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We have found 423 datasets for the keyword " relative density". You can continue exploring the search results in the list below.
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423 Datasets, Page 1 of 43
Beluga Relative Summer Density in the St. Lawrence Estuary
This layer represents the relative summer density of belugas in the St. Lawrence Estuary based on 35 aerial surveys carried out from 1990 to 2009. The boundaries of the areas were determined by combining the highest densities until the desired proportion of the population was obtained using kernel density estimation in order to obtain a smooth and continuous density distribution.Within Fisheries and Oceans Canada (DFO), the ecosystem approach is considered a tool for operational planning, project implementation and preparation of advisory reports. In response to this strategic direction, the DFO science division is committed to implement the ecosystem approach in its activities as Ecosystem Research Initiatives (ERI) in each of the six administrative regions of DFO. In the Quebec region, two pilot projects were implemented, of which one aimed to define and characterize the habitat of the St. Lawrence beluga (Delphinapterus leucas).Data sources and references:DFO. 2016. Ecosystem Research Initiative (ERI): Integrated Advice on the Summer Habitat of the St. Lawrence Estuary Beluga (Delphinapterus leucas). DFO Can. Sci. Advis. Sec. Sci. Advis. Rep. 2016/030. Mosnier, A., R. Larocque, M. Lebeuf, J.-F. Gosselin, S. Dubé, V. Lapointe, V. Lesage, V., H. Bourdages, D. Lefaivre, S. Senneville and C. Chion. 2016. Définition et caractérisation de l'habitat du béluga (Delphinapterus leucas) de l'estuaire du Saint-Laurent selon une approche écosystémique. Secr. can. de consult. sci. du MPO. Doc. de rech. 2016/052. vi + 93 p.
Beluga Calves Relative Summer Density in the St. Lawrence Estuary
This layer represents the relative summer density of beluga calves in the St. Lawrence Estuary based on 35 aerial surveys carried out from 1990 to 2009. The boundaries of the areas were determined by combining the highest densities until the desired proportion of the population was obtained using kernel density estimation in order to obtain a smooth and continuous density distribution.Within Fisheries and Oceans Canada (DFO), the ecosystem approach is considered as a tool for operational planning, project implementation and preparation of advisory reports. In response to this strategic direction, the DFO science division is committed to implement the ecosystem approach in its activities as Ecosystem Research Initiatives (ERI) in each of the six administrative regions of DFO. In the Quebec region, two pilot projects were implemented, of which one aimed to define and characterize the habitat of the St. Lawrence beluga (Delphinapterus leucas).Data sources and references:DFO. 2016. Ecosystem Research Initiative (ERI): Integrated Advice on the Summer Habitat of the St. Lawrence Estuary Beluga (Delphinapterus leucas). DFO Can. Sci. Advis. Sec. Sci. Advis. Rep. 2016/030. Mosnier, A., R. Larocque, M. Lebeuf, J.-F. Gosselin, S. Dubé, V. Lapointe, V. Lesage, V., H. Bourdages, D. Lefaivre, S. Senneville and C. Chion. 2016. Définition et caractérisation de l'habitat du béluga (Delphinapterus leucas) de l'estuaire du Saint-Laurent selon une approche écosystémique. Secr. can. de consult. sci. du MPO. Doc. de rech. 2016/052. vi + 93 p.
Sponge significant concentration areas in the Gulf of St. Lawrence
Identification of significant concentrations of sponges in the Gulf of St. Lawrence biogeographic unit using Kernel density estimation (KDE).This method was applied to create a modelled biomass surface for each taxa and an aerial expansion method was permitted to identify significant concentrations. Only geo-referenced biomass data have been used to identify the “hot spots”. The borders of the areas were refined using knowledge of null catches and species distribution models. Predictive models were produced using a random forest machine-learning technique. For more details, please refer to this report: Kenchington, E., L. Beazley, C. Lirette, F.J. Murillo, J. Guijarro, V. Wareham, K. Gilkinson, M. Koen Alonso, H. Benoît, H. Bourdages, B. Sainte-Marie, M. Treble, and T. Siferd. 2016. Delineation of Coral and Sponge Significant Benthic Areas in Eastern Canada Using Kernel Density Analyses and Species Distribution Models. DFO Can. Sci. Advis. Sec. Res. Doc. 2016/093. vi + 178 p.http://waves-vagues.dfo-mpo.gc.ca/Library/40577806.pdfThe present layer only contains the analysis results for sponges. Purpose:As part of the Canada's commitment to the identification and protection of sensitive benthic marine ecosystems, maps of the location of significant concentrations of corals and sponges on the east coast of Canada were produced through quantitative analyses of research vessel trawl survey data, supplemented with other data sources where available. The taxa analyzed are sponges (Porifera), large and small gorgonian corals (Alcyonacea), and sea pens (Pennatulacea). However, only the sponges (Porifera) and sea pens (Pennatulacea) have been considered in the analysis concerning the Gulf of St. Lawrence biogeographic unit.
