Habitat suitability and ecoscape predictions for vulnerable and foundation cold-water coral of the Azores (NE Atlantic)

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Bibliographic Details
Main Authors: Taranto, Gerald Hechter, González-Irusta, José-Manuel, Domínguez-Carrió, Carlos, Pham, Christopher Kim, Tempera, Fernando, Carreiro-Silva, Marina, Morato, Telmo
Format: Dataset Open Access
Language:en
Published: PANGAEA 2020
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author Taranto, Gerald Hechter
González-Irusta, José-Manuel
Domínguez-Carrió, Carlos
Pham, Christopher Kim
Tempera, Fernando
Carreiro-Silva, Marina
Morato, Telmo
author_facet Taranto, Gerald Hechter
González-Irusta, José-Manuel
Domínguez-Carrió, Carlos