Arctic SDI catalogue
Colombie-Britannique
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This dataset displays the geographic areas within which critical habitat for species at risk listed on Schedule 1 of the federal Species at Risk Act (SARA) occurs in British Columbia. However, not all of the area within these boundaries is necessarily critical habitat. To precisely define what constitutes critical habitat for a particular species it is essential that this geo-spatial information be considered in conjunction with complementary information provided in a species’ recovery document. Recovery documents are available from the Species at Risk (SAR) Public Registry (http://www.sararegistry.gc.ca). The recovery documents contain important information about the interpretation of the geo-spatial information, especially regarding the biological and environmental features (“biophysical attributes”) that complete the definition of a species’ critical habitat.. Each species’ dataset is part of a larger collection of critical habitat data that is available for download. The collection includes both “final” and “proposed” critical habitat as it is depicted in the recovery documents. “Proposed” critical habitat depicted in proposed recovery documents has not been formally identified and is subject to change before it is posted as final. Despite the use of the term “final”, it is important to note that recovery documents (and therefore critical habitat) may be amended from time to time. Species are added as the data becomes ready, which may occur after the recovery document has been posted on the SAR Public Registry. You should always consider the SAR Public Registry as the main source for critical habitat information. In cases where the data is sensitive (e.g. species noted in the List of Species and Ecosystems Susceptible to Persecution or Harm that are managed by the Province of British Columbia), the geographic area within which critical habitat occurs may be represented as “grid squares”. These are coarse (1, 10, 50 or 100 km2) squares based on a UTM grid that serve as a flag to review the associated species’ recovery document. To reiterate, not all of the area within these boundaries is necessarily critical habitat. Critical habitat is defined in the federal Species at Risk Act (SARA) as “the habitat that is necessary for the survival or recovery of a listed wildlife species and that is identified as the species’ critical habitat in the recovery strategy or action plan for the species”. Critical habitat identification alone is not an automatic “protection” designation. Federal or non-federal laws or bylaws may be in place to provide protection. / Cet ensemble de données présente les zones géographiques au sein desquelles l’habitat essentiel d’espèces en péril inscrites à l’annexe 1 de la Loi sur les espèces en péril (LEP) du Canada est présent en Colombie-Britannique. Toutefois, l’ensemble d’une zone en particulier ne fait pas nécessairement partie de l’habitat essentiel. Afin de déterminer avec précision l’habitat essentiel d’une espèce donnée, il est crucial de considérer ces données géospatiales conjointement avec des renseignements supplémentaires contenus dans le document de rétablissement de l’espèce. Les documents de rétablissement peuvent être téléchargés à partir du Registre public des espèces en péril (http://www.sararegistry.gc.ca). Ces documents renferment des renseignements importants sur l’interprétation de l’information géospatiale, particulièrement en ce qui concerne les caractéristiques biologiques et environnementales (« attributs biophysiques ») qui complètent la définition de l’habitat essentiel d’une espèce. L’ensemble de données de chacune des espèces fait partie d’un ensemble de données plus vaste sur l’habitat essentiel, qui est téléchargeable. Cet ensemble de données indique à la fois l’habitat essentiel « proposé » et l’habitat essentiel « final », tels qu’ils sont décrits dans les documents de rétablissement. L’habitat essentiel « proposé » dans une proposition de document de rétablissement n’est pas désigné de manière officielle et pourrait être modifié avant la publication de la version définitive du document de rétablissement. Malgré l’utilisation du terme « définitif », il est important de mentionner que les documents de rétablissement (et, par conséquent, l’habitat essentiel) sont appelés à être modifiés à l’occasion. Des espèces sont ajoutées à mesure que de nouvelles données sont disponibles, ce qui peut se produire après la publication du document de rétablissement dans le Registre public des espèces en péril. Ce Registre doit toujours être considéré comme étant la principale source de renseignements sur l’habitat essentiel. Dans les cas où les données sont sensibles (p. ex. espèces figurant dans la liste « Species and Ecosystems Susceptible to Persecution or Harm » [espèces et écosystèmes exposés à des risques de persécution ou de préjudice] gérées par la Colombie-Britannique), la zone géographique qui contient l’habitat essentiel peut être représentée par des « carrés au sein d’un quadrillage ». Ces carrés grossiers (de 1, 10, 50 ou 100 km2) fondés sur un quadrillage UTM servent d’indicateurs pour l’examen du document de rétablissement de l’espèce pertinente. Encore une fois, l’ensemble d’une zone en particulier ne fait pas nécessairement partie de l’habitat essentiel. L’habitat essentiel est défini dans la Loi sur les espèces en péril (LEP) fédérale comme étant « l’habitat nécessaire à la survie ou au rétablissement d’une espèce sauvage inscrite, qui est désigné comme tel dans un programme de rétablissement ou un plan d’action élaboré à l’égard de l’espèce ». La désignation seule d’habitat essentiel ne donne pas lieu automatiquement à une désignation de « protection ». Des lois fédérales ou non fédérales ou des règlements administratifs peuvent être en place pour offrir une protection.
