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This dataset contains layers of predicted occurrence for 65 groundfish species as well as overall species richness (i.e., the total number of species present) in Canadian Pacific waters, and the median standard error per grid cell across all species. They cover all seafloor habitat depths between 10 and 1400 m that have a mean summer salinity above 28 PSU. Two layers are provided for each species: 1) predicted species occurrence (prob_occur) and 2) the probability that a grid cell is an occurrence hotspot for that species (hotspot_prob; defined as being in the lower of: 1) 0.8, or 2) the 80th percentile of the predicted probability of occurrence values across all grid cells that had a probability of occurrence greater than 0.05.). The first measure provides an overall prediction of the distribution of the species while the second metric identifies areas where that species is most likely to be found, accounting for uncertainty within our model. All layers are provided at a 1 km resolution.<\/SPAN><\/P> These layers were developed using a species distribution model described in Thompson et al. 2022. This model integrates data from three fisheries-independent surveys: the Fisheries and Oceans Canada (DFO) Groundfish Synoptic Bottom Trawl Surveys (Sinclair et al. 2003; Anderson et al. 2019), the DFO Groundfish Hard Bottom Longline Surveys (Lochead and Yamanaka 2006, 2007; Doherty et al. 2019), and the International Pacific Halibut Commission Fisheries Independent Setline Survey (IPHC 2021). <\/SPAN><\/P> Abstract from Thompson et al. 2022:<\/SPAN><\/P> Predictions of the distribution of groundfish species are needed to support ongoing marine spatial planning initiatives in Canadian Pacific waters. Data to inform species distribution models are available from several fisheries-independent surveys. However, no single survey covers the entire region and different gear types are required to survey the range of habitats that are occupied by groundfish. Bottom trawl gear is used to sample soft bottom habitat, predominantly on the continental shelf and slope, whereas longline gear often focuses on nearshore and hardbottom habitats where trawling is not possible. Because data from these two gear types are not directly comparable, previous species distribution models in this region have been limited to using data from one survey at a time, restricting their spatial extent and usefulness at a regional scale. Here we demonstrate a method for integrating presence-absence data across surveys and gear types that allows us to predict the coastwide distributions of 66 groundfish species in British Columbia. Our model leverages the use of available data from multiple surveys to estimate how species respond to environmental gradients while accounting for differences in catchability by the different surveys. Overall, we find that this integrated method has two main benefits: 1) it increases the accuracy of predictions in data-limited surveys and regions while having negligible impacts on the accuracy when data are already sufficient to make predictions, 2) it reduces uncertainty, resulting in tighter confidence intervals on predicted species occurrences. These benefits are particularly relevant in areas of our coast where our understanding of habitat suitability is limited due to a lack of spatially comprehensive long-term groundfish research surveys.<\/SPAN><\/P> Learn more or download this dataset from the Government of Canada's Open data portal.<\/SPAN><\/A><\/P> Cet ensemble de données contient des couches d\u2019occurrence prévue pour 65 espèces de poissons de fond ainsi que la richesse globale des espèces (c.-à-d. le nombre total d\u2019espèces présentes) dans les eaux du Pacifique canadien, et l\u2019erreur-type médiane par cellule de grille pour toutes les espèces. Il couvre toutes les profondeurs d\u2019habitat du fond marin comprises entre 10 et 1 400 mètres qui ont une salinité estivale moyenne supérieure à 28 USP. Deux couches sont fournies pour chaque espèce : 1) l\u2019occurrence prévue de l\u2019espèce (prob_occur) et 2) la probabilité qu\u2019une cellule de grille soit un point chaud d\u2019occurrence pour cette espèce (hotspot_prob) défini comme étant le seuil le plus bas entre : 1) 0,8 ou 2) le 80e centile des valeurs de probabilité d\u2019occurrence prévues pour toutes les cellules de grille dont la probabilité d\u2019occurrence était supérieure à 0.05. La première mesure fournit une prévision globale de la répartition de l\u2019espèce, tandis que la deuxième indique les régions où l\u2019espèce est la plus susceptible d\u2019être présente, ce qui tient compte de l\u2019incertitude dans notre modèle. Toutes les couches sont fournies à une résolution de 1 km.