Misiuk Benjamin, Lecours Vincent et Bell Trevor. (2018). A multiscale approach to mapping seabed sediments. PLOS ONE, 13, (2), e0193647.
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URL officielle: http://dx.doi.org/doi:10.1371/journal.pone.0193647
Résumé
Benthic habitat maps, including maps of seabed sediments, have become critical spatial-decision support tools for marine ecological management and conservation. Despite the increasing recognition that environmental variables should be considered at multiple spatial scales, variables used in habitat mapping are often implemented at a single scale. The objective of this study was to evaluate the potential for using environmental variables at multiple scales for modelling and mapping seabed sediments. Sixteen environmental variables were derived from multibeam echosounder data collected near Qikiqtarjuaq, Nunavut, Canada at eight spatial scales ranging from 5 to 275 m, and were tested as predictor variables for modelling seabed sediment distributions. Using grain size data obtained from grab samples, we tested which scales of each predictor variable contributed most to sediment models. Results showed that the default scale was often not the best. Out of 129 potential scale-dependent variables, 11 were selected to model the additive log-ratio of mud and sand at five different scales, and 15 were selected to model the additive log-ratio of gravel and sand, also at five different scales. Boosted Regression Tree models that explained between 46.4 and 56.3% of statistical deviance produced multiscale predictions of mud, sand, and gravel that were correlated with cross-validated test data (Spearman’s ρmud = 0.77, ρsand = 0.71, ρgravel = 0.58). Predictions of individual size fractions were classified to produce a map of seabed sediments that is useful for marine spatial planning. Based on the scale-dependence of variables in this study, we concluded that spatial scale consideration is at least as important as variable selection in seabed mapping.
Type de document: | Article publié dans une revue avec comité d'évaluation |
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ISSN: | 1932-6203 |
Volume: | 13 |
Numéro: | 2 |
Pages: | e0193647 |
Version évaluée par les pairs: | Oui |
Date: | 28 Février 2018 |
Nombre de pages: | 1 |
Identifiant unique: | 10.1371/journal.pone.0193647 |
Sujets: | Sciences naturelles et génie > Sciences appliquées > Océanographie Sciences naturelles et génie > Sciences naturelles > Sciences de la terre (géologie, géographie) |
Département, module, service et unité de recherche: | Unités de recherche > Centre de recherche sur la Boréalie (CREB) Départements et modules > Département des sciences humaines |
Mots-clés: | dependent variable, Nunavut, particle size, prediction, predictor variable, sediment, ecosystem, sea, spatial analysis, statistical model |
Déposé le: | 31 oct. 2023 13:53 |
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Dernière modification: | 31 juill. 2024 15:47 |
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