The West Africa Coastal Vulnerability Mapping: Population Projections, 2030 and 2050 data set is based on an unreleased working version of the Gridded Population of the World (GPW), Version 4, year 2010 population count raster but at a coarser 5 arc-minute resolution. Bryan Jones of Baruch College produced country-level projections based on the Shared Socioeconomic Pathway 4 (SSP4). SSP4 reflects a divided world where cities that have relatively high standards of living, are attractive to internal and international migrants. In low income countries, rapidly growing rural populations live on shrinking areas of arable land due to both high population pressure and expansion of large-scale mechanized farming by international agricultural firms. This pressure induces large migration flow to the cities, contributing to fast urbanization, although urban areas do not provide many opportUnities for the poor and there is a massive expansion of slums and squatter settlements. This scenario may not be the most likely for the West Africa region, but it has internal coherence and is at least plausible.

These data include the general extents of canopy-forming kelp surveys from 1989 to 2014 and a compilation of existing data sets delineating canopy-forming kelp beds along the coasts of Washington, Oregon, and California. Canopy-forming kelp includes species of the genera Nereocystis (bull kelp) and Macrocystis (giant kelp). It does not include the understory kelp genera, such as Laminaria or Alaria. The source data were created from remote-sensing surveys (aerial photos and digital imagery) which often used different survey methods from area to area or year to year. The data depict all kelp observations from all surveys, merged into continuous polygons with the internal boundaries removed (dissolved). This depiction is sometimes referred to as the "maximum extent." Different sections of the coast have been surveyed during different time periods. The number of surveys per section of coast ranges from 1 to 25 surveys. The kelp survey extent data depict the general sections of coastline that were surveyed, how many times they were surveyed, the years of the survey, and which source data were included in the final kelp data compilation.

The National Marine Sanctuary Program (NMSP) updates and revises the management plans for each of its 13 sanctuaries. This process, which is open to the public, enables each site to revisit the reasons for sanctuary designation and assess whether they are meeting their goals, as well as to set new goals consistent with the mandates of the National Marine Sanctuaries Act. Issues raised by the public during this process are evaluated and a determination is made as to whether they will be incorporated into the updated plan. Many of these issues focus on topics such as the implementation of marine zoning or sanctuary boundary adjustments, both of which require information on the distribution of resources within and around the sanctuary. Recognizing this, NMSP and NOAA?s National Centers for Coastal Ocean Science (NCCOS) formalized an agreement to collaborate in the revision process by developing such information through a series of biogeographic assessments conducted in selected sanctuaries. The resulting products are then supplied to sanctuary managers and staff for use in the policy and decision making process. This collaborative effort began along the west coast of the U.S. with the Cordell Bank, Gulf of Farallones, and Monterey Bay national marine sanctuaries, and is herein centered on the Channel Islands National Marine Sanctuary (CINMS).

The dataset includes age- and length-based catch per unit effort data for commercial fish species collected during the Scottish West Coast Bottom Trawl Survey. This is a new survey from 2011, replacing the historical DATRAS SWC-IBTS dataset

