Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Maritimes Region

Species distribution models (SDMs) are tools that combine species observations of occurrence, abundance, or biomass with environmental variables to predict the distribution of a species in unsampled locations. To produce accurate predictions of occurrence, abundance or biomass distribution, a wide r...

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Main Author: Lirette, Camille
Format: Dataset
Language:unknown
Published: Mendeley 2020
Subjects:
Online Access:https://dx.doi.org/10.17632/34hhtjyyd3
https://data.mendeley.com/datasets/34hhtjyyd3
id ftdatacite:10.17632/34hhtjyyd3
record_format openpolar
spelling ftdatacite:10.17632/34hhtjyyd3 2023-05-15T17:34:08+02:00 Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Maritimes Region Lirette, Camille 2020 https://dx.doi.org/10.17632/34hhtjyyd3 https://data.mendeley.com/datasets/34hhtjyyd3 unknown Mendeley https://dx.doi.org/10.17632/34hhtjyyd3.1 Creative Commons Attribution 4.0 International info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY North Atlantic Benthic Ecology dataset Dataset 2020 ftdatacite https://doi.org/10.17632/34hhtjyyd3 https://doi.org/10.17632/34hhtjyyd3.1 2021-11-05T12:55:41Z Species distribution models (SDMs) are tools that combine species observations of occurrence, abundance, or biomass with environmental variables to predict the distribution of a species in unsampled locations. To produce accurate predictions of occurrence, abundance or biomass distribution, a wide range of physical and/or biological variables is desirable. Such data is often collected over limited or irregular spatial scales, and require the application of geospatial techniques to produce continuous environmental surfaces that can be used for modelling at all spatial scales. Here we provide a review of 102 environmental data layers that were compiled for the entire spatial extent of Fisheries and Oceans Canada’s (DFO) Maritimes Region. Variables were obtained from a broad range of physical and biological data sources and spatially interpolated using geostatistical methods. For each variable we document the underlying data distribution, provide relevant diagnostics of the interpolation models and an assessment of model performance, and present the final standard error and interpolation surfaces. These layers have been archived in a common (raster) format at the Bedford Institute of Oceanography to facilitate future use. Based on the diagnostic summaries in this report, a subset of these variables has subsequently been used in species distribution models to predict the distribution of deep-water corals, sponges, and other significant benthic taxa in the Maritimes Region. Dataset North Atlantic DataCite Metadata Store (German National Library of Science and Technology) Bedford ENVELOPE(-67.150,-67.150,-66.467,-66.467)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic North Atlantic
Benthic Ecology
spellingShingle North Atlantic
Benthic Ecology
Lirette, Camille
Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Maritimes Region
topic_facet North Atlantic
Benthic Ecology
description Species distribution models (SDMs) are tools that combine species observations of occurrence, abundance, or biomass with environmental variables to predict the distribution of a species in unsampled locations. To produce accurate predictions of occurrence, abundance or biomass distribution, a wide range of physical and/or biological variables is desirable. Such data is often collected over limited or irregular spatial scales, and require the application of geospatial techniques to produce continuous environmental surfaces that can be used for modelling at all spatial scales. Here we provide a review of 102 environmental data layers that were compiled for the entire spatial extent of Fisheries and Oceans Canada’s (DFO) Maritimes Region. Variables were obtained from a broad range of physical and biological data sources and spatially interpolated using geostatistical methods. For each variable we document the underlying data distribution, provide relevant diagnostics of the interpolation models and an assessment of model performance, and present the final standard error and interpolation surfaces. These layers have been archived in a common (raster) format at the Bedford Institute of Oceanography to facilitate future use. Based on the diagnostic summaries in this report, a subset of these variables has subsequently been used in species distribution models to predict the distribution of deep-water corals, sponges, and other significant benthic taxa in the Maritimes Region.
format Dataset
author Lirette, Camille
author_facet Lirette, Camille
author_sort Lirette, Camille
title Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Maritimes Region
title_short Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Maritimes Region
title_full Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Maritimes Region
title_fullStr Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Maritimes Region
title_full_unstemmed Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Maritimes Region
title_sort characteristics of environmental data layers for use in species distribution modelling in the maritimes region
publisher Mendeley
publishDate 2020
url https://dx.doi.org/10.17632/34hhtjyyd3
https://data.mendeley.com/datasets/34hhtjyyd3
long_lat ENVELOPE(-67.150,-67.150,-66.467,-66.467)
geographic Bedford
geographic_facet Bedford
genre North Atlantic
genre_facet North Atlantic
op_relation https://dx.doi.org/10.17632/34hhtjyyd3.1
op_rights Creative Commons Attribution 4.0 International
info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
op_rightsnorm CC-BY
op_doi https://doi.org/10.17632/34hhtjyyd3
https://doi.org/10.17632/34hhtjyyd3.1
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