24 Forage Fish Indices
Description: Forage fish biomass and center of gravity indices
Found in: State of the Ecosystem - Gulf of Maine & Georges Bank (2023+), State of the Ecosystem - Mid-Atlantic (2023+)
Indicator category: Extensive analysis, Published methods
Contributor(s): Sarah Gaichas, James Gartland, Brian Smith, Elizabeth Ng, Michael Celestino, Anthony Wood, Katie Drew, Abigail Tyrell, and James Thorson
Data steward: Sarah Gaichas, Sarah.Gaichas@noaa.gov
Point of contact: Sarah Gaichas, Sarah.Gaichas@noaa.gov
Public availability statement: Source data are publicly available. All data and code available on GitHub at https://github.com/NOAA-EDAB/forageindex
24.1 Methods
Forage fish indices were developed in support of the Bluefish Research Track stock assessment working group in 2022 and extended for the 2023 and subsequent State of the Ecosystem reports. Key methods are briefly reported here. Detailed methods, results, and model diagnostics are available in Gaichas et al. (2023).
Small pelagic forage species are difficult to survey directly, so we developed a novel method of assessing small pelagic fish aggregate abundance using predator diet data. We used piscivore diet data collected from multiple bottom trawl surveys within a Vector Autoregressive Spatio-Temporal (VAST, Thorson and Barnett (2017); Thorson (2019)) model to assess trends of small pelagic forage species on the Northeast US shelf. This approach uses survey-sampled predator stomach contents as observations to develop a survey index for forage fish, following Ng et al. (2021), which used predator stomach data to create a biomass index for a single prey, Atlantic herring.
We adapted the approach of Ng et al. (2021) to get an index for small pelagics in aggregate rather than a single prey species. We include inshore and offshore regions by combining results across two regional bottom trawl surveys surveys, the Northeast Fisheries Science Center (NEFSC) survey and the Northeast Area Monitoring and Assessment Program (NEAMAP) survey, as was done for summer flounder biomass in Perretti and Thorson (2019). Finally, we aggregate all predators that have a similar diet composition to bluefish to better represent generalist pelagic piscivore prey (“forage fish”) biomass.
Minor changes to the prey included in the forage index were made between the Bluefish Research Track/2023 SOE and the index published in Gaichas et al. (2023) and used in the 2024 SOE. A comparison of these methods, and of the index extended back in time to the 1970s and 1980s, is presented at https://noaa-edab.github.io/forageindex/SOEforageindex.html.
24.1.1 Data sources
Data used to develop this indicator comes from multispecies diet data collected on the Northeast Fisheries Science Center (NEFSC) and NorthEast Area Monitoring and Assessment Program (NEAMAP) bottom trawl surveys. Sea Surface Temperature (SST) data were used from in situ NEFSC and NEAMAP survey in-situ collections, as well as NOAA High Resolution SST data (Optimal Interpolation Sea Surface Temperature- OISST, Reynolds et al. (2007)), provided by the NOAA/OAR/ESRL PSL, Boulder, Colorado, USA, from their Web site at https://psl.noaa.gov/data/gridded/data.noaa.oisst.v2.highres.html. This is the same source data used in seasonal SST anomaly analyses.
24.1.2 Data extraction
NEFSC survey diet data were extracted and provided by Brian Smith (NEFSC). NEAMAP survey diet data were extracted and processed by James Gartland (VIMS). Code to extract the OISST information was modified from code kindly provided by Kim Bastille pulling daily gridded SST for each year 1985-2021 using her code starting line 260, as well as Kim’s nc_to_raster function for NEUS shelf from at this link. The full OISST extraction script is available at this link with visualizations of survey in-situ temperatures compared with OISST at this link
24.1.3 Data analysis
The steps involved to estimate the forage index included defining the input dataset, and running multiple configurations of the VAST model. Steps involved in defining the dataset included defining “bluefish prey”, defining a set of piscivore predators with similar diets to bluefish, integrating diet data from two regional surveys, and integrating supplementary SST data to fill gaps in in-situ temperature data measurements. Steps involved in running the VAST model included decisions on spatial footprint, model structure, model selection to determine if spatial and spatio-temporal random effects were supported by the data, and further model selection to determine which catchability covariates were best supported by the data. Finally, subsets of the spatial domain were defined to match bluefish assessment inputs (survey and recreational fishery CPUE) for potential use as covariates in bluefish stock assessment models, and a bias-corrected (Thorson and Kristensen 2016) forage index for each spatial subset was generated.
24.1.3.1 Forage fish in bluefish diets
Prey categories such as fish unidentified, Osteichthyes, and unidentified animal remains were not included in the prey list. Although unidentified fish and Osteichthyes can comprise a significant portion of bluefish stomach contents, we cannot assume that unidentified fish in other predator stomachs represent unidentified fish in bluefish stomachs.
24.1.3.1.1 2024+ SOE
Using NEFSC (1973-2021), and NEAMAP (2007-2021) survey diet data, 21 small pelagic prey groups were identified with at least 25 bluefish stomachs across both datasets. Atlantic mackerel were also included despite being encountered in only 14 stomachs, due to their historic importance as bluefish prey (Collette and Klein-Macphee 2002).