Humanity's role in changing the face of the earth is a long-standing concern, as is the human domination of ecosystems. Geologists are debating the introduction of a new geological epoch, the 'anthropocene', as humans are 'overwhelming the great forces of nature'. In this context, the accumulation of artefacts, i.e., human-made physical objects, is a pervasive phenomenon. Variously dubbed 'manufactured capital', 'technomass', 'human-made mass', 'in-use stocks' or 'socioeconomic material stocks', they have become a major focus of sustainability sciences in the last decade. Globally, the mass of socioeconomic material stocks now exceeds 10e14 kg, which is roughly equal to the dry-matter equivalent of all biomass on earth. It is doubling roughly every 20 years, almost perfectly in line with 'real' (i.e. inflation-adjusted) GDP. In terms of mass, buildings and infrastructures (here collectively called 'built structures') represent the overwhelming majority of all socioeconomic material stocks. This dataset features a detailed map of material stocks in the CONUS on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors. Spatial extentThis subdataset covers the West Coast CONUS, i.e. CA OR WA For the remaining CONUS, see the related identifiers. Temporal extentThe map is representative for ca. 2018. Data formatThe data are organized by states. Within each state, data are split into 100km x 100km tiles (EQUI7 grid), and mosaics are provided. Within each tile, images for area, volume, and mass at 10m spatial resolution are provided. Units are m², m³, and t, respectively. Each metric is split into buildings, other, rail and street (note: In the paper, other, rail, and street stocks are subsumed to mobility infrastructure). Each category is further split into subcategories (e.g. building types). Additionally, a grand total of all stocks is provided at multiple spatial resolutions and units, i.e. t at 10m x 10m kt at 100m x 100m Mt at 1km x 1km Gt at 10km x 10km For each state, mosaics of all above-described data are provided in GDAL VRT format, which can readily be opened in most Geographic Information Systems. File paths are relative, i.e. DO NOT change the file structure or file naming. Additionally, the grand total mass per state is tabulated for each county in mass_grand_total_t_10m2.tif.csv. County FIPS code and the ID in this table can be related via FIPS-dictionary_ENLOCALE.csv. Material layersNote that material-specific layers are not included in this repository because of upload limits. Only the totals are provided (i.e. the sum over all materials). However, these can easily be derived by re-applying the material intensity factors from (see related identifiers): A. Baumgart, D. Virág, D. Frantz, F. Schug, D. Wiedenhofer, Material intensity factors for buildings, roads and rail-based infrastructure in the United States. Zenodo (2022), doi:10.5281/zenodo.5045337. Further informationFor further information, please see the publication.A web-visualization of this dataset is available here.Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society. PublicationD. Frantz, F. Schug, D. Wiedenhofer, A. Baumgart, D. Virág, S. Cooper, C. Gómez-Medina, F. Lehmann, T. Udelhoven, S. van der Linden, P. Hostert, and H. Haberl (2023): Unveiling patterns in human dominated landscapes through mapping the mass of US built structures. Nature Communications 14, 8014. https://doi.org/10.1038/s41467-023-43755-5 FundingThis research was primarly funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). Workflow development was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—Project-ID 414984028-SFB 1404. AcknowledgmentsWe thank the European Space Agency and the European Commission for freely and openly sharing Sentinel imagery; USGS for the National Land Cover Database; Microsoft for Building Footprints; Geofabrik and all contributors for OpenStreetMap.This dataset was partly produced on EODC - we thank Clement Atzberger for supporting the generation of this dataset by sharing disc space on EODC.

The West Africa Coastal Vulnerability Mapping: GPW Version 4 Population Growth, Preliminary Release 1, 2000-2010, represents positive or negative growth in the number of persons per grid cell, and was calculated by subtracting an unreleased working version of the Gridded Population of the World (GPW), Version 4, year 2000 population count raster for the West Africa region from an unreleased working version of the GPWv4 year 2010 population count raster and cropping the result to within 200 kilometers of the coast. GPW provides globally consistent and spatially explicit human population information and data for use in research, policy making, and communications. This is a gridded (raster) data product that renders global population data at the scale and extent needed to demonstrate the spatial relationship of human populations and the environment globally. The gridded data set is constructed from national or subnational input Units (usually administrative Units) of varying resolutions. The native grid cell resolution of GPWv4 is 30 arc-second, or ~1 km at the equator.

The West Africa Coastal Vulnerability Mapping: Social Vulnerability Indices data set includes three indices: Social Vulnerability, Population Exposure, and Poverty and Adaptive Capacity. The Social Vulnerability Index (SVI) was developed using six indicators: population density (2010), population growth (2000-2010), subnational poverty and extreme poverty (2005), maternal education levels circa 2008, market accessibility (travel time to markets) circa 2000, and conflict data for political violence (1997-2013). Because areas of high population density and growth (high vulnerability) are generally associated with urban areas that have lower levels of poverty and higher degrees of adaptive capacity (low vulnerability), to some degree, the population factors cancel out the poverty and adaptive capacity indicators. To account for this, the data set includes two sub-indices, a Population Exposure Index (PEI), which only includes population density and population growth; and a Poverty and Adaptive Capacity Index (PACI), composed of subnational poverty, maternal education levels, market accessibility, and conflict. These sub-indices are able to isolate the population indicators from the poverty and conflict metrics. The indices represent Social Vulnerability in the West Africa region within 200 kilometers of the coast.

Spatial datasets utilized to conduct the spatial analysis and additional information from the research article: Coastal proximity of populations in 22 Pacific Island Countries and Territories. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0223249 https://sdd.spc.int/mapping-coastal

Transient killers whales inhabit the West Coast of the United States. Their range and movement patterns are difficult to ascertain, but are vital to understanding killer whale population dynamics and abundance trends. Satellite tagging of West Coast transient killer whales to determine range and movement patterns will provide data to assist in understanding transient killer whale populations. L...

