PURPOSE:These data have been updated following a Canadian Science Advice Secretariat (CSAS) Regional Science Advisory Process. Associated publications are available in the citation section below or will be posted on the Fisheries and Oceans Canada (DFO) Science Advisory Schedule as they become available.Estimate the abundance of Striped bass spawners in the Northwest Miramichi estuary.DESCRIPTION:Spawner abundance estimates of Striped Bass in the Northwest Miramichi estuary based on Catch per unit effort (CPUE) analysis in the commercial gaspereau fishery.USE LIMITATION:To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.

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 DataThis 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 PredictionsWe 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.

PURPOSE:To track juvenile Atlantic salmon densities.DESCRIPTION:Indices of freshwater production are derived annually from electrofishing surveys in the rivers of Nova Scotia flowing into the Gulf of St. Lawrence. Fixed site sampling for juvenile salmon has been conducted most consistently since the mid-1980s for these rivers. Juvenile salmon abundances at sites, in terms of number of fish per habitat area sampled by age or size group (densities), are obtained using successive removal sampling or catch per unit effort sampling calibrated to densities. Sampling intensities vary among years and among rivers. PARAMETERS COLLECTED:distribution (ecological); species counts (ecological); point (spatial)USE LIMITATION:To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.

PURPOSE:From August 1st to September 11th, 2014, Fisheries and Oceans Canada conducted a baseline survey of marine fishes and their habitats in the southern Canadian Beaufort Sea and Amundsen Gulf as part of the Beaufort Regional Environmental Assessment (BREA) called the Beaufort Sea Marine Fishes Project (BSMFP). Sampling was conducted from the F/V Frosti at 54 stations along 14 transects. Standardized sampling was conducted at pre-determined depth stations (20-1500 m) using benthic trawling nets. The BSMFP is the first research project to use large research trawls to assess the biodiversity and abundance of offshore marine fishes in this area. In total, 42 species of fish were caught. This report contains information on fishing net deployments, catch per unit effort (CPUE), and basic biological data for all fishes caught.DESCRIPTION:Basic biological data for all fish caught during the 2014 BSMFP expedition. Includes identification, weight, length (total, fork, and, standard), liver weight, gonad weight, sex and maturity level. PARAMETERS COLLECTED:familyspeciesweighttotal lengthfork lengthstandard lengthliver weightgonad weightsexmaturitySAMPLING METHODS:Various trawl types.

Fisheries landings and effort mapping of the inshore lobster fishery on the DFO Maritimes Region statistical grid (2012-2014). This report describes an analysis of Maritimes Region inshore lobster logbook data reported at a grid level, including Bay of Fundy Grey Zone data reported at the coordinate level. Annual and composite (2012–2014) grid maps were produced for landings, number of license-days fished, number of trap hauls, and the same series standardized by grid area, as well as maps of catch weight per number of trap hauls as an index of catch per unit effort (CPUE). Spatial differences in fishing pressure, landings, and CPUE are indicated, and potential mapping applications are outlined. Mapping the distribution and intensity of inshore lobster fishing activity has management applications for spatial planning and related decision support. The lack of region-wide latitude and longitude coordinates for lobster effort and landings limits the utility of commercial logbook data for marine spatial planning purposes.

PURPOSE:"Biological, relative abundance, and environmental data have been collected from the Yellowknife River Cisco population that can be used to inform fisheries management decision-making. Under the conditions of a commercial licence issued under the New Emerging Fisheries Policy, licence holders are required to record catch and biological information to support the assessment of the feasibility and sustainability of the fishery over time, and potential advancement in the stages of a developing fishery. In addition to the information collected from the commercial harvest (fishery-dependent), a fishery-independent sampling and snorkel survey program was conducted with the objective of collecting additional biological, observational, and environmental data during the fall spawning run.The objective of this report is to compile available data from fishery-dependent and fishery-independent sampling of adfluvial Yellowknife River Cisco during fall, 1998-2020*, specifically by:• Summarizing commercial fishery quotas and reported harvest;• Characterizing population demographics and examining for trends over time;• Summarizing metrics of relative abundance (i.e., catch-per-unit-effort data and snorkel survey observations) and examining for trends over time; and• Determining if there were any associations between relative abundance of Cisco and river discharge and temperature. *A commercial harvest occurred in 1998, although no biological or catch-effort records were located. In addition, in response to concerns about the status of the population, the fishery was put on hold 2006–2009 to allow for a population assessment (no data during that time). DESCRIPTION:Cisco (Coregonus artedi) from the Yellowknife River, Northwest Territories, are an important fishery resource for nearby communities. Biological, catch-effort, and environmental data were collected from the Yellowknife River (Tartan Rapids and Bluefish areas) during their fall spawning run from Great Slave Lake. Data from the commercial harvest (fishery-dependent; 1998–2020) and supplementary monitoring (fishery-independent; 2013–2020) of these adfluvial Cisco were compiled to summarize commercial fishery quotas and reported harvest, characterize population demographics and catch-effort over time, and assess potential associations between relative abundance and seasonal river characteristics. A single commercial fishing licence for Cisco was issued on an annual basis each fall for 1,000 kg from 1998–2002, 2,000 kg from 2004–2005, 1,000 kg from 2010–2018, and 1,500 kg from 2019–2020. Cisco ranged from 102–239 mm fork length, 10.0–139.6 g round weight, and 1 and 9 years of age, with the majority of fish (>99%) being sexually mature. The demographics (length, weight, age) of the spawning population collected from the commercial fishery remained relatively stable between 1999 and 2020. Catch-effort of the commercial fishery varied widely among years without trend, although this was not standardized to the number of individuals/nets used to capture the fish. The biological, catch-effort, and environmental data collected from the Yellowknife River spawning population of Cisco serve as a benchmark for their ongoing assessment and management.