Kelp Beds - Coastal Resource Information Management System (CRIMS)
Distribution of kelp beds in coastal British Columbia. Attribute information includes relative abundance, species, biomass and density of the beds. CRIMS is a legacy dataset of BC coastal resource data that was acquired in a systematic and synoptic manner from 1979 and was intermittently updated throughout the years. Resource information was collected in nine study areas using a peer-reviewed provincial Resource Information Standards Committee consisting of DFO Fishery Officers, First Nations, and other subject matter experts. There are currently no plans to update this legacy data.
Average Relative Density of Fish Functional Groups and Species in the Newfoundland and Labrador Shelves Bioregion, 1981-2017
The Science Branch of Fisheries and Oceans Canada (DFO) in the Newfoundland and Labrador (NL) region has been conducting multispecies research vessel (RV) surveys using a stratified random survey design since the early 1970s. The DFO RV survey dataset represents the longest time series of species data in the NL region, making it ideal for mapping the average relative densities of species over time. Average relative density maps depict the interpolated densities (calculated from kg/tow) of fish species or functional groups. These densities are averaged over each time series (Engel and Campelen) and include data from all available seasons, so they represent persistent areas of relatively high and low densities for that species or functional group for the duration of the time series, independent of season. These maps are well suited as decision support tools related to conservation areas and marine spatial planning. These maps can also inform other processes that require information on areas important to marine fish, such as environmental assessments. Spring, fall, and winter data from the DFO RV survey between 1981 and 2017, inclusive, were used for the analysis. Due to a gear change from an Engel 145 Hi-Lift Otter Trawl to a Campelen 1800 Shrimp Trawl in 1995, the time series is treated as two separate datasets. NAFO Divisions 2J3KLNOP were sampled during the Engel time series and Division 2H was added for the Campelen time series. The data were filtered prior to use so that only core strata (areas consistently sampled across years) were included, resulting in most deep water and inshore sets being excluded in this analysis. Weight per tow (kg/tow; standardized for tow length for each gear type) data for fish, shrimp, and crab species were extracted from the database, and all successful sets from regular multispecies surveys were used for analyses. Eight fish functional groups (groups of species of similar size and diet) were identified based on the RV survey dataset: small benthivores, medium benthivores, large benthivores, piscivores, plank-piscivores, planktivores, shrimp, and forage fish. Data for each functional group were mapped three ways: all species, dominant species (i.e. top 90% biomass), and non-dominant species. In total, 40 dominant species and/or at-risk species (i.e. COSEWIC endangered, threatened, special concern; SARA; DFO/NAFO depleted) were mapped individually. To identify the average relative density, independent of seasonality, the spring, fall, and winter survey sets were compiled into a composite dataset using a log transformation on the biomass (kg/tow). For functional groups, these values were then standardized across each group. Absences (0 kg/tow catch values) were included. A continuous raster with a 4x4km resolution was generated through ordinary kriging. The raster was clipped to an 8-km buffer of the RV survey extent and the zero values were then removed. The results of this process are maps depicting the average relative density of fish functional groups and selected individual species during both the Engel (1981-1995) and Campelen (1995-2017) time series. Note that the original units (e.g. kg/tow) are no longer relevant due to data processing. Cell values are not comparable between groups or species; when mapping, all numeric values should be removed from the labels and legend, with relative qualifiers (“high” and “low”) used instead. More detailed information can be found in Wells et al. (2021). References: Wells, N.J., Pretty, C., Warren, M., Novaczek, E. and Koen-Alonso, M. 2021. Average Relative Density of Fish Species and Functional Groups in the Newfoundland and Labrador Shelves Bioregion from 1981-2017. Can. Tech. Rep. Fish. Aquat. Sci. 3427: viii + 76 p.