This geodataabase provides an estimate to the spatial distribution of potential historical habitat for California Coastal Chinook Salmon, Central California Coast Coho Salmon, Northern California Steelhead and Central California Coast Steelhead.

Intrinsic potential measures the potential for development of favorable habitat characteristics as a function of the underlying geomorphic and hydrological attributes, as determined through a Digital Elevation Model (DEM) and mean annual precipitation grid. The model does not predict the actual distribution of "good'' habitat, but rather the potential for that habitat to occur, nor does the model predict abundance or productivity. Additionally, the model does not predict current conditions, but rather those patterns expected under pristine conditions as related through the input data. Thus, IP provides a tool for examining the historical distribution of habitat among and within watersheds, a proxy for population size and structure, and a useful template for examining the consequences of recent anthropogenic activity at landscape scales.

Beginning in the spring of 2015 the US West Coast began to experience the most wide-spread toxic Pseudo-nitzschia bloom to date, after approximately eight years without a toxic bloom event. Some species of Pseudo-nitzschia produce the neurotoxin domoic acid, which can have deleterious effects on marine wildlife (e.g. mammals and seabirds) as well as human consumers of food items (e.g. shellfish, crabs, sardines, anchovies) that are contaminated with the toxin. This multi-agency project aims to survey the bloom region, which stretches from southern California into the Gulf of Alaska, on the greatest spatial and temporal extent possible. Goals of the survey are to identify the extent of the bloom, the concentration of domoic acid in the bloom, the Pseudo-nitzschia species responsible for the toxicity, and the relationship of the bloom event to prevailing oceanographic and atmospheric conditions. The survey will allow for the creation of maps showing the spatial extent and concentrations of domoic acid, Pseudo-nitzschia, and oceanographic parameters such as temperature and salinity. The data collected from the survey will inform inferences as to the cause(s) of the toxic event. The effort will employ targeted research cruises, cruises of opportunity, and shore based sampling. Samples will be analyzed for marine toxins, harmful algal species, and other environmental and oceanographic parameters using state-of-the-art methodologies. Dataset contains domoic acid measurements, Pseudo-nitzschia species identifications and enumerations, and other physical oceanographic, biological and chemical oceanographic data.

These files contain the key distribution metrics of center of gravity, range limits, and depth for each species in the portal. This data set covers 8 regions of the United States: Northeast, Southeast, Gulf of Mexico, West Coast, Bering Sea, Aleutian Islands, Gulf of Alaska, and Hawai'i Islands.

The West Africa Coastal Vulnerability Mapping: Economic Systems Index is a composite index based on several spatial indicators, including gridded Gross Domestic Product (GDP), nighttime lights as a proxy for urban built-up and industrial areas, and cocoa, coconut, palm oil, rubber, and banana production in metric tons. It covers the coastal region of West Africa within 200 km of the coast. Population growth in the coastal zone is mostly a function of migration related to coastal economic activities; this indicator provides insights into highly exposed coastal areas that not only have high levels of economic activity but also high population growth and migration.

The dataset includes edge-lists for all US west coast port-group participation networks and for the entire coast from 2009-2010 for US California Current Large Marine Ecosystem (CCLME). access_formats=.htmlTable,.csv,.json,.mat,.nc,.tsv acquisition_description=In order to quantify and explore fisheries connectivity in the US California Current Large Marine Ecosystem (CCLME), we first synthesized fisheries landings ticket data for the entire region, from which we defined fisheries and subsequently fisheries connectivity. We analyzed fisheries connectivity using network theoretic metrics applied at the port-group level (i.e. clusters of geographically proximate ports), and relating them to the social vulnerability framework (Adger, 2006), with a focus on sensitivity to change and adaptive capacity. The port-group spatial scale was chosen so as to best represent fisheries connectivity in terms of coastal fishing communities. However, we also calculated fisheries connectivity at larger spatial scales, specifically at the scale of the whole CCLME. All our calculations were performed for a short period (2009\u20132010); 2\u2009years without El Nino or La Nina conditions, and without major management changes) and in the discussion, we mention the importance of collecting longer time-series data, from which changes in fisheries connectivity could be observed.