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Herring Section shapefile - used for spatial analysis/presentation of data from Herring Stock Assessment Database.
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Description: These commercial whale watching data are comprised of two datasets. First, the ‘whale_watching_trips_jun_sep_british_columbia’ data layer summarizes commercial whale watching trips that took place in 2019, 2020 and 2021 during the summer months (June to September). The second data layer, ‘wildlife_viewing_events_jun_sep_british_columbia’ contains estimated wildlife viewing events carried out by commercial whale watching vessels for the same years (2019, 2020 and 2021) and months (June to September). Commercial whale watching trips and wildlife viewing events are summarized using the same grid, and they can be related using the unique cell identifier field ‘cell_id’. The bulk of this work was carried out at University of Victoria and was funded by the Marine Environmental Observation, Prediction and Response (MEOPAR) Network under the ‘Whale watching AIS Vessel movement Evaluation’ or WAVE project (2018 – 2022). The aim of the WAVE project was to increase the understanding of whale watching activities in Canada’s Pacific region using vessel traffic data derived from AIS (Automatic Identification System). The work was finalized by DFO Science in the Pacific Region. These spatial data products of commercial whale watching operations can be used to inform Marine Spatial Planning, conservation planning activities, and threat assessments involving vessel activities in British Columbia. Methods: A list of commercial whale watching vessels based in British Columbia and Washington State and their corresponding MMSIs (Maritime Mobile Service Identity) was compiled from the whale watching companies and Marine Traffic (www.marinetraffic.com). This list was used to query cleaned CCG AIS data to extract AIS positions corresponding to commercial whale watching vessels. A commercial whale watching trip was defined as a set of consecutive AIS points belonging to the same vessel departing and ending in one of the previously identified whale watching home ports. A classification model (unsupervised Hidden Markov Model) using vessel speed as the main variable was developed to classify AIS vessel positions into wildlife-viewing and non wildlife viewing events. Commercial whale watching trips in the south and north-east of Vancouver Island were limited to a duration of minimum 1 hour and maximum 3.5 hours. For trips in the west coast of Vancouver island the maximum duration was set to 6 hours. Wildlife-viewing events duration was set to minimum of 10 minutes to a maximum of 1 hour duration. For more information on methodology, consult metadata pdf available with the Open Data record. References: Nesdoly, A. 2021. Modelling marine vessels engaged in wildlife-viewing behaviour using Automatic Identification Systems (AIS). Available from: https://dspace.library.uvic.ca/handle/1828/13300. Data Sources: Oceans Network Canada (ONC) provided encoded AIS data for years 2019, 2020 and 2021, within a bounding box including Vancouver Island and Puget Sound used to generate these products. This AIS data was in turn provided by the Canadian Coast Guard (CCG) via a licensing agreement between the CCG and ONC for the non-commercial use of CCG AIS Data. More information here: https://www.oceannetworks.ca/science/community-based-monitoring/marine-domain-awareness-program/ Molly Fraser provided marine mammal sightings data collected on board a whale watching vessels to develop wildlife-viewing events classification models. More information about this dataset here: https://www.sciencedirect.com/science/article/pii/S0308597X20306709?via%3Dihub Uncertainties: The main source of uncertainty is with the conversion of AIS point locations into track segments, specifically when the distance between positions is large (e.g., greater than 1000 meters).
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Herring biological (fish and sample) data as part of Herring Stock Assessment database
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Herring Permanent Spawn Transects (geodatabase) - used for herring spawn survey program and spatial analysis/presentation of spawn data from Herring Stock Assessment Database (including creation of spawn polygons).