Sensitivity of index results to changes in the prey groups is reported in Gaichas et al. (2023). Trends were not sensitive to the minor change in prey inclusion between this method and the one used in the 2023 SOE.
24.1.3.1.2 2023 SOE
Using NEFSC bottom trawl survey diet data from 1973-2021, 20 small pelagic groups were identified as major bluefish prey with 10 or more observations (in descending order of observations): Longfin squids (Doryteuthis formerly Loligo sp.), Anchovy family (Engraulidae), bay anchovy (Anchoa mitchilli), Atlantic butterfish, (Peprilus triachanthus), Cephalopoda, (Anchoa hepsetus), red eye round herring (Etrumeus teres), Sandlance (Ammodytes sp.), scup (Stenotomus chrysops), silver hake (Merluccius bilinearis), shortfin squids (Illex sp.), Atlantic herring (Clupea harengus), Herring family (Clupeidae), Bluefish (Pomatomus saltatrix), silver anchovy (Engraulis eurystole), longfin inshore squid (Doryteuthis pealeii), Atlantic mackerel (Scomber scombrus), flatfish (Pleuronectiformes), weakfish (Cynoscion regalis), and Atlantic menhaden (Brevoortia tyrannus).
24.1.3.2 Predators feeding similarly to bluefish
All size classes of 50 fish predators captured in the NEFSC bottom trawl survey were grouped by diet similarity to identify the size classes of piscivore species with the most similar diet to bluefish in the region. Diet similarity analysis was completed using the Schoener similarity index (Schoener (1970); B. Smith, pers. comm.), and is available available via this link on the NEFSC food habits shiny app. The working group evaluated several clustering methods to develop the predator list (see this link with detailed cluster results).
Predators with highest diet similarity to Bluefish from the NEFSC diet database (1973-2020) include Atlantic cod, Atlantic halibut, buckler dory, cusk, fourspot flounder, goosefish, longfin squid, shortfin squid, pollock, red hake, sea raven, silver hake, spiny dogfish, spotted hake, striped bass, summer flounder, thorny skate, weakfish, and white hake. The NEAMAP survey operates closer to shore than the current NEFSC survey. The NEAMAP dataset includes predators sampled by the NEFSC survey and adds two species, Spanish mackerel and spotted sea trout, not captured by the NEFSC survey offshore but included based on working group expert judgement of prey similarity to bluefish. Predator size classes included are listed in Table 2 of Gaichas et al. (2023) at https://cdnsciencepub.com/doi/full/10.1139/cjfas-2023-0093.
24.1.3.3 VAST Input Dataset
Diets from all 22 piscivores (including bluefish) were combined for the 21 forage fish (bluefish prey) groups at each surveyed location, and the mean weight of forage fish per predator stomach at each location was calculated. Data for each station included station ID, year, season, date, latitude, longitude, vessel, mean bluefish prey weight (g), mean piscivore length (cm), number of piscivore species, and sea surface temperature (degrees C). Because approximately 10% of survey stations were missing in-situ sea water temperature measurements, National Oceanic and Atmospheric Administration Optimum Interpolation Sea Surface Temperature (NOAA OI SST) V2 High Resolution Dataset (Reynolds et al. 2007) data provided by the NOAA PSL, Boulder, Colorado, USA, from their website at https://psl.noaa.gov were used to fill gaps. For survey stations with in-situ temperature measurements, the in-situ measurement was retained. For survey stations with missing temperature data, OI SST was substituted for input into VAST models.
The 2023 SOE dataset input to VAST is available at this link.
Operational updates to the forage index submitted to the State of the Ecosystem report (2024+) are in the forageindex github repository: https://github.com/NOAA-EDAB/forageindex
Data input files are in the folder fhdat and were processed with the script VASTforage_ProcessInputDat.R in that folder: https://github.com/NOAA-EDAB/forageindex/blob/main/fhdat/VASTforage_ProcessInputDat.R
The 2024 SOE dataset input to VAST is available at this link.
24.1.3.4 VAST modeling
Approaches, model selection, and bias correction are described in detail in Gaichas et al. (2023).
VAST models were run using the script VASTunivariate_seasonalforageindex_operational.R in the folder VASTscripts: https://github.com/NOAA-EDAB/forageindex/blob/main/VASTscripts/VASTunivariate_seasonalforageindex_operational.R
Model output was saved in the folder SOEpyindex for three different time series options: 1973-2022, 1982-2022, and 1985-2022.
24.1.3.5 Spatial Forage Indices
The script to create the 2024+ SOE forage indices from the VAST output is in the SOEpyindex folder: https://github.com/NOAA-EDAB/forageindex/blob/main/SOEpyindex/SOE-VASTForageIndices.R
24.1.3.6 Forage Center of Gravity
Center of Gravity is a standard output of VAST models. Forage center of gravity indices were introduced in the 2024 SOE from the same model as the forage indices. Code to extract the center of gravity output is at https://noaa-edab.github.io/forageindex/SOEforageindex.html#5_Center_of_gravity_exploration, along with visualizations of the center of gravity indicator for spring and fall models.
catalog link https://noaa-edab.github.io/catalog/forage_index.html