Port-groups were defined as:
NPS (Bellingham Bay, Port Townsend, Port Angeles, Anacortes, Sequim, La Conner, Neah Bay, Friday Harbor, Blaine, other north Puget Sound ports)
SPS (Seattle, Olympia, Everett, Shelton, Tacoma)
CWA (Westport, La Push, Willapa Bay, Grays Harbor, other Washington coastal ports)
CLW (Ilwaco/Chinook, other Columbia River ports)
CLO (Astoria, Cannon Beach, Seaside-Gearhart)
TLA (Tillamook/Garibaldi, Pacific City, Netarts Bay, Nehalem Bay)
NPA (Newport, Depoe Bay, Waldport, Siletz Bay)
CBA (Winchester Bay, Charleston (Coos Bay), Bandon, Florence)
BRA (Brookings, Port Orford, Gold Beach, Crescent City, other Del Norte county ports)
ERA (Trinidad, Eureka, Fields Landing, other Humboldt county ports)
BGA (Fort Bragg, Albion, Point Arena, other Mendocino county ports)
BDA (Bodga Bay, Bolinas, Point Reyes, Tomales Bay, other Sonoma and Marin county ports)
SFA (Princeton/Half Moon Bay, San Francisco, Berkley, Richmond, Oakland, Sausalito, Alameda, other SF Bay and San Mateo county ports)
MNA (Santa Cruz, Moss Landing, Moneterey, other Santa Crus and Monterey county ports)
MRA (Morro Bay, Avila, other San Luis Obispo county ports)
SBA Santa Barbara, Port Hueneme, Oxnard, Ventura, other Santa Barbara Ventura county ports)
LAA (Long Beach, San Pedro, Dana Point, Terminal Island, Newport Beach, Wilmington, other LA and Orange county ports)
SDA (Oceanside, San Diego, other San Diego county ports) awards_0_award_nid=559952 awards_0_award_number=OCE-1426746 awards_0_data_url=http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1426746 awards_0_funder_name=NSF Division of Ocean Sciences awards_0_funding_acronym=NSF OCE awards_0_funding_source_nid=355 awards_0_program_manager=Michael E. Sieracki awards_0_program_manager_nid=50446 awards_1_award_nid=748879 awards_1_award_number=GEO-1211972 awards_1_funder_name=National Science Foundation awards_1_funding_acronym=NSF awards_1_funding_source_nid=350 awards_1_program_manager=Sarah L. Ruth awards_1_program_manager_nid=748878 cdm_data_type=Other comment=Participation networks (all) PI: Emma Fuller Data version 1: 2018-10-26 Conventions=COARDS, CF-1.6, ACDD-1.3 data_source=extract_data_as_tsv version 2.3 19 Dec 2019 defaultDataQuery=&time<now doi=10.1575/1912/bco-dmo.748875.1 infoUrl=https://www.bco-dmo.org/dataset/748875 institution=BCO-DMO metadata_source=https://www.bco-dmo.org/api/dataset/748875 param_mapping={'748875': {}} parameter_source=https://www.bco-dmo.org/mapserver/dataset/748875/parameters people_0_affiliation=Princeton University people_0_person_name=Emma Fuller people_0_person_nid=748888 people_0_role=Principal Investigator people_0_role_type=originator people_1_affiliation=Princeton University people_1_person_name=Emma Fuller people_1_person_nid=748888 people_1_role=Contact people_1_role_type=related people_2_affiliation=Woods Hole Oceanographic Institution people_2_affiliation_acronym=WHOI BCO-DMO people_2_person_name=Amber York people_2_person_nid=643627 people_2_role=BCO-DMO Data Manager people_2_role_type=related project=CC Fishery Adaptations projects_0_acronym=CC Fishery Adaptations projects_0_description=Description from NSF award abstract: Climate change presents a profound challenge to the sustainability of coastal systems. Most research has overlooked the important coupling between human responses to climate effects and the cumulative impacts of these responses on ecosystems. Fisheries are a prime example of this feedback: climate changes cause shifts in species distributions and abundances, and fisheries adapt to these shifts. However, changes in the location and intensity of fishing also have major ecosystem impacts. This project's goal is to understand how climate and fishing interact to affect the long-term sustainability of marine populations and the ecosystem services they support. In addition, the project will explore how to design fisheries management and other institutions that are robust to climate-driven shifts in species distributions. The project focuses on fisheries for summer flounder and hake on the northeast U.S. continental shelf, which target some of the most rapidly shifting species in North America. By focusing on factors affecting the adaptation of fish, fisheries, fishing communities, and management institutions to the impacts of climate change, this project will have direct application to coastal sustainability. The project involves close collaboration with the National Oceanic and Atmospheric Administration, and researchers will conduct regular presentations for and maintain frequent dialogue with the Mid-Atlantic and New England Fisheries Management Councils in charge of the summer flounder and hake fisheries. To enhance undergraduate education, project participants will design a new online laboratory investigation to explore the impacts of climate change on fisheries, complete with visualization tools that allow students to explore inquiry-driven problems and that highlight the benefits of teaching with authentic data. This project is supported as part of the National Science Foundation's Coastal Science, Engineering, and Education for Sustainability program - Coastal SEES. The project will address three questions: 1) How do the interacting impacts of fishing and climate change affect the persistence, abundance, and distribution of marine fishes? 2) How do fishers and fishing communities adapt to species range shifts and related changes in abundance? and 3) Which institutions create incentives that sustain or maximize the value of natural capital and comprehensive social wealth in the face of rapid climate change? An interdisciplinary team of scientists will use dynamic range and statistical models with four decades of geo-referenced data on fisheries catch and fish biogeography to determine how fish populations are affected by the cumulative impacts of fishing, climate, and changing species interactions. The group will then use comprehensive information on changes in fisher behavior to understand how fishers respond to changes in species distribution and abundance. Interviews will explore the social, regulatory, and economic factors that shape these strategies. Finally, a bioeconomic model for summer flounder and hake fisheries will examine how spatial distribution of regulatory authority, social feedbacks within human communities, and uncertainty affect society's ability to maintain natural and social capital. projects_0_end_date=2018-08 projects_0_geolocation=Northeast US Continental Shelf Large Marine Ecosystem projects_0_name=Adaptations of fish and fishing communities to rapid climate change projects_0_project_nid=559948 projects_0_start_date=2014-09 sourceUrl=(local files) standard_name_vocabulary=CF Standard Name Table v55 version=1 xml_source=osprey2erddap.update_xml() v1.3