Kernel Density Analyses of Coral and Sponge Catches from Research Vessel Survey Data (2016)
Kernel density estimation (KDE) utilizes spatially explicit data to model the distribution of a variable of interest. It is a simple non-parametric neighbour-based smoothing function that relies on few assumptions about the structure of the observed data. It has been used in ecology to identify hotspots, that is, areas of relatively high biomass/abundance, and in 2010 was used by Fisheries and Oceans Canada to delineate significant concentrations of corals and sponges. The same approach has been used successfully in the Northwest Atlantic Fisheries Organization (NAFO) Regulatory Area. Here, we update the previous analyses with the catch records from up to 5 additional years of trawl survey data from Eastern Canada, including the Gulf of Saint Lawrence. We applied kernel density estimation to create a modelled biomass surface for each of sponges, small and large gorgonian corals, and sea pens, and applied an aerial expansion method to identify significant concentrations of these taxa. We compared our results to those obtained previously and provided maps of significant concentrations as well as point data co-ordinates for catches above the threshold values used to construct the significant area polygons. The borders of the polygons can be refined using knowledge of null catches and species distribution models of species presence/absence and/or biomass.
Reproductive Ecology of Zostera marina L. (Eelgrass) Across Varying Environmental Conditions
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
Seaweed medium to high density areas in the Chaleur Bay, the Estuary and the Gulf of St. Lawrence
Production of a layer that includes the known information on seaweed medium to high density areas in the Chaleur Bay, the Estuary and the Gulf of St. Lawrence according to a literature review of documents produced between 1995 and 1999.Additional InformationSeaweed density areas were produced according to a literature review of the following documents:Mariculture de Percé inc. 1995. Essai d'augmentation de la biomasse du homard "Récifs artificiels", Rapport no 95, Programme d'essai et d'expérimentation halieutiques et aquicoles.Lemieux, C. 1995. Acquisition de connaissances des habitats côtiers dans la région de Rimouski (1995). Rapport du Groupe-Conseil GENIVAR présenté au Ministère des Pêches et des Océans du Canada, Division de la Gestion de l’Habitat du Poisson, 52 pages + 2 annexes.Belzile, L., Lalumière, R., Cloutier, O. et J.F. Martel. 1997. Inventaire des laminaires dans la Baie des Chaleurs entre Miguasha et Bonaventure. Rapport conjoint Groupe-conseil Génivar inc. et Regroupement des pêcheurs professionnels du sud de la Gaspésie pour le compte de Pêches et Océans Canada, Québec. 13 pagesVaillancourt, M.-A. et C. Lafontaine. 1999. Caractérisation de la Baie Mitis. Jardins de Métis et Pêches et Océans Canada. Grand-Métis. 185 p.Calderón, I. 1996. Caractérisation de la végétation et de la faune ichtyenne de la baie de Sept-Îles. Document réalisé par la Corporation de protection de l'environnement de Sept-Îles pour Pêches et Océans Canada. 26p. + 5 annexes.Calderón, I. 1996. Caractérisation des habitats du poisson de la baie de Sept-Îles - Phase II. Corporation de protection de l'environnement de Sept-Îles. 37 pages.
Spatial Density of Soybean in Canada
This data shows spatial density of Soybean cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which Soybeans are more expected. Results are provided as rasters with numerical values for each pixel indicating the spatial density calculated for that location. Higher spatial density values represent higher likelihood to have Soybeans based on analysis of the 2009 to 2021 AAFC annual crop inventory data.
Spatial Density of Rye in Canada
This data shows spatial density of rye cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which rye are more expected. Results are provided as rasters with numerical values for each pixel indicating the spatial density calculated for that location. Higher spatial density values represent higher likelihood to have rye based on analysis of the 2009 to 2021 AAFC annual crop inventory data.
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