<\/SPAN><\/P> Ces couches ont été élaborées à l\u2019aide d\u2019un modèle de répartition des espèces décrit dans Thompson et al. 2022. Ce modèle intègre les données de trois relevés indépendants des pêches, soit les relevés synoptiques au chalut de fond des poissons démersaux de Pêches et Océans Canada (MPO) [Sinclair et al. 2003; Anderson et al. 2019], les relevés à la palangre sur fond dur des poissons démersaux du MPO (Lochead et Yamanaka 2006, 2007; Doherty et al. 2019) et le relevé à la ligne fixe indépendant des pêches de la Commission internationale du flétan du Pacifique (CIFP 2021). <\/SPAN><\/P> Extrait de Thompson et al. 2022: Des prévisions de la répartition des espèces de poissons de fond sont nécessaires pour soutenir les initiatives de planification spatiale marine en cours dans les eaux du Pacifique canadien. Des données pour éclairer les modèles de répartition des espèces sont disponibles à partir de plusieurs relevés indépendants des pêches. Cependant, aucun relevé unique ne couvre l\u2019ensemble de la région et différents types d\u2019engins de pêche sont nécessaires pour étudier la diversité des habitats occupés par les poissons de fond. Les engins de chalutage de fond sont utilisés pour échantillonner l\u2019habitat de fond meuble, principalement sur le plateau continental et le talus, tandis que les engins de pêche à la palangre se concentrent souvent sur les habitats littoraux et de fond dur où le chalutage est impossible. Puisque les données obtenues par les relevés de ces deux types d\u2019engins de pêche ne sont pas directement comparables, les modèles antérieurs de répartition des espèces dans cette région se sont limités à l\u2019utilisation des données d\u2019un relevé à la fois, réduisant ainsi leur étendue spatiale et leur utilité à l\u2019échelle régionale. Nous présentons ici une méthode d\u2019intégration des données sur la présence et l\u2019absence des espèces entre les relevés et les types d\u2019engins de pêche qui nous permet de prévoir la répartition sur toute la côte de 65 espèces de poissons de fond en Colombie-Britannique. Notre modèle tire parti de l\u2019utilisation des données disponibles provenant de multiples relevés pour estimer la façon dont les espèces réagissent aux gradients environnementaux tout en tenant compte des différences de capturabilité entre les différents relevés. Dans l\u2019ensemble, nous constatons que cette méthode intégrée présente deux avantages principaux : 1) elle augmente l\u2019exactitude des prévisions dans les régions et les relevés à données limitées tout en ayant des répercussions négligeables sur l\u2019exactitude lorsque les données sont déjà suffisantes pour réaliser des prévisions; 2) elle réduit l\u2019incertitude, ce qui se traduit par des intervalles de confiance plus serrés concernant les espèces qui devraient être présentes. Ces avantages sont particulièrement pertinents dans les régions de notre côte où notre compréhension de la qualité de l\u2019habitat est limitée en raison de l\u2019absence de relevés de recherche spatialement complets à long terme sur les poissons de fond.<\/SPAN><\/P> Apprenez-en plus ou téléchargez cet ensemble de données à partir du portail de données ouvertes du gouvernement du Canada.<\/SPAN><\/A><\/P> <\/P><\/DIV><\/DIV><\/DIV>",
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"description": " This dataset contains layers of predicted occurrence for 65 groundfish species as well as overall species richness (i.e., the total number of species present) in Canadian Pacific waters, and the median standard error per grid cell across all species. They cover all seafloor habitat depths between 10 and 1400 m that have a mean summer salinity above 28 PSU. Two layers are provided for each species: 1) predicted species occurrence (prob_occur) and 2) the probability that a grid cell is an occurrence hotspot for that species (hotspot_prob; defined as being in the lower of: 1) 0.8, or 2) the 80th percentile of the predicted probability of occurrence values across all grid cells that had a probability of occurrence greater than 0.05.). The first measure provides an overall prediction of the distribution of the species while the second metric identifies areas where that species is most likely to be found, accounting for uncertainty within our model. All layers are provided at a 1 km resolution.<\/SPAN><\/P> These layers were developed using a species distribution model described in Thompson et al. 2022. This model integrates data from three fisheries-independent surveys: the Fisheries and Oceans Canada (DFO) Groundfish Synoptic Bottom Trawl Surveys (Sinclair et al. 2003; Anderson et al. 2019), the DFO Groundfish Hard Bottom Longline Surveys (Lochead and Yamanaka 2006, 2007; Doherty et al. 2019), and the International Pacific Halibut Commission Fisheries Independent Setline Survey (IPHC 2021). <\/SPAN><\/P> Abstract from Thompson et al. 2022:<\/SPAN><\/P> Predictions of the distribution of groundfish species are needed to support ongoing marine spatial planning initiatives in Canadian Pacific waters. Data to inform species distribution models are