This dataset contains data collected from the National Oceanic and Atmospheric Administration Ocean Acidification Program cruise on NOAA Ship Ronald H. Brown from 2021-06-13 to 2021-07-26. 133 stations were occupied on 17 transect lines from Queen Charlotte Sound, Canada to southern California USA. The cruise was designed to obtain a synoptic snapshot of key carbon, physical, and other biogeochemical parameters as they relate to ocean acidification (OA) in coastal waters and large estuaries of the northeast Pacific. At all sampling stations, CTD casts were conducted to measure temperature, conductivity, pressure, and oxygen concentrations using CTD and oxygen sensors. Discrete water samples were collected throughout the water column at all stations in Niskin bottles. Laboratory analyses were run to measure dissolved inorganic carbon (DIC), pH, oxygen, nutrient concentrations, total alkalinity (TA), chlorophyll and other biological measurements. This effort was conducted in support of the estuarine and coastal monitoring and research objectives of the NOAA Ocean Acidification Program and conforms to monitoring guidelines of the Global Ocean Acidification Observing Network (goa-on.org) and the U.S. National Oceanic and Atmospheric Administration's Ocean Acidification Program. Fair Use Data Statement for Cruise Data: Ocean acidification data from the 2021 NOAA Ocean Acidification Program West Coast cruise are made freely available to the public and the scientific community in the belief that their wide dissemination will lead to greater understanding and new scientific and policy insights. The investigators sharing these data rely on the ethics and integrity of the user to ensure that the institutions and investigators involved in producing West Coast cruise data sets receive fair credit for their work, which in turn helps ensure the continuity of the observational time-series. If the data are obtained for potential use in a publication or presentation, we urge the end user to inform the investigators at the outset of this work so that we can help ensure that the quality and limitations of the data are accurately represented. If these data are essential to the work, or if an important result or conclusion depends on these data, co-authorship may be appropriate. This should be discussed at an early stage in the work. We request that manuscripts using these data be shared before they are submitted for publication. Please direct all queries about this dataset to Drs. Richard Feely (e-mail: Richard.A.Feely@noaa.gov) and Brendan Carter (e-mail: Brendan.Carter@noaa.gov). _NCProperties=version=2,netcdf=4.9.2,hdf5=1.14.0 abstract=This dataset contains data collected from the National Oceanic and Atmospheric Administration Ocean Acidification Program cruise on NOAA Ship Ronald H. Brown from 2021-06-13 to 2021-07-26. 133 stations were occupied on 17 transect lines from Queen Charlotte Sound, Canada to southern California USA. The cruise was designed to obtain a synoptic snapshot of key carbon, physical, and other biogeochemical parameters as they relate to ocean acidification (OA) in coastal waters and large estuaries of the northeast Pacific. At all sampling stations, CTD casts were conducted to measure temperature, conductivity, pressure, and oxygen concentrations using CTD and oxygen sensors. Discrete water samples were collected throughout the water column at all stations in Niskin bottles. Laboratory analyses were run to measure dissolved inorganic carbon (DIC), pH, oxygen, nutrient concentrations, total alkalinity (TA), chlorophyll and other biological measurements. This effort was conducted in support of the estuarine and coastal monitoring and research objectives of the NOAA Ocean Acidification Program and conforms to monitoring guidelines of the Global Ocean Acidification Observing Network (goa-on.org) and the U.S. National Oceanic and Atmospheric Administration's Ocean Acidification Program. Fair Use Data Statement for Cruise Data: Ocean acidification data from the 2021 NOAA Ocean Acidification Program West Coast cruise are made freely available to the public and the scientific community in the belief that their wide dissemination will lead to greater understanding and new scientific and policy insights. The investigators sharing these data rely on the ethics and integrity of the user to ensure that the institutions and investigators involved in producing West Coast cruise data sets receive fair credit for their work, which in turn helps ensure the continuity of the observational time-series. If the data are obtained for potential use in a publication or presentation, we urge the end user to inform the investigators at the outset of this work so that we can help ensure that the quality and limitations of the data are accurately represented. If these data are essential to the work, or if an important result or conclusion depends on these data, co-authorship may be appropriate. This should be discussed at an early stage in the work. We request that manuscripts using these data be shared before they are submitted for publication. Please direct all queries about this dataset to Drs. Richard Feely (e-mail: Richard.A.Feely@noaa.gov) and Brendan Carter (e-mail: Brendan.Carter@noaa.gov). acknowledgment=National Oceanic and Atmospheric Administration (NOAA) cdm_altitude_proxy=z cdm_data_type=Profile cdm_profile_variables=profile contributor_name=Marine Lebrec, CeNCOOS contributor_role=Data Specialist Conventions=CF-1.6, ACDD-1.3, Axiom CRUISE-3.0.1 description=Data were originally stored in CSV files, but converted to netCDF for visualization within a data portal provided by Axiom Data Science. Easternmost_Easting=-130.847 featureType=Profile geospatial_bbox=POLYGON ((-117.751 31.775, -117.751 52.399, -130.847 52.399, -130.847 31.775, -117.751 31.775)) geospatial_bounds=POLYGON ((-120.251 31.777, -122.533 33.483, -123.366 34.643, -123.93 35.91, -130.846 51.458, -130.642 51.711, -129.971 52.018, -129.051 52.399, -124.791 48.37, -117.751 33.491, -120.251 31.777)) geospatial_bounds_crs=EPSG:4326 geospatial_lat_max=52.399 geospatial_lat_min=31.775 geospatial_lat_units=degrees_north geospatial_lon_max=-130.847 geospatial_lon_min=-117.751 geospatial_lon_units=degrees_east geospatial_vertical_max=4131.7 geospatial_vertical_min=2.6 geospatial_vertical_positive=down geospatial_vertical_units=m history=2023-10-27T15:43:12Z - Methods for sampling and analysis for each variable are described in the NCEI metadata for this dataset: https://doi.org/10.25921/tzxh-n954. NetCDF generated by Axiom Data Science id=processed_data_w07_20230425 infoUrl=https://portal.axds.co/?portal_id=152#platform/d04b3286-08de-58b3-92b3-0291e9721f72/v2 institution=NOAA Pacific Marine Environmental Laboratory keywords_vocabulary=GCMD Science Keywords Version 16.5 Metadata_Conventions=Unidata Dataset Discovery v1.0 metadata_link=https://doi.org/10.25921/tzxh-n954 naming_authority=com.axiomdatascience ncei_template_version=NCEI_NetCDF_Trajectory_Template_v2.0 netcdf_creator_url=http://www.axiomdatascience.com/ netcdf_writer=Axiom Data Science Northernmost_Northing=52.399 packrat_source=axiom.netcdf_harvest.netcdf_harvest packrat_source_id=caloos/oah/processed_wcoa_cruise_w07 packrat_uuid=d04b3286-08de-58b3-92b3-0291e9721f72 platform=NOAA Ship Ronald H. Brown platform_category=ctd platform_country=United States of America platform_groups=Ocean Acidification and Hypoxia platform_owner=unknown platform_type=ship project=CeNCOOS OAH Monitoring references=https://doi.org/10.25921/tzxh-n954 sea_name=Pacific Ocean sourceUrl=https://files.platforms.axds.co/axiom/netcdf_harvest/caloos/oah/processed_wcoa_cruise_w07/processed.nc Southernmost_Northing=31.775 standard_name_vocabulary=NetCDF Climate and Forecast (CF) Metadata Convention Standard Name Table v46 time_coverage_duration=P28DT10H17M0S time_coverage_end=2021-07-23T10:56:00Z time_coverage_resolution=P0DT0H23M5S time_coverage_start=2021-06-25T02:39:00Z vessel_name=NOAA Ship Ronald H. Brown Westernmost_Easting=-117.751