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The __Counties of British Columbia__ contains areas of land within the Province of British Columbia representing legally defined administrative areas described in the County Boundary Act. The purpose of this division is for the administration of justice. The counties were delineated using provincial base mapping features, following the metes and bounds descriptions in the Letters Patent. A polygon dataset that includes all of the administrative areas currently in the __Administrative Boundaries Management System (ABMS)__ is available [here](https://catalogue.data.gov.bc.ca/dataset/legally-defined-administrative-areas-of-bc). A complimentary point dataset that defines the administrative areas is also available [here](https://catalogue.data.gov.bc.ca/dataset/legally-defined-administrative-areas-of-bc-boundary-locations). The Legal document which divides the province of British Columbia into counties is available [here](http://www.bclaws.ca/civix/document/id/complete/statreg/96075_01). Other individual datasets are available from the following records: https://catalogue.data.gov.bc.ca/dataset/province-of-british-columbia-legally-defined-administrative-areas-of-bc https://catalogue.data.gov.bc.ca/dataset/municipalities-legally-defined-administrative-areas-of-bc https://catalogue.data.gov.bc.ca/dataset/regional-districts-legally-defined-administrative-areas-of-bc https://catalogue.data.gov.bc.ca/dataset/electoral-areas-legally-defined-administrative-areas-of-bc https://catalogue.data.gov.bc.ca/dataset/islands-trust-legally-defined-administrative-areas-of-bc https://catalogue.data.gov.bc.ca/dataset/local-trust-areas-legally-defined-administrative-areas-of-bc https://catalogue.data.gov.bc.ca/dataset/sh-sh-lh-nation-legally-defined-administrative-areas-of-bc
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Description: Data on recreational boating are needed for marine spatial planning initiatives in British Columbia (BC). Vessel traffic data are typically obtained by analyzing automatic identification system (AIS) vessel tracking data, but recreational vessels are often omitted or underrepresented in AIS data because they are not required to carry AIS tracking devices. Transport Canada’s National Aerial Surveillance Program (NASP) conducted aerial surveys to collect information on recreational vessels along several sections of the BC coast between 2018 and 2022. Recreational vessel sightings were modeled against predictor variables (e.g., distance to shore, water depth, distance to, and density of marinas) to predict the number of recreational vessels along coastal waters of BC. The files included here are: --A Geodatabase (‘Recreational_Boating_Data_Model’), which includes: (1) recreational vessel sightings data collected by NASP in BC and used in the recreational vessel traffic model (‘Recreational_Vessels_PointData_BC’); (2) aerial survey effort (or number of aerial surveys) raster dataset (‘surveyeffort’); and (3) a vector grid dataset (2.5 km resolution) containing the predicted number of recreational vessels per cell and predictor variables (‘Recreational_Boating_Model_Results_BC). --Scripts folder which includes R Markdown file with R code to run the modelling analysis (‘Recreational_Boating_Model_R_Script’) and data used to run the code. Methods: Data on recreational vessels were collected by NASP during planned aerial surveys along pre-determined routes along the BC coast from 2018 to 2022. Data on non-AIS recreational vessels were collected using video cameras onboard the aircraft, and data on AIS recreational vessels using an AIS receiver also onboard the aircraft. Recreational boating predictors explored were: water depth, distance to shore, distance to marinas, density of marinas, latitude, and longitude. Recreational vessel traffic models were fitted using Generalized Linear Models (GLM) R packages and libraries used here include: AED (Roman Lustrik, 2021) and MASS (Venables, W. N., Ripley, 2002), pscl package (Zeileis, Kleiber, and Jackman, 2008) for zeroinfl() and hurdle() function. Final model was selected based on the Akaike’s information criterion (AIC) and the Bayes’ information criterion (BIC). An R Markdown file with code use to run this analysis is included in the data package in a folder called Script. Spatial Predictive Model: The selected model, ZINB, consist of two parts: one with a binomial process that predicts the probability of encountering a recreational vessel, and a second part that predicts the number of recreational vessels via a count model. The closer to shore and to marinas, and the higher the density of marinas, the higher the predicted number of recreational vessels. The probability of encountering recreational vessels is driven by water depth and distance to shore. For more information on methodology, consult metadata pdf available with the Open Data record. References: Serra-Sogas, N. et al. 2021. Using aerial