github.io/ms-keyrun/articles/GBLandingsByLength.html)

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## Sample output: Gear

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## Sample output: Market codes

--
.pull-right[
<img src="EDAB_images/6a_market_category_lengths.png" width="450px" />

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## Sample output: Temporal

.pull-right[
<img src="EDAB_images/9_market_category_SEMESTER_lengths_pelagic.png" width="450px" />
]

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## Sample output: Length-Weight relationships

.pull-left[
<img src="EDAB_images/length_weight_relationship_ATLANTIC MACKEREL-SEMESTER.png" width="500px" />
]
.pull-right[
<img src="EDAB_images/length_weight_relationship_ATLANTIC MACKEREL-YEAR.png" width="500px" />

]

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class: yf

## To Do

* Data pull from [`comlandr`](https://noaa-edab.github.io/comlandr/) for both landings (domestic + foreign), discards, lengths

* QA/QC code to detect and remove anomalous values

* More flexibility in species options

* Additional diagnostics and figures

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## Walkthrough: Aggregating data

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