Purpose: The purpose of this data is to provide positional and attribute information about west coast marine ports, terminals, shipyards, and harbours.Notes: This dataset identifies the geographic locations of marine ports, terminals, shipyards, and harbours on the west coast of British Columbia. The points were reviewed and cross referenced with government and industry data sources for geographic and attribute data accuracy.Suggested Filters:Harbour or Port: DESCRIPTION IN ('Harbour', 'Port')Shipyard or Terminal: DESCRIPTION IN ('Shipyard', 'Terminal')See how to apply filters.WMS GetCapabilities URL: DataBC also offers access to this data in OGC WMS format. WMS is useful when the map author does not require custom popups, styling, or analytic capabilities for the layer. ArcGIS Online authors may want to use WMS, instead of this ArcGIS Server layer, in the following scenarios: Where they want to use existing Data Custodian approved styling, and/or They only need simple identify and map rendering functionality.Copy the: WMS GetCapabilities URL to add this web item to an ArcGIS Online Map or Scene Viewer. In some cases, multiple Styles are listed in the GetCapabilities and can be added as WMS Custom parameters. For more information on how to use a WMS layer see - ESRI's OGC ArcGIS Online HelpBC Data Catalogue Metadata URL: https://catalogue.data.gov.bc.ca/dataset/5f3c273a-7a0d-4b5f-8059-b34cc3f116c7

