Benthic habitats of the Saba Bank

Habitat mapping is crucial for understanding habitat connectivity and for spatial planning, environmental management, conservation, and targeted research, including long-term change monitoring. However, such information has been lacking for many Dutch Caribbean islands, especially regarding marine habitats. This study used 2144 georeferenced images from different surveys to develop habitat models predicting the distribution of habitat types within the Saba Bank National Park. The habitat models link environmental factors to species or habitat occurrence, enabling predictions in unsurveyed areas with known covariates. Machine learning techniques (Random Forests, Gradient Boosting, and weighted K Nearest Neighbor) were applied to interpret and predict ten habitat types over the Bank. Three models were created for each technique: 1) utilizing only geographic coordinates; 2) incorporating covariables such as depth, distance to the edge of the Bank, Topographic Position Index (TPI), and Terrain Ruggedness index (TRI); 3) a combination of the previous two models. All models performed well, accurately predicting habitat types between 67 and 74% of the georeferenced images. However, the most natural representation occurred with models combining geographic and covariate variables. Predicted habitats include coral reef, patch reef, gorgonian reef, sargassum fields, cyanobacteria-dominated fields, Lobophora fields, Neogoniolithon- Lyngbya habitat, other macroalgae fields, sand with a mix of species, and bare sand. Habitat distribution appears to be related to the main currents in the area and depth, with coral reefs occurring mainly along the southern and eastern edge of the Bank, with gorgonians and other soft corals dominating there the shallow areas. Macroalgae, including fields of Sargassum, dominate the back-reef area. Extensive sand plains dominate the center of the Bank, and along the north-western and northern edge of the Bank, between 40 and 60m depth Lobophora fields can occur. In the south-eastern back reef area a number of mounds built up by the coralline alga Neogoniolithon occur. The Luymes Bank, the northeastern part of the Saba Bank, was the only area that was not correctly predicted, indicating that additional field-based observations are needed to refine results in this aree.

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Main Authors: Meesters, Erik H., van der Ouderaa, Isabelle, Wilkes, Tony, van Leijsen, Michelle, Debrot, Dolfi, Mücher, Sander, Doğruer, Gülşah
Format: External research report biblioteca
Language:English
Published: Wageningen Marine Research
Subjects:Life Science,
Online Access:https://research.wur.nl/en/publications/benthic-habitats-of-the-saba-bank
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spelling dig-wur-nl-wurpubs-6282822024-12-03 Meesters, Erik H. van der Ouderaa, Isabelle Wilkes, Tony van Leijsen, Michelle Debrot, Dolfi Mücher, Sander Doğruer, Gülşah External research report Benthic habitats of the Saba Bank 2024 Habitat mapping is crucial for understanding habitat connectivity and for spatial planning, environmental management, conservation, and targeted research, including long-term change monitoring. However, such information has been lacking for many Dutch Caribbean islands, especially regarding marine habitats. This study used 2144 georeferenced images from different surveys to develop habitat models predicting the distribution of habitat types within the Saba Bank National Park. The habitat models link environmental factors to species or habitat occurrence, enabling predictions in unsurveyed areas with known covariates. Machine learning techniques (Random Forests, Gradient Boosting, and weighted K Nearest Neighbor) were applied to interpret and predict ten habitat types over the Bank. Three models were created for each technique: 1) utilizing only geographic coordinates; 2) incorporating covariables such as depth, distance to the edge of the Bank, Topographic Position Index (TPI), and Terrain Ruggedness index (TRI); 3) a combination of the previous two models. All models performed well, accurately predicting habitat types between 67 and 74% of the georeferenced images. However, the most natural representation occurred with models combining geographic and covariate variables. Predicted habitats include coral reef, patch reef, gorgonian reef, sargassum fields, cyanobacteria-dominated fields, Lobophora fields, Neogoniolithon- Lyngbya habitat, other macroalgae fields, sand with a mix of species, and bare sand. Habitat distribution appears to be related to the main currents in the area and depth, with coral reefs occurring mainly along the southern and eastern edge of the Bank, with gorgonians and other soft corals dominating there the shallow areas. Macroalgae, including fields of Sargassum, dominate the back-reef area. Extensive sand plains dominate the center of the Bank, and along the north-western and northern edge of the Bank, between 40 and 60m depth Lobophora fields can occur. In the south-eastern back reef area a number of mounds built up by the coralline alga Neogoniolithon occur. The Luymes Bank, the northeastern part of the Saba Bank, was the only area that was not correctly predicted, indicating that additional field-based observations are needed to refine results in this aree. en Wageningen Marine Research application/pdf https://research.wur.nl/en/publications/benthic-habitats-of-the-saba-bank 10.18174/644676 https://edepot.wur.nl/644676 Life Science (c) publisher Wageningen University & Research
institution WUR NL
collection DSpace
country Países bajos
countrycode NL
component Bibliográfico
access En linea
databasecode dig-wur-nl
tag biblioteca
region Europa del Oeste
libraryname WUR Library Netherlands
language English
topic Life Science
Life Science
spellingShingle Life Science
Life Science
Meesters, Erik H.
