Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Gulf of St. Lawrence

Species distribution modelling is often employed to predict the distribution of a species in unsampled areas based on its species-environment relationship in sampled areas, and is becoming a more widely used tool in the management of fisheries resources and benthic ecosystems. Continuous surfaces of...

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Main Author: Lirette, Camille
Format: Dataset
Language:unknown
Published: Mendeley 2020
Subjects:
Online Access:https://dx.doi.org/10.17632/2zj42mxzjp.1
https://data.mendeley.com/datasets/2zj42mxzjp/1
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spelling ftdatacite:10.17632/2zj42mxzjp.1 2023-05-15T17:34:08+02:00 Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Gulf of St. Lawrence Lirette, Camille 2020 https://dx.doi.org/10.17632/2zj42mxzjp.1 https://data.mendeley.com/datasets/2zj42mxzjp/1 unknown Mendeley https://dx.doi.org/10.17632/2zj42mxzjp 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/10.17632/2zj42mxzjp.1 https://doi.org/10.17632/2zj42mxzjp 2021-11-05T12:55:41Z Species distribution modelling is often employed to predict the distribution of a species in unsampled areas based on its species-environment relationship in sampled areas, and is becoming a more widely used tool in the management of fisheries resources and benthic ecosystems. Continuous surfaces of environmental data are necessary in order to predict over the entire spatial domain of the model. There are growing numbers of online sources of environmental data assembled for the purpose of habitat classification or species distribution modelling. However, the data hosted on these sites is often on differing spatial scales. Such data are often spatially interpolated to provide continuous surfaces that can be used for modelling at all spatial scales. In this report we provide detailed information on 113 environmental variables for the Gulf of St. Lawrence that have been obtained from a broad range of data sources and spatially interpolated using geostatistical methods. For each variable we document the underlying data distribution and relevant diagnostics of the interpolation models, and present the final interpolated surface. These interpolated layers have been compiled in a common (raster) format and archived at the Bedford Institute of Oceanography. The information detailed in this report will help future users of these layers make informed decisions on which variables are appropriate for their modelling needs. 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 Gulf of St. Lawrence
topic_facet North Atlantic
Benthic Ecology
description Species distribution modelling is often employed to predict the distribution of a species in unsampled areas based on its species-environment relationship in sampled areas, and is becoming a more widely used tool in the management of fisheries resources and benthic ecosystems. Continuous surfaces of environmental data are necessary in order to predict over the entire spatial domain of the model. There are growing numbers of online sources of environmental data assembled for the purpose of habitat classification or species distribution modelling. However, the data hosted on these sites is often on differing spatial scales. Such data are often spatially interpolated to provide continuous surfaces that can be used for modelling at all spatial scales. In this report we provide detailed information on 113 environmental variables for the Gulf of St. Lawrence that have been obtained from a broad range of data sources and spatially interpolated using geostatistical methods. For each variable we document the underlying data distribution and relevant diagnostics of the interpolation models, and present the final interpolated surface. These interpolated layers have been compiled in a common (raster) format and archived at the Bedford Institute of Oceanography. The information detailed in this report will help future users of these layers make informed decisions on which variables are appropriate for their modelling needs.
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 Gulf of St. Lawrence
title_short Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Gulf of St. Lawrence
title_full Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Gulf of St. Lawrence
title_fullStr Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Gulf of St. Lawrence
title_full_unstemmed Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Gulf of St. Lawrence
title_sort characteristics of environmental data layers for use in species distribution modelling in the gulf of st. lawrence
publisher Mendeley
publishDate 2020
url https://dx.doi.org/10.17632/2zj42mxzjp.1
https://data.mendeley.com/datasets/2zj42mxzjp/1
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/10.17632/2zj42mxzjp
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/10.17632/2zj42mxzjp.1
https://doi.org/10.17632/2zj42mxzjp
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