Data for this project resides in the West Coast Groundfish Bottom Trawl Survey Database. Deep-sea corals are often components of trawling bycatch, though their brittle skeleton and slow growth make them particularly vulnerable to such impacts. An understanding of the population structure of deep-sea corals will be critical to ascertaining the effects of habitat loss and genetic connections bet...

Catch, effort, location (latitude, longitude), relative abundance indices, and associated biological data from groundfish multi-species bottom trawl surveys in West Coast Haida Gwaii. Introduction The West Coast Haida Gwaii (WCHG) synoptic bottom trawl survey was first conducted annually from 2006 to 2008 and has since been repeated every second year on even numbered years. The survey was not impacted by the COVID-19 pandemic. This survey is one of a set of long-term and coordinated surveys that together cover the continental shelf and upper slope of most of the British Columbia coast. The other surveys are the Queen Charlotte Sound (QCS) survey, the Hecate Strait (HS) survey, the West Coast Vancouver Island (WCVI) survey, and the Strait of Georgia (SOG) survey. The objectives of these surveys are to provide fishery independent abundance indices of all demersal fish species available to bottom trawling and to collect biological samples of selected species. The survey follows a random depth-stratified design and the sampling units are 2 km by 2 km blocks. The synoptic bottom trawl surveys are conducted by Fisheries and Oceans Canada (DFO) in collaboration with the Canadian Groundfish Research and Conservation Society (CGRCS), a non-profit society composed of participants in the British Columbia commercial groundfish trawl fishery. The Queen Charlotte Sound and West Coast Haida Gwaii surveys are conducted under collaborative agreements, with the CGRCS providing chartered commercial fishing vessels and field technicians, while DFO provides in-kind contributions for running the surveys including personnel and equipment. The Hecate Strait, West Coast Vancouver Island, and Strait of Georgia surveys are conducted by DFO and have typically taken place on a Canadian Coast Guard research vessel. Until 2016 this vessel was the CCGS W.E. Ricker. From 2021 onwards, this vessel was the CCGS Sir John Franklin. In years when a coast guard vessel has not been available, the Hecate Strait, West Coast Vancouver Island, and Strait of Georgia surveys have taken place on chartered industry vessels. Data from these surveys are also presented in the groundfish data synopsis report (Anderson et al. 2019). Effort This table contains information about the survey trips and fishing events (trawl tows/sets) that are part of this survey series. Trip-level information includes the year the survey took place, a unique trip identifier, the vessel that conducted the survey, and the trip start and end dates (the dates the vessel was away from the dock conducting the survey). Set-level information includes the date, time, location, and depth that fishing took place, as well as information that can be used to calculate fishing effort (duration) and swept area. All successful fishing events are included, regardless of what was caught. Catch This table contains the catch information from successful fishing events. Catches are identified to species or to the lowest taxonomic level possible. Most catches are weighed, but some are too small (“trace” amounts) or too large (e.g. very large Big Skate). The unique trip identifier and set number are included so that catches can be related to the fishing event information (including capture location). Biology This table contains the available biological data for catches which were sampled. Data may include any or all of length, sex, weight, age. Different length types are measured depending on the species. Age structures are collected when possible for species where validated aging methods exist and are archived until required for an assessment; therefore, all existing structures have not been aged at this time. The unique trip identifier and set number are included so that samples can be related to the fishing event and catch information. Biomass This table contains relative biomass indices of species that have been captured in every survey of the time series. The coefficient of variation and bootstrapped 95% confidence intervals are provided for each index. The groundfish data synopsis report (Anderson et al. 2019) provides an explanation of how the relative biomass indices are derived. Note that we do not calculate a biomass index for the 2014 West Coast Haida Gwaii survey, as this survey was incomplete due to operational problems.

