herring_recruitment: Pacific Herring annual age-2 recruitments as estimated by the...

In pbs-assess/PACea: An R package of Pacific ecosystem information to help facilitate an ecosystem approach to fisheries management

Pacific Herring annual age-2 recruitments as estimated by the most recent stock assessment, for each of the five major stock assessment regions.

Description

Pacific Herring (Clupea pallasii) abundance in British Columbia is assessed using a Bayesian statistical catch-age model. There are five major herring stock assessment regions: Haida Gwaii (HG), Prince Rupert District (PRD), Central Coast (CC), Strait of Georgia (SoG), and West Coast of Vancouver Island (WCVI). (There are also two minor regions but full stock assessments are not done for those). Results for the five major regions are included in pacea. The most recent assessment is DFO (2024); see that and references within for full details, including the map in Figure 1 that denotes the regions. Note that recruitments are calculated for age-2 fish, and that uncertainty is given by 90% credible intervals, defined as the 5th and 95th percentiles, (whereas the hake recruitments in pacea correspond to age-0 fish and 95% credible intervals, defined as the 2.5 and 97.5 percentiles).

Usage

herring_recruitment

herring_recruitment_2023

Format

A tibble also of class 'pacea_herring_recruitment' with columns:

year:

year of the recruitment estimate for age-2 fish

low:

low end (5th percentile) of the 90% credible interval for recruitment, billions of age-2 fish

median:

median estimate of recruitment, billions of age-2 fish

high:

high end (95th percentile) of the 90% credible interval for recruitment, billions of age-2 fish

An object of class pacea_recruitment_herring (inherits from tbl_df, tbl, data.frame) with 355 rows and 5 columns.

Details

Historical estimates of recruitment and biomass will change from stock assessment to stock assessment, and so we use 'herring_recruitment' to represent the results from the most recent assessment (currently for the status in 2023, with the reference being DFO 2024), and also save these as 'herring_recruitment_2023' so that they will be preserved in future updates of 'pacea'. This is so that you can always refer to a specific set of assessment results (rather than have your analyses change because you have updated 'pacea' and we have replaced 'herring_recruitment' with results from a new assessment). The same holds for the other herring object, namely 'herring_spawning_biomass'; i.e. it is also saved with the assessment year appended.

The 2023 status and results included here are given in DFO (2024):

DFO. 2024. Stock Status Update with Application of Management Procedures for Pacific Herring (Clupea pallasii) in British Columbia: Status in 2023 and Forecast for 2024. DFO Canadian Science Advisory Secretariat Science Response 2024/001. 65 p. https://publications.gc.ca/collections/collection_2024/mpo-dfo/fs70-7/Fs70-7-2024-001-eng.pdf

Author(s)

Andrew Edwards

Source

Generated from Andy running 'data-raw/herring/herring.R', which uses model results provided by Matthew Grinnell.

Examples

## Not run: 
herring_recruitment
plot(herring_recruitment)
plot(herring_recruitment, region = "HG")

## End(Not run)

pbs-assess/PACea documentation built on April 17, 2025, 11:36 p.m.