available from several fisheries-independent surveys. However, no single survey covers the entire region and different gear types are required to survey the range of habitats that are occupied by groundfish. Bottom trawl gear is used to sample soft bottom habitat, predominantly on the continental shelf and slope, whereas longline gear often focuses on nearshore and hardbottom habitats where trawling is not possible. Because data from these two gear types are not directly comparable, previous species distribution models in this region have been limited to using data from one survey at a time, restricting their spatial extent and usefulness at a regional scale. Here we demonstrate a method for integrating presence-absence data across surveys and gear types that allows us to predict the coastwide distributions of 66 groundfish species in British Columbia. Our model leverages the use of available data from multiple surveys to estimate how species respond to environmental gradients while accounting for differences in catchability by the different surveys. Overall, we find that this integrated method has two main benefits: 1) it increases the accuracy of predictions in data-limited surveys and regions while having negligible impacts on the accuracy when data are already sufficient to make predictions, 2) it reduces uncertainty, resulting in tighter confidence intervals on predicted species occurrences. These benefits are particularly relevant in areas of our coast where our understanding of habitat suitability is limited due to a lack of spatially comprehensive long-term groundfish research surveys.<\/SPAN><\/P> Learn more or download this dataset from the Government of Canada's Open data portal.<\/SPAN><\/A><\/P> Cet ensemble de données contient des couches d\u2019occurrence prévue pour 65 espèces de poissons de fond ainsi que la richesse globale des espèces (c.-à-d. le nombre total d\u2019espèces présentes) dans les eaux du Pacifique canadien, et l\u2019erreur-type médiane par cellule de grille pour toutes les espèces. Il couvre toutes les profondeurs d\u2019habitat du fond marin comprises entre 10 et 1 400 mètres qui ont une salinité estivale moyenne supérieure à 28 USP. Deux couches sont fournies pour chaque espèce : 1) l\u2019occurrence prévue de l\u2019espèce (prob_occur) et 2) la probabilité qu\u2019une cellule de grille soit un point chaud d\u2019occurrence pour cette espèce (hotspot_prob) défini comme étant le seuil le plus bas entre : 1) 0,8 ou 2) le 80e centile des valeurs de probabilité d\u2019occurrence prévues pour toutes les cellules de grille dont la probabilité d\u2019occurrence était supérieure à 0.05. La première mesure fournit une prévision globale de la répartition de l\u2019espèce, tandis que la deuxième indique les régions où l\u2019espèce est la plus susceptible d\u2019être présente, ce qui tient compte de l\u2019incertitude dans notre modèle. Toutes les couches sont fournies à une résolution de 1 km.<\/SPAN><\/P> Ces couches ont été élaborées à l\u2019aide d\u2019un modèle de répartition des espèces décrit dans Thompson et al. 2022. Ce modèle intègre les données de trois relevés indépendants des pêches, soit les relevés synoptiques au chalut de fond des poissons démersaux de Pêches et Océans Canada (MPO) [Sinclair et al. 2003; Anderson et al. 2019], les relevés à la palangre sur fond dur des poissons démersaux du MPO (Lochead et Yamanaka 2006, 2007; Doherty et al. 2019) et le relevé à la ligne fixe indépendant des pêches de la Commission internationale du flétan du Pacifique (CIFP 2021). <\/SPAN><\/P> Extrait de Thompson et al. 2022: Des prévisions de la répartition des espèces de poissons de fond sont nécessaires pour soutenir les initiatives de planification spatiale marine en cours dans les eaux du Pacifique canadien. Des données pour éclairer les modèles de répartition des espèces sont disponibles à partir de plusieurs relevés indépendants des pêches. Cependant, aucun relevé unique ne couvre l\u2019ensemble de la région et différents types d\u2019engins de pêche sont nécessaires pour étudier la diversité des habitats occupés par les poissons de fond. Les engins de chalutage de fond sont utilisés pour échantillonner l\u2019habitat de fond meuble, principalement sur le plateau continental et le talus, tandis que les engins de pêche à la palangre se concentrent souvent sur les habitats littoraux et de fond dur où le chalutage est impossible. Puisque les données obtenues par les relevés de ces deux types d\u2019engins de pêche ne sont pas directement comparables, les modèles antérieurs de répartition des espèces dans cette région se sont limités à l\u2019utilisation des données d\u2019un relevé à la fois, réduisant ainsi leur étendue spatiale et leur utilité à l\u2019échelle régionale. Nous présentons ici une méthode d\u2019intégration des données sur la présence et l\u2019absence des espèces entre les relevés et les types d\u2019engins de pêche qui nous permet