This polygon GIS data set represents a compilation of statewide seagrass data from various source agencies and scales. The data were mapped from sources ranging in date from 1987 to 2024. This dataset is complete as of data available to FWRI in October 2025. Not all data in this compilation are mapped from photography; some are the results of field measurements. See the "Sources" section for more information. The original source data sets were not all classified in the same manner; some used the Florida Land Use Cover and Forms Classification System (FLUCCS) codes 9113 for discontinuous seagrass and 9116 for continuous seagrass; some defined only presence and absence of seagrass, and some defined varying degrees of seagrass percent cover. In order to merge all of these data sources into one compilation data set, FWRI reclassified the various source data attribute schemes into two categories: "Continuous Seagrass" and "Patchy (Discontinuous) Seagrass". In areas where studies overlap, the most recent study where a given area has been interpreted is represented in this data set. This data set is not comparable to previous statewide data sets for time series studies - not all areas have been updated since the previous statewide compilation and some areas previously not mapped are now included. Please contact GIS Librarian to request the source data if you need to do a time series comparison. This data set has been updated in several areas from the previous compilation, including Naples Bay (2007), Big Bend (2022), Choctawhatchee Bay (2017), Pensacola Bay/Santa Rosa Bay/Big Lagoon (2017), Perdido Bay (2017), and St. Andrew Bay (2024), St. Joseph Bay (2024), Florida Bay (2016), portions of the Caloosahatchee, Loxahatchee, and St. Lucie Rivers (2011), Lake Worth Lagoon (2018), Rookery Bay (2014), Estero Bay and the West Coast (2014), Indian River Lagoon (2023), Sunken Island (2023), the Springs Coast (2024) and Southwest Florida (2024). Version 2 of the Unified Florida Reef Tract Map, with seagrass data ranging in source date from 2004-2015, has also been integrated into this compilation to represent the most recent data available from St. Lucie County to the Dry Tortugas in Florida Keys.

Rockfish Conservation Areas (RCAs) are closed areas for west coast groundfish fisheries and for some fisheries that may incidentally take groundfish as bycatch. The RCA boundary line is a connection of a series of GPS coordinates published in federal regulations (See 50 CFR 660.71-660.74) that are intended to approximate underwater depth contours. RCA boundaries are used in groundfish regulations to avoid interactions with certain groundfish species of concern and may change between seasons and Recreational Fishing Management Areas. The process of digitizing these boundary lines is as follows: 30, 40, 50, 100, and 150fm waypoint .csv files were downloaded from NOAA’s West Coast Groundfish Closed Areas website https://www.fisheries.noaa.gov/west-coast/sustainable-fisheries/west-coast-groundfish-closed-areas and imported into ArcGIS Pro. Each point feature was clipped to ocean waters offshore of California and merged together. “Fathom” was added as a field to each shapefile and populated with the corresponding depth in fathoms. Boundary lines for each shapefile (30, 40, 50, 100, and 150 fm) were created using the “Points to line” tool. Line Field: “area_name”. Attribute Source: Start Point. Transfer Fields: FID, area_name, Fathom. Attributes: area_name: Unique name field displaying depth and location. Fathom: Approximate depth in fathoms of contour line. Region: Describes which of the five groundfish management zones the section of the contour line is in.