van der Ouderaa, Isabelle
Wilkes, Tony
van Leijsen, Michelle
Debrot, Dolfi
Mücher, Sander
Doğruer, Gülşah
Benthic habitats of the Saba Bank
description Habitat mapping is crucial for understanding habitat connectivity and for spatial planning, environmental management, conservation, and targeted research, including long-term change monitoring. However, such information has been lacking for many Dutch Caribbean islands, especially regarding marine habitats. This study used 2144 georeferenced images from different surveys to develop habitat models predicting the distribution of habitat types within the Saba Bank National Park. The habitat models link environmental factors to species or habitat occurrence, enabling predictions in unsurveyed areas with known covariates. Machine learning techniques (Random Forests, Gradient Boosting, and weighted K Nearest Neighbor) were applied to interpret and predict ten habitat types over the Bank. Three models were created for each technique: 1) utilizing only geographic coordinates; 2) incorporating covariables such as depth, distance to the edge of the Bank, Topographic Position Index (TPI), and Terrain Ruggedness index (TRI); 3) a combination of the previous two models. All models performed well, accurately predicting habitat types between 67 and 74% of the georeferenced images. However, the most natural representation occurred with models combining geographic and covariate variables. Predicted habitats include coral reef, patch reef, gorgonian reef, sargassum fields, cyanobacteria-dominated fields, Lobophora fields, Neogoniolithon- Lyngbya habitat, other macroalgae fields, sand with a mix of species, and bare sand. Habitat distribution appears to be related to the main currents in the area and depth, with coral reefs occurring mainly along the southern and eastern edge of the Bank, with gorgonians and other soft corals dominating there the shallow areas. Macroalgae, including fields of Sargassum, dominate the back-reef area. Extensive sand plains dominate the center of the Bank, and along the north-western and northern edge of the Bank, between 40 and 60m depth Lobophora fields can occur. In the south-eastern back reef area a number of mounds built up by the coralline alga Neogoniolithon occur. The Luymes Bank, the northeastern part of the Saba Bank, was the only area that was not correctly predicted, indicating that additional field-based observations are needed to refine results in this aree.
format External research report
topic_facet Life Science
author Meesters, Erik H.
van der Ouderaa, Isabelle
Wilkes, Tony
van Leijsen, Michelle
Debrot, Dolfi
Mücher, Sander
Doğruer, Gülşah
author_facet Meesters, Erik H.
van der Ouderaa, Isabelle
Wilkes, Tony
van Leijsen, Michelle
Debrot, Dolfi
Mücher, Sander
Doğruer, Gülşah
author_sort Meesters, Erik H.
title Benthic habitats of the Saba Bank
title_short Benthic habitats of the Saba Bank
title_full Benthic habitats of the Saba Bank
title_fullStr Benthic habitats of the Saba Bank
title_full_unstemmed Benthic habitats of the Saba Bank
title_sort benthic habitats of the saba bank
publisher Wageningen Marine Research
url https://research.wur.nl/en/publications/benthic-habitats-of-the-saba-bank
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AT wilkestony benthichabitatsofthesababank
AT vanleijsenmichelle benthichabitatsofthesababank
AT debrotdolfi benthichabitatsofthesababank
AT muchersander benthichabitatsofthesababank
AT dogruergulsah benthichabitatsofthesababank
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