Spatial estimates of juvenile Pacific salmon (Oncorhynchus spp.) abundance in the Strait of Georgia

Description:

Spatial information on the distribution of juvenile Pacific salmon is needed to support Marine Spatial Planning in the Pacific Region of Canada. Here we provide spatial estimates of the distribution of juvenile fish in the Strait of Georgia for all five species of Pacific salmon. These estimates were generated using a spatiotemporal generalized linear model and are based on standardized fishery-independent survey data from the Strait of Georgia mid-water juvenile salmon mid-water trawl survey from 2010 to 2020. We provide predicted catch per unit effort (CPUE), year-to-year variation in CPUE, and prediction uncertainty for both summer (June–July) and fall (September–October) at a 0.5 km resolution, covering the majority of the strait. These results show that the surface 75 m of the entire Strait of Georgia is habitat for juvenile salmon from June through early October, but that distributions within the strait differ across species and across seasons. While there is interannual variability in abundances and distributions, our analysis identifies areas that have consistently high abundances across years. The results from this study illustrate juvenile habitat use in the Strait of Georgia for the five species of Pacific salmon and can support ongoing marine spatial planning initiatives in the Pacific region of Canada.

Methods:

Juvenile Salmon Survey Data

This analysis is based on surveys conducted between 2010 and 2020. Sets that lasted between 12 and 50 minutes and at depths less than or equal to 60 m (head rope depth) were included. The resulting survey dataset consists of 1588 sets. The analysis included all five species of Pacific salmon. For pink salmon, only even year surveys were included as they have a two-year life cycle and are effectively absent from the Strait in odd years.

Geostatistical model of salmon abundance and Predictions

We estimated the spatial distribution and abundance of each species of Pacific Salmon using geostatistical models fit with sdmTMB (Anderson et al. 2022). For each species, we modelled the number of individuals caught in a set, at a location and time using a negative binomial observation model with a log link. Predictions were made for each survey season (summer and fall) in each year from 2010 to 2020 over a 500 m by 500 m grid based on a 3 km buffer around the outer concave hull of the trawl coordinates. The concave hull was calculated using the ‘sf_concave_hull’ function from the sf package using a concavity ratio of 0.3, and excluding holes. Predictions were made as catch per unit effort (CPUE, for 60 minutes) for tows conducted in the surface waters (i.e., head rope at 0 m). Continuous estimates are provided at a 0.5 km resolution throughout the Strait of Georgia. These estimates consist of 1) mean catch per unit effort (CPUE), 2) year-to-year coefficient of variation (CV) of CPUE as a measure of the temporal variability, 3) binned biscale measures of mean vs. CV of CPUE to distinguish areas where abundance is consistently high vs. areas where it is high on average, but with high year-to-year variability, and 4) mean standard error in CPUE as a measure of uncertainty.

See Thompson and Neville for full method details.

Uncertainties:

Although the models had relatively low uncertainty and the estimated spatial patterns reflected the spatial and temporal variation in CPUE in the surveys, it is important to understand the limitations of these model predictions. Because juvenile salmon are often aggregated, there is high variability in the CPUE in the survey data. Our model predictions represent the geometric mean CPUE and so are an average expectation, but do not reproduce the high inter-tow variability that is present in the survey data. Spatially, our predictions have low uncertainty in areas that are central within the standard survey track line. However, uncertainty is higher on the margins of the survey area, where there are fewer sets to inform those predictions.

Data Sources:

Juvenile salmon survey database from Salmon Marine Interactions Program, REEFF, ESD, Pacific Biological Station.

Data is also available through Canadian Data Report of Fisheries and Aquatic Sciences publications.