de prévoir la répartition sur toute la côte de 65 espèces de poissons de fond en Colombie-Britannique. Notre modèle tire parti de l\u2019utilisation des données disponibles provenant de multiples relevés pour estimer la façon dont les espèces réagissent aux gradients environnementaux tout en tenant compte des différences de capturabilité entre les différents relevés. Dans l\u2019ensemble, nous constatons que cette méthode intégrée présente deux avantages principaux : 1) elle augmente l\u2019exactitude des prévisions dans les régions et les relevés à données limitées tout en ayant des répercussions négligeables sur l\u2019exactitude lorsque les données sont déjà suffisantes pour réaliser des prévisions; 2) elle réduit l\u2019incertitude, ce qui se traduit par des intervalles de confiance plus serrés concernant les espèces qui devraient être présentes. Ces avantages sont particulièrement pertinents dans les régions de notre côte où notre compréhension de la qualité de l\u2019habitat est limitée en raison de l\u2019absence de relevés de recherche spatialement complets à long terme sur les poissons de fond.<\/SPAN><\/P> Apprenez-en plus ou téléchargez cet ensemble de données à partir du portail de données ouvertes du gouvernement du Canada.<\/SPAN><\/A><\/P> <\/P><\/DIV><\/DIV><\/DIV>",
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"Title": "Predicted distributions of 65 groundfish species in Canadian Pacific waters / Répartition prévue de 66 espèces de poissons de fond dans les eaux canadiennes du Pacifique",
"Author": "",
"Comments": " This dataset contains layers of predicted occurrence for 65 groundfish species as well as overall species richness (i.e., the total number of species present) in Canadian Pacific waters, and the median standard error per grid cell across all species. They cover all seafloor habitat depths between 10 and 1400 m that have a mean summer salinity above 28 PSU. Two layers are provided for each species: 1) predicted species occurrence (prob_occur) and 2) the probability that a grid cell is an occurrence hotspot for that species (hotspot_prob; defined as being in the lower of: 1) 0.8, or 2) the 80th percentile of the predicted probability of occurrence values across all grid cells that had a probability of occurrence greater than 0.05.). The first measure provides an overall prediction of the distribution of the species while the second metric identifies areas where that species is most likely to be found, accounting for uncertainty within our model. All layers are provided at a 1 km resolution.<\/SPAN><\/P> These layers were developed using a species distribution model described in Thompson et al. 2022. This model integrates data from three fisheries-independent surveys: the Fisheries and Oceans Canada (DFO) Groundfish Synoptic Bottom Trawl Surveys (Sinclair et al. 2003; Anderson et al. 2019), the DFO Groundfish Hard Bottom Longline Surveys (Lochead and Yamanaka 2006, 2007; Doherty et al. 2019), and the International Pacific Halibut Commission Fisheries Independent Setline Survey (IPHC 2021). <\/SPAN><\/P> Abstract from Thompson et al. 2022:<\/SPAN><\/P> Predictions of the distribution of groundfish species are needed to support ongoing marine spatial planning initiatives in Canadian Pacific waters. Data to inform species distribution models are available from several fisheries-independent surveys. However, no single survey covers the entire region and different gear types are required to survey the range of habitats that are occupied by groundfish. Bottom trawl gear is used to sample soft bottom habitat, predominantly on the continental shelf and slope, whereas longline gear often focuses on nearshore and hardbottom habitats where trawling is not possible. Because data from these two gear types are not directly comparable, previous species distribution models in this region have been limited to using data from one survey at a time, restricting their spatial extent and usefulness at a regional scale. Here we demonstrate a method for integrating presence-absence data across surveys and gear types that allows us to predict the coastwide distributions of 66 groundfish species in British Columbia. Our model leverages the use of available data from multiple surveys to estimate how species respond to environmental gradients while accounting for differences in catchability by the different surveys. Overall, we find that this integrated method has two main benefits: 1) it increases the accuracy of predictions in data-limited surveys and regions while having negligible impacts on the accuracy when data are already sufficient to make predictions, 2) it reduces uncertainty, resulting in tighter confidence intervals on predicted species occurrences. These benefits are particularly relevant in areas of our coast where our understanding of habitat suitability is limited due to a lack of spatially comprehensive long-term groundfish research surveys.<\/SPAN><\/P>