PURPOSE:This data relates to the Canadian Science Advice Secretariat (CSAS) Regional Science Advisory Process from the Limit Reference Point and Population Model Review of the Southern Gulf of Saint Lawrence Sea Scallop peer review meeting held on November 1-2, 2023. The SFAs 22 and 24 have been identified as the core scallop habitat within the sGSL for this process. Associated publications from this meeting will be posted on the Fisheries and Oceans Canada (DFO) Science Advisory Schedule as they become available. DESCRIPTION:Data on landings, fishing efforts, and catch per unit effort (CPUE) used in the stock assessment for southern Gulf of St. Lawrence (sGSL) sea scallop (_Placopecten magellanicus_) stock assessments and the limit reference point.The dataset contains corrected information from the following data sources:- DFO annual historic reports on landings and efforts- published documents about population assessments and surveys- logbooks, produced by DFO’s regional statistics- purchase slips, produced by DFO’s regional statistics- Catch per unit effort calculated by DFO's Science BranchPrior to 1947, data represents the combined landings that cannot be attributed to individual Scallop Fishing Areas (SFAs). USE LIMITATION:To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.

Point layer of the registration points (centroids) of the evaluation units of the graphic matrix.**Collection context** Update provided by the evaluator or evaluation department.**Collection method** Computer-aided mapping.**Attributes*** `ID` (`integer`): Identifier* `ADM01A` (`varchar`): Municipality code* `SI0317A` (`smalldatetime`): Registration date* `SI0317B` (`integer`): Representation scale* `SI0317C` (`varchar`): Registration* `SI0317D` (`varchar`): Location* `SI0102C` (`varchar`): Section* `SI0103C` (`varchar`): Division* `UNIT_V` (`varchar`): Neighborhood unit* `NOTES` (`varchar`): Notes* `DATE_CREATION` (`smalldatetime`): Creation date* `DATE_MODIFICATION` (`smalldatetime`): Date of modification* `USER_MODIFICATION` (`varchar`): Modified byFor more information, consult the metadata on the Isogeo catalog (OpenCatalog link).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Biogeoclimatic Ecosystem Classification (BEC) subzone\variant\phase boundaries with percent protected, number of overlapping protected areas and other attributes added as a result of geoprocessing in the Protected Area System Overview (PASO) application. Protected area and park representation by BEC unit provides a small scale ecosystem classification context for natural resource planning processes such as; management plans, land use zoning, environmental risk assessment, landscape analysis, habitat supply, and management of high priority species. Biogeoclimatic subzones are the basic unit of the BEC system. Subzones are grouped into biogeoclimatic zones to create more generalized units, and subdivided into biogeoclimatic variants and phases to create more specific or climatically homogeneous units. For more information on the BEC system see: http://www.for.gov.bc.ca/hre/becweb/. For important warnings about using this data for spatial analysis see the Data Quality section of the metadata

This report describes an analysis of Maritimes Region inshore lobster logbook data reported at a grid level, including Bay of Fundy Disputed Zone data reported at the coordinate level. Annual and composite (2015–2019) grid maps were produced for landings, number of trap hauls, and the same series standardized by grid area, as well as maps of catch weight per number of trap hauls as an index of catch per unit effort (CPUE). Spatial differences in fishing pressure, landings, and CPUE are indicated, and potential mapping applications are outlined. Mapping the distribution and intensity of inshore lobster fishing activity has management applications for spatial planning and related decision support. The lack of region-wide latitude and longitude coordinates for inshore lobster effort and landings limits the utility of commercial logbook data for marine spatial planning purposes.