Datasets available for download

• Spatial estimates of juvenile Pacific salmon...TIFF
  To Download

  • More information
  • Go to resource
• Data DictionaryCSV
  To Download

  • More information
  • Go to resource
• Data Dictionary FrenchCSV
  To Download

  • More information
  • Go to resource
• Canadian Technical Report of Fisheries and...PDF
  To Download

  • More information
  • Go to resource
• Spatial estimates of juvenile Pacific salmon...Esri REST
  To Download

  • More information
  • Go to resource
• Spatial estimates of juvenile Pacific salmon...Esri REST
  To Download

  • More information
  • Go to resource

• Aquatic ecosystems
• Environmental management
• Nature and Environment
• Pacific region
• Salt water fish
• Science and Technology
• anadromous
• catch per unit effort cpue
• geostatistical models
• juvenile pacific salmon
• marine spatial planning
• strait of Georgia

Additional Info

• Maturity Level 1 (54%)
• Maturity Level 2 (38%)
• Maturity Level 3 (0%)
• Maturity Level 4 (0%)
• Maturity Level 5 (0%)
• Maturity Level 6 (0%)

Field	Value
Last Updated	October 20, 2025, 02:40 (UTC)
Created	October 20, 2025, 02:40 (UTC)
Domain / Topic Domain or topic of the dataset being cataloged.	Biota
Title Title for the Dataset.	Spatial estimates of juvenile Pacific salmon (Oncorhynchus spp.) abundance in the Strait of Georgia
Description A description of the dataset.	Description: Spatial information on the distribution of juvenile Pacific salmon is needed to support Marine Spatial Planning in the Pacific Region of Canada. Here we provide spatial estimates of the distribution of juvenile fish in the Strait of Georgia for all five species of Pacific salmon. These estimates were generated using a spatiotemporal generalized linear model and are based on standardized fishery-independent survey data from the Strait of Georgia mid-water juvenile salmon mid-water trawl survey from 2010 to 2020. We provide predicted catch per unit effort (CPUE), year-to-year variation in CPUE, and prediction uncertainty for both summer (June–July) and fall (September–October) at a 0.5 km resolution, covering the majority of the strait. These results show that the surface 75 m of the entire Strait of Georgia is habitat for juvenile salmon from June through early October, but that distributions within the strait differ across species and across seasons. While there is interannual variability in abundances and distributions, our analysis identifies areas that have consistently high abundances across years. The results from this study illustrate juvenile habitat use in the Strait of Georgia for the five species of Pacific salmon and can support ongoing marine spatial planning initiatives in the Pacific region of Canada. Methods: Juvenile Salmon Survey Data This analysis is based on surveys conducted between 2010 and 2020. Sets that lasted between 12 and 50 minutes and at depths less than or equal to 60 m (head rope depth) were included. The resulting survey dataset consists of 1588 sets. The analysis included all five species of Pacific salmon. For pink salmon, only even year surveys were included as they have a two-year life cycle and are effectively absent from the Strait in odd years. Geostatistical model of salmon abundance and Predictions We estimated the spatial distribution and abundance of each species of Pacific Salmon using geostatistical models fit with sdmTMB (Anderson et al. 2022). For each species, we modelled the number of individuals caught in a set, at a location and time using a negative binomial observation model with a log link. Predictions were made for each survey season (summer and fall) in each year from 2010 to 2020 over a 500 m by 500 m grid based on a 3 km buffer around the outer concave hull of the trawl coordinates. The concave hull was calculated using the ‘sf_concave_hull’ function from the sf package using a concavity ratio of 0.3, and excluding holes. Predictions were made as catch per unit effort (CPUE, for 60 minutes) for tows conducted in the surface waters (i.e., head rope at 0 m). Continuous estimates are provided at a 0.5 km resolution throughout the Strait of Georgia. These estimates consist of 1) mean catch per unit effort (CPUE), 2) year-to-year coefficient of variation (CV) of CPUE as a measure of the temporal variability, 3) binned biscale measures of mean vs. CV of CPUE to distinguish areas where abundance is consistently high vs. areas where it is high on average, but with high year-to-year variability, and 4) mean standard error in CPUE as a measure of uncertainty. See Thompson and Neville for full method details. Uncertainties: Although the models had relatively low uncertainty and the estimated spatial patterns reflected the spatial and temporal variation in CPUE in the surveys, it is important to understand the limitations of these model predictions. Because juvenile salmon are often aggregated, there is high variability in the CPUE in the survey data. Our model predictions represent the geometric mean CPUE and so are an average expectation, but do not reproduce the high inter-tow variability that is present in the survey data. Spatially, our predictions have low uncertainty in areas that are central within the standard survey track line. However, uncertainty is higher on the margins of the survey area, where there are fewer sets to inform those predictions. Data Sources: Juvenile salmon survey database from Salmon Marine Interactions Program, REEFF, ESD, Pacific Biological Station. Data is also available through Canadian Data Report of Fisheries and Aquatic Sciences publications.
Tags / Keywords Keywords/tags categorizing the dataset.	Aquatic ecosystems Environmental management Nature and Environment Pacific region Salt water fish Science and Technology anadromous catch per unit effort cpue geostatistical models juvenile pacific salmon marine spatial planning strait of Georgia
Format (CSV, XLS, TXT, PDF, etc) File format of the dataset.
Dataset Size Dataset size in megabytes.
Metadata Identifier Metadata identifier – can be used as the unique identifier for catalogue entry
Published Date Published date of the dataset.	2025-01-24
Time Period Data Span (start date) Start date of the data in the dataset.
Time Period Data Span (end date) End date of time data in the dataset.
GeoSpatial Area Data Span A spatial region or named place the dataset covers.