surveys to fill gaps in AIS vessel traffic data to inform threat assessments, vessel management and planning. Marine Policy 133: 104765. https://doi.org/10.1016/j.marpol.2021.104765 Data Sources: Recreational vessel sightings and survey effort: Data collected by NASP and analyzed by Norma Serra to extract vessel information and survey effort (more information on how this data was analyzed see SerraSogas et al, 2021). Bathymetry data for the whole BC coast and only waters within the Canadian EEZ was provided by DFO – Science (Selina Agbayani). The data layer was presented as a raster file of 100 meters resolution. Coastline dataset used to estimate distance to shore and to clip grid was provided by DFO – Science (Selina Agbayani), created by David Williams and Yuriko Hashimoto (DFO – Oceans). Marinas dataset was provided by DFO – Science (Selina Agbayani), created by Josie Iacarella (DFO – Science). This dataset includes large and medium size marinas and fishing lodges. The data can be downloaded from here: Floating Structures in the Pacific Northwest - Open Government Portal (https://open.canada.ca/data/en/dataset/049770ef-6cb3-44ee-afc8-5d77d6200a12) Uncertainties: Model results are based on recreational vessels sighted by NASP and their related predictor variables and not always might reflect real-world vessel distributions. Any biases caused by the opportunistic nature of the NASP surveys were minimized by using survey effort as an offset variable.
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The __shíshálh Nation__ contains legally defined areas of land within the Province of British Columbia over which the shíshálh Nation exercises self-government, including the administration of resources and services available to its members, as described in the shíshálh Nation Self-Government Act of 1986. This spatial layer contains multipart features. Note that the name of the spatial layer is outdated; after the notification of retirement of the layer has been circulated the dataset will be recreated with the correct name. The source data for the geometry of the parcels was the federal "GeoBase - Aboriginal Lands" dataset, available under OGL - Canada. Parcels were adjusted to match provincial base mapping features, following the metes and bounds descriptions in the Letters Patent. A polygon dataset that includes all of the administrative areas currently in the __Administrative Boundaries Management System (ABMS)__ is available [here](https://catalogue.data.gov.bc.ca/dataset/legally-defined-administrative-areas-of-bc). A complimentary point dataset that defines the administrative areas is also available [here](https://catalogue.data.gov.bc.ca/dataset/legally-defined-administrative-areas-of-bc-boundary-locations). The shíshálh Nation Government District Enabling Act, [RSBC 1996] CHAPTER 416 is available [here.](http://www.bclaws.ca/civix/document/id/complete/statreg/96416_01) Other individual datasets are available from the following records: https://catalogue.data.gov.bc.ca/dataset/province-of-british-columbia-legally-defined-administrative-areas-of-bc https://catalogue.data.gov.bc.ca/dataset/municipalities-legally-defined-administrative-areas-of-bc https://catalogue.data.gov.bc.ca/dataset/regional-districts-legally-defined-administrative-areas-of-bc https://catalogue.data.gov.bc.ca/dataset/electoral-areas-legally-defined-administrative-areas-of-bc https://catalogue.data.gov.bc.ca/dataset/islands-trust-legally-defined-administrative-areas-of-bc https://catalogue.data.gov.bc.ca/dataset/local-trust-areas-legally-defined-administrative-areas-of-bc
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Survey data depicting the presence of the endangered Rocky Mountain Ridged Mussel (Gonidea angulata) from 2008-2011. Surveys were conducted by different researchers at different locations.
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A literature review, focusing on oil sand products (e.g., diluted bitumen), diluents, spill-treating agents, and crude oil toxicology and ecological studies, relevant to the northeast Pacific was compiled as part of the Government of Canada’s World Class Tanker Safety program. Of the 763 references identified, 14 involved diluted bitumen and other heavy crude oils, indicating the need for further research of these products in the marine environment. Diluent research suggests relatively fast evaporation and dispersion times for this component, however high toxicities may pose a threat to marine biota. Historical studies indicate older dispersant formulations had potential ecological implications, therefore newer formulations, which have not been studied in detail, require full assessment. Consistent utilization of toxicology standards remains elusive, hindering species sensitivity analyses. Exxon Valdez literature demonstrates highly variable impacts from a single oil type and the need for baseline data, recovery status, and suitable ecological end-point determination.