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Modeling the spatial and seasonal distribution of offshore recreational vessels in the southeast United States
Understanding the distribution and intensity of recreational boating activities is key for managing safety as well as environmental and social impacts. Recreational boating is a very important component of the diverse maritime traffic in the southeastern United States. The seasonal distribution of o...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6261638/ https://www.ncbi.nlm.nih.gov/pubmed/30485361 http://dx.doi.org/10.1371/journal.pone.0208126 |
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author | Montes, Nancy Swett, Robert Ahrens, Robert |
author_facet | Montes, Nancy Swett, Robert Ahrens, Robert |
author_sort | Montes, Nancy |
collection | PubMed |
description | Understanding the distribution and intensity of recreational boating activities is key for managing safety as well as environmental and social impacts. Recreational boating is a very important component of the diverse maritime traffic in the southeastern United States. The seasonal distribution of offshore recreational vessels in waters off the coast of Northeast Florida and Southeast Georgia was modeled using several techniques (Poisson, negative binomial, hurdle and zero inflated modes, generalized additive models, and generalized mixed models) and by combining map-based information provided by recreational boaters with environmental and geographical variables to find the most parsimonious model. Based on model performance, the final model analysis was conducted using a GAM approach with a negative binomial distribution. The best seasonal models explained between 86.1%– 88.6% of the total deviance. For most seasons, a model that included latitude, longitude, interaction between latitude and longitude, chlorophyll a concentration, and abundance of artificial reefs resulted in the best fit. The only exception was the model for the summer season, which did not include chlorophyll a concentration. Given the complexity of the study area, with a number of maritime activities and several marine species co-occurring, these models could provide information to analyze the distribution and overlap of recreational boating trips with other maritime activities (e.g., cargo ships, commercial vessels) and species (e.g., right whales, sea turtles, sharks). These analyses could be used to decrease harmful interactions among these groups and activities. |
format | Online Article Text |
id | pubmed-6261638 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-62616382018-12-19 Modeling the spatial and seasonal distribution of offshore recreational vessels in the southeast United States Montes, Nancy Swett, Robert Ahrens, Robert PLoS One Research Article Understanding the distribution and intensity of recreational boating activities is key for managing safety as well as environmental and social impacts. Recreational boating is a very important component of the diverse maritime traffic in the southeastern United States. The seasonal distribution of offshore recreational vessels in waters off the coast of Northeast Florida and Southeast Georgia was modeled using several techniques (Poisson, negative binomial, hurdle and zero inflated modes, generalized additive models, and generalized mixed models) and by combining map-based information provided by recreational boaters with environmental and geographical variables to find the most parsimonious model. Based on model performance, the final model analysis was conducted using a GAM approach with a negative binomial distribution. The best seasonal models explained between 86.1%– 88.6% of the total deviance. For most seasons, a model that included latitude, longitude, interaction between latitude and longitude, chlorophyll a concentration, and abundance of artificial reefs resulted in the best fit. The only exception was the model for the summer season, which did not include chlorophyll a concentration. Given the complexity of the study area, with a number of maritime activities and several marine species co-occurring, these models could provide information to analyze the distribution and overlap of recreational boating trips with other maritime activities (e.g., cargo ships, commercial vessels) and species (e.g., right whales, sea turtles, sharks). These analyses could be used to decrease harmful interactions among these groups and activities. Public Library of Science 2018-11-28 /pmc/articles/PMC6261638/ /pubmed/30485361 http://dx.doi.org/10.1371/journal.pone.0208126 Text en © 2018 Montes et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Montes, Nancy Swett, Robert Ahrens, Robert Modeling the spatial and seasonal distribution of offshore recreational vessels in the southeast United States |
title | Modeling the spatial and seasonal distribution of offshore recreational vessels in the southeast United States |
title_full | Modeling the spatial and seasonal distribution of offshore recreational vessels in the southeast United States |
title_fullStr | Modeling the spatial and seasonal distribution of offshore recreational vessels in the southeast United States |
title_full_unstemmed | Modeling the spatial and seasonal distribution of offshore recreational vessels in the southeast United States |
title_short | Modeling the spatial and seasonal distribution of offshore recreational vessels in the southeast United States |
title_sort | modeling the spatial and seasonal distribution of offshore recreational vessels in the southeast united states |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6261638/ https://www.ncbi.nlm.nih.gov/pubmed/30485361 http://dx.doi.org/10.1371/journal.pone.0208126 |
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