Field	Value
Access category Type of access granted for the dataset (open, closed, service, etc).
License License used to access the dataset.	Open Government Licence - Canada
Limits on use Limits on use of data.
Location Location of the dataset.	https://open.canada.ca/data/en/dataset/46902cbc-4bc2-40f5-bd02-b0111bd2818f
Data Service Data service for accessing a dataset.
Owner Owner of the dataset.	Fisheries and Oceans Canada | Pêches et Océans Canada
Contact Point Who to contact regarding access?	Government of Canada; Fisheries and Oceans Canada; Ecosystems and Ocean Science/Pacific Science/Ecosystem Science Division/Marine Spatial Ecology and Analysis Section, 604-999-3490, [email protected]
Contact Point Email The email to contact regarding access?
Publisher Publisher of the dataset.
Publisher Email Email of the publisher.	[email protected]
Author Author of the dataset.
Author Email Email of the author.
Accessed At Date the data and metadata was accessed.

Field	Value
Identifier Unique identifier for the dataset.
Language Language(s) of the dataset
Link to dataset description A URL to an external document describing the dataset.
Persistent Identifier Data is identified by a persistent identifier.
Globally Unique Identifier Data is identified by a persistent and globally unique identifier.
Contains data about individuals Does the data hold data about individuals?
Contains data about identifiable individuals Does the data hold identifiable data about individual?
Contains Indigenous Data Does the data hold data about Indigenous communities?
Portal Type Platform type of the source portal.

Field	Value
Version Version of the datatset	None
Source Source of the dataset.	None
Version notes Version notes about the dataset.
Is version of another dataset Link to dataset that it is a version of.
Other versions Link to datasets that are versions of it.
Provenance Text Provenance Text of the data.
Provenance URL Provenance URL of the data.
Temporal resolution Describes how granular the date/time data in the dataset is.
GeoSpatial resolution in meters Describes how granular (in meters) geospatial data is in the dataset.
GeoSpatial resolution (in regions) Describes how granular (in regions) geospatial data is in the dataset.

Field	Value
Indigenous Community Permission Who holds the Indigenous Community Permission. Who to contact regarding access to a dataset that has data about Indigenous communities.
Community Permission Community permission (who gave permission).
The Indigenous communities the dataset is about Indigenous communities from which data is derived.

Field	Value
Number of data rows If tabular dataset, total number of rows.
Number of data columns If tabular dataset, total number of unique columns.
Number of data cells If tabular dataset, total number of cells with data.
Number of data relations If RDF dataset, total number of triples.
Number of entities If RDF dataset, total number of entities.
Number of data properties If RDF dataset, total number of unique properties used by the triples.
Data quality Describes the quality of the data in the dataset.
Metric for data quality A metric used to measure the quality of the data, such as missing values or invalid formats.

Please login or register to comment.