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Testing the Potential for Predictive Modeling and Mapping and Extending Its Use as a Tool for Evaluating Management Scenarios and Economic Valuation in the Baltic Sea (PREHAB)

We evaluated performance of species distribution models for predictive mapping, and how models can be used to integrate human pressures into ecological and economic assessments. A selection of 77 biological variables (species, groups of species, and measures of biodiversity) across the Baltic Sea we...

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Autores principales: Lindegarth, Mats, Bergström, Ulf, Mattila, Johanna, Olenin, Sergej, Ollikainen, Markku, Downie, Anna-Leena, Sundblad, Göran, Bučas, Martynas, Gullström, Martin, Snickars, Martin, von Numers, Mikael, Svensson, J. Robin, Kosenius, Anna-Kaisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3888663/
https://www.ncbi.nlm.nih.gov/pubmed/24414807
http://dx.doi.org/10.1007/s13280-013-0479-2
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author Lindegarth, Mats
Bergström, Ulf
Mattila, Johanna
Olenin, Sergej
Ollikainen, Markku
Downie, Anna-Leena
Sundblad, Göran
Bučas, Martynas
Gullström, Martin
Snickars, Martin
von Numers, Mikael
Svensson, J. Robin
Kosenius, Anna-Kaisa
author_facet Lindegarth, Mats
Bergström, Ulf
Mattila, Johanna
Olenin, Sergej
Ollikainen, Markku
Downie, Anna-Leena
Sundblad, Göran
Bučas, Martynas
Gullström, Martin
Snickars, Martin
von Numers, Mikael
Svensson, J. Robin
Kosenius, Anna-Kaisa
author_sort Lindegarth, Mats
collection PubMed
description We evaluated performance of species distribution models for predictive mapping, and how models can be used to integrate human pressures into ecological and economic assessments. A selection of 77 biological variables (species, groups of species, and measures of biodiversity) across the Baltic Sea were modeled. Differences among methods, areas, predictor, and response variables were evaluated. Several methods successfully predicted abundance and occurrence of vegetation, invertebrates, fish, and functional aspects of biodiversity. Depth and substrate were among the most important predictors. Models incorporating water clarity were used to predict increasing cover of the brown alga bladderwrack Fucus vesiculosus and increasing reproduction area of perch Perca fluviatilis, but decreasing reproduction areas for pikeperch Sander lucioperca following successful implementation of the Baltic Sea Action Plan. Despite variability in estimated non-market benefits among countries, such changes were highly valued by citizens in the three Baltic countries investigated. We conclude that predictive models are powerful and useful tools for science-based management of the Baltic Sea.
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spelling pubmed-38886632014-01-14 Testing the Potential for Predictive Modeling and Mapping and Extending Its Use as a Tool for Evaluating Management Scenarios and Economic Valuation in the Baltic Sea (PREHAB) Lindegarth, Mats Bergström, Ulf Mattila, Johanna Olenin, Sergej Ollikainen, Markku Downie, Anna-Leena Sundblad, Göran Bučas, Martynas Gullström, Martin Snickars, Martin von Numers, Mikael Svensson, J. Robin Kosenius, Anna-Kaisa Ambio Article We evaluated performance of species distribution models for predictive mapping, and how models can be used to integrate human pressures into ecological and economic assessments. A selection of 77 biological variables (species, groups of species, and measures of biodiversity) across the Baltic Sea were modeled. Differences among methods, areas, predictor, and response variables were evaluated. Several methods successfully predicted abundance and occurrence of vegetation, invertebrates, fish, and functional aspects of biodiversity. Depth and substrate were among the most important predictors. Models incorporating water clarity were used to predict increasing cover of the brown alga bladderwrack Fucus vesiculosus and increasing reproduction area of perch Perca fluviatilis, but decreasing reproduction areas for pikeperch Sander lucioperca following successful implementation of the Baltic Sea Action Plan. Despite variability in estimated non-market benefits among countries, such changes were highly valued by citizens in the three Baltic countries investigated. We conclude that predictive models are powerful and useful tools for science-based management of the Baltic Sea. Springer Netherlands 2014-01-12 2014-02 /pmc/articles/PMC3888663/ /pubmed/24414807 http://dx.doi.org/10.1007/s13280-013-0479-2 Text en © The Author(s) 2013 https://creativecommons.org/licenses/by/2.0/ Open AccessThis article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Article
Lindegarth, Mats
Bergström, Ulf
Mattila, Johanna
Olenin, Sergej
Ollikainen, Markku
Downie, Anna-Leena
Sundblad, Göran
Bučas, Martynas
Gullström, Martin
Snickars, Martin
von Numers, Mikael
Svensson, J. Robin
Kosenius, Anna-Kaisa
Testing the Potential for Predictive Modeling and Mapping and Extending Its Use as a Tool for Evaluating Management Scenarios and Economic Valuation in the Baltic Sea (PREHAB)
title Testing the Potential for Predictive Modeling and Mapping and Extending Its Use as a Tool for Evaluating Management Scenarios and Economic Valuation in the Baltic Sea (PREHAB)
title_full Testing the Potential for Predictive Modeling and Mapping and Extending Its Use as a Tool for Evaluating Management Scenarios and Economic Valuation in the Baltic Sea (PREHAB)
title_fullStr Testing the Potential for Predictive Modeling and Mapping and Extending Its Use as a Tool for Evaluating Management Scenarios and Economic Valuation in the Baltic Sea (PREHAB)
title_full_unstemmed Testing the Potential for Predictive Modeling and Mapping and Extending Its Use as a Tool for Evaluating Management Scenarios and Economic Valuation in the Baltic Sea (PREHAB)
title_short Testing the Potential for Predictive Modeling and Mapping and Extending Its Use as a Tool for Evaluating Management Scenarios and Economic Valuation in the Baltic Sea (PREHAB)
title_sort testing the potential for predictive modeling and mapping and extending its use as a tool for evaluating management scenarios and economic valuation in the baltic sea (prehab)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3888663/
https://www.ncbi.nlm.nih.gov/pubmed/24414807
http://dx.doi.org/10.1007/s13280-013-0479-2
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