This data publication contains an optimized mosaic of PALSAR-2 L-band dual-polarized radar backscatter summer composite for the year 2020 across Canada (excluding the Arctic Archipelago). Its primary purpose is to offer the best possible L-band radar summer-like composite mosaic mostly tailored for i) classifying natural treed or shrubby vegetation covers, and ii) estimating their structural attributes, such as height and biomass. ## Methodology:This product is based on the freely available and open dataset of yearly JAXA Global PALSAR-2/PALSAR Mosaics ver. 1 (hereafter JAXA GPM v1). They were generated by the Japanese space agency (JAXA) using PALSAR L-band synthetic aperture radar sensors aboard the Advanced Land Observing Satellites (ALOS): ALOS-2 PALSAR-2 (2015 to 2020) and ALOS PALSAR (2007 to 2010). JAXA GPM v1 provide yearly mosaics orthorectified and slope-corrected L-band HH- and HV-polarized gamma naught (γ°) backscatter amplitude with 25-m pixel size and scaled as 16-bit data (Shimada et al. 2014). JAXA GPM v1 are accessible as a Google Earth Engine image collection at https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR_YEARLY_SAR.The yearly 2007 to 2020 JAXA GPM v1 dataset across Canada underwent a post-processing and compositing methodology implemented in Google Earth Engine, as detailed in Pontone et al. 2024 and summarized in a pdf “Readme” file provided with the dataset. In summary, the method involves these three steps: 1. Post-processing of yearly γ° HH and HV datasets: handling data gaps, filtering speckle noise, and generating two radar vegetation indices, the HV/HH ratio (HVHH) and the radar forest degradation index (RFDI).2. Temporal compositing from 2015 to 2020 of post-processed yearly γ° PALSAR-2 HH, HV, HVHH, and RFDI backscatter data aimed to i) address data gaps and ii) mitigate detrimental backscatter fluctuations across ALOS-2 orbits resulting from numerous out-of-summer acquisitions.3. Generating the final PALSAR-2 L-band γ° radar backscatter summer composite circa 2020 raster files. ## Performance et limitations:The resulting Canada-wide, excluding the Arctic Archipelago, gap-free and radiometrically optimized mosaic of circa 2020 PALSAR-2 L-band backscatter summer composite was found significantly improved compared to the single-year 2020 JAXA GPM v1 mosaic, particularly in northern boreal Canada (Pontone et al. 2024). However, this product should be considered as a summer-like composite and users should be mindful of the following known limitations: • In northwestern Canada, there were often minimal to no summer PALSAR-2 acquisitions, resulting in residual backscatter fluctuations across ALOS-2 orbits.• The composite may exhibit patchy radiometric noise in areas that experienced major disturbances (fires, harvesting) between 2015 and 2020 despite they were accounted for in our compositing methodology.• This product is deemed less performant, or possibly not suitable, for i) characterizing highly dynamic land cover types such as grasslands, croplands, and water bodies, or for ii) estimating soil and/or vegetation moisture content for the year 2020.As a final note, JAXA released an improved GPM ver. 2 that was not available at the time of this study. A preliminary analysis shows that the circa 2020 PALSAR-2 composite product still seems to outperform the 2020 JAXA GPM v2 in northern Canada. ## Additional Information on Dataset: This dataset comprises four raster geotiff files of circa 2020 L-band PALSAR-2 summer temporal composites as mosaics of orthorectified and radiometrically slope corrected dual-polarized HH and HV gamma naught (γ°) backscatter amplitude, along with two radar vegetation indices (HVHH, RFDI), all scaled as 16-bit Digital Number (DN) values with 30-m pixel size in Lambert conformal conic projection. An additional 8-bit RGB quick-view file is also provided. A companion pdf ”Readme” file provides further details about these geotiff files and equations to convert DN values to γ° absolute intensity values. ## Dataset Citation: Beaudoin, A., Villemaire, P., Gignac, C., Tolszczuk, S., Guindon, L., Pontone, N., Millard, C. (2024). Canada’s PALSAR-2 dual-polarized L-band radar summer backscatter composite, circa 2020. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec, Canada. https://doi.org/10.23687/8ec4ee78-9240-4bd0-9c97-d3a27829e209In addition, please provide credits to the Japanese space agency JAXA with the mention “Original Global PALSAR-2/PALSAR Mosaics v1 provided by JAXA (©JAXA)” ## Publication Reference for Product Development and Use in Wetland Mapping: Pontone, N., Millard, K., Thompson, D., Guindon, L., Beaudoin, A. (2024). A hierarchical, Multi-Sensor Framework for Peatland Sub-Class and Vegetation Mapping Throughout the Canadian Boreal Forest. Remote Sensing for Ecology and Conservation (accepted for publication).## Cited reference: Shimada, M., Itoh, T., Motooka, T., Watanabe, M., Tomohiro, S., Thapa, T., Lucas, R. (2014). New Global Forest/Non-Forest Maps from ALOS PALSAR Data (2007-2010). Remote Sensing of Environment, 155, pp. 13-31. https://doi.org/ 10.1016/j.rse.2014.04.014

Rouyn-Noranda cycling network**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Sexual reproduction is critical to the resilience of seagrass beds impacted by habitat degradation or environmental changes, as robust seed banks allow new shoots to establish each year. Reproductive strategies of seagrass beds range on a continuum from strictly annual to perennial, driven by local environmental conditions. We examined the reproductive dynamics of Zostera marina beds at six sites on the Atlantic coast of Canada to characterize how life history strategies are shaped by the surrounding environment. Sites were categorized as wave protected and wave exposed, where protected sites were warm, shallow, with little water movement and muddy sediments, and exposed sites were either shallow or deep, with cooler water and sandy sediments. While mixed life history strategies were evident at all sites, protected eelgrass beds exhibited both the highest and lowest sexual reproductive effort relative to exposed beds. These beds regularly experienced thermal stress, with higher temperature range and extended warm water events relative to exposed beds. The development of reproductive shoots were similar across sites with comparable Growing Degree-days at the beginning and end of anthesis, but the First Flowering Date was earlier at the protected warmer sites relative to exposed sites. With different reproductive shoot density among sites, seed production, seed retention, and seedling recruitment also varied strongly. Only one site, located in a warm, shallow and protected lagoon, contained a mixed life history population with a high reproductive effort (33.7%), strong seed bank, and high seedling establishment. However, a primarily perennial population with the lowest reproductive effort (0.5%) was identified at the warmest site, suggesting that conditions here could not support high sexual reproduction. Robustness of seed banks was strongly linked to reproductive shoot density, although the role of seed retention, germination and seedling survival require further investigation. Our study provides insights into one key aspect of seagrass resilience, and suggests that resilience assessments should include reproductive shoot density to inform their management and conservation.Cite this data: Vercaemer B. and Wong M. Reproductive ecology of Zostera marina L. (eelgrass) across varying environmental conditions. Published: May 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/56cfea6f-aeca-47ed-94ab-c519d9e63c91

Species characterization by environmental DNA (eDNA) is a method that allows the use of DNA released into the environment by organisms from various sources (secretions, faeces, gametes, tissues, etc.). It is a complementary tool to standard sampling methods for the identification of biodiversity. This project provides a list of invertebrates species whose DNA has been detected in water samples collected at 2018 using the marker COI.The surveys were carried out in the summer of 2018 from August 11 to 14, between Forestville and Godbout (Haute-Côte-Nord). Sampling was carried out between 9-52 meters depth in 40 stations with one sample par station. Two liters of water were filtered through a 1.2 µm fiberglass filter. DNA extractions were performed with the DNeasy Blood and Tissue extraction kit (Qiagen). Negative field, extraction and PCR controls were added at the different stages of the protocol. Libraries at the COI locus were prepared by Genome Quebec and sequenced on an Illumina MiSeq PE250 system. The bioinformatics analysis of the sequences obtained was carried out using an in-house analysis pipeline as reported in Bourret et al. 2022. A first step made it possible to obtain a molecular operational taxonomic unit table (MOTU) using the cutadapt software for the removal of the adapters and the DADA2 R package for the filtration, fusion, chimera removal and data compilation. The MOTUs table was subsequently corrected by taking into account the negative controls, where the number of observations in the latter was removed from the linked samples. Singleton MOTUs have also been removed. Finally, the taxonomic assignments were carried out on the MOTUs using the IDTAXA classifier (present in the DECIPHIER R package) using a training set trained on the COI reference bank for Golf St-Laurent (GSL-rl v1.0, https://github.com/GenomicsMLI-DFO/MLI_GSL-rl) and a threshold of 40. Detections with an “Unreliable due to gaps” category were reported at the genus level only.The file provided includes generic activity information, including site, station name, date, marker type, assignment types used for taxa identification, and a list of taxa or species. The list of taxa has been verified by a biodiversity expert from the Maurice-Lamontagne Institute.This project was funded by Fisheries and Oceans Canada's Coastal Environmental Baseline Data Program under the Oceans Protection Plan. This initiative aims to acquire baseline environmental data that contributes to the characterization of significant coastal areas and supports evidence-based assessments and management decisions to preserve marine ecosystems.Data are also available on SLGO platform : https://doi.org/10.26071/ogsl-cd4c205b-f63b

Species characterization by environmental DNA (eDNA) is a method that allows the use of DNA released into the environment by organisms from various sources (secretions, faeces, gametes, tissues, etc.). It is a complementary tool to standard sampling methods for the identification of biodiversity. This project provides a list of fish and marine mammal species whose DNA has been detected in water samples collected between 2019 and 2021 using the mitochondrial marker MiFish (12S).The surveys were carried out in the summer of 2019 (July 14-18) and (July 30 - August 5), in the fall of 2020 (October 27-28) and in the summer-fall of 2021 (May 31 - June 3 ) and (August 24-25) between Forestville and Godbout (Haute-Côte-Nord). Sampling was carried out between 1-50 meters depth in 91 stations, with 1 to 3 replicates per station. Two liters of water were filtered through a 1.2 µm fiberglass filter. DNA extractions were performed with the DNeasy Blood and Tissues or PowerWater extraction kit (Qiagen). Negative field, extraction and PCR controls were added at the different stages of the protocol. The libraries were prepared either by Génome Québec (2019, 2020) or by the Genomics Laboratory of the Maurice-Lamontagne Institute (2021), then sequenced on a NovaSeq 4000 PE250 system by Génome Québec. The bioinformatics analysis of the sequences obtained was carried out using an analysis pipeline developed in the genomics laboratory. A first step made it possible to obtain a table of molecular operational taxonomic units (MOTU) using the cutadapt software for the removal of the adapters and the R package DADA2 for the filtration, the fusion, removal of chimeras and compilation of data. The MOTUs table was then corrected using the R package metabaR to eliminate the tag-jumping and take contaminants into consideration. Samples showing a strong presence of contaminating MOTUs were removed from the dataset. The MOTUs were also filtered to remove all remaining adapter sequences and also retain only those of the expected size (around 170 bp). Finally, taxonomic assignments were made on the MOTUs using the BLAST+ program and the NCBI-nt database. Taxonomic levels (species, genus or family) were assigned using a best match method (Top hit), with a threshold of 95%. Only assignments at the level of fish and marine mammals were considered, and the taxa detected were compared to a list of regional species, and corrected if necessary. The species detections of the different replicas have been combined.The file provided includes generic activity information, including site, station name, date, marker type, assignment types used for taxa identification, and a list of taxa or species. The list of taxa has been verified by a biodiversity expert from the Maurice-Lamontagne Institute.This project was funded by Fisheries and Oceans Canada's Coastal Environmental Baseline Data Program under the Oceans Protection Plan. This initiative aims to acquire baseline environmental data that contributes to the characterization of significant coastal areas and supports evidence-based assessments and management decisions to preserve marine ecosystems.Data were also published on SLGO platform : https://doi.org/10.26071/ogsl-2239bca5-c24a

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).EffortThis 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.CatchThis 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).BiologyThis 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.BiomassThis 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.

Radar coverage is provided to dynamically display the zones covered by the radars every 6 minutes, and to provide information on the availability (or not) of the contributing radars as well as on the areas of overlap.

The Regional Deterministic Wave Prediction System (RDWPS) produces wave forecasts out to 48 hours in the future using the third generation spectral wave forecast model WaveWatch III® (WW3). The model is forced by the 10 meters winds from the High Resolution Deterministic Prediction System (HRDPS). Over the Great Lakes, an ice forecast from the Water Cycle Prediction System of the Great Lakes (WCPS) is used by the model to attenuate or suppress wave growth in areas covered by 25% to 75% and more than 75% ice, respectively. Over the ocean, an ice forecast from the Regional Ice Ocean Prediction System (RIOPS) is used: in the Northeast Pacific, waves propagate freely for ice concentrations below 50%, above this threshold there is no propagation; in the Northwest Atlantic the same logic is used as in the Great Lakes. Forecast elements include significant wave height, peak period, partitioned parameters and others. This system includes several domains: Lake Superior, Lake Huron-Michigan, Lake Erie, Lake Ontario, Atlantic North-West and Pacific North-East.

Basic biological data for all fish caught during the 2012 BSMFP expedition. Includes identification, weight, length (total, fork, and, standard), liver weight, gonad weight, sex and maturity level.

FERRYSEG_OFFICIAL provides the information about the Ferry Connection Segments. Ferry Connection Segment is the specific representation of a portion of a ferry connection with uniform characteristics. FERRYSEG_OFFICIAL is one of the base layer used to create "Ferryseg" layer for Saskatchewan Upgraded Road Network (SURN) and National Road Network (NRN). This data layer has been created for mainly MHI data users, that require relatively up-to-date and accurate description of all ferry routes in the Province of Saskatchewan.FERRYSEG_OFFICIAL consists of the data for the average route a ferryboat takes when transporting vehicles between two fixed locations on the Road Network. "NID" National Identifier is used to manage the updates between data producer and data users. FERRYSEG_OFFICIAL data layer serves as a foundation for SURN, NRN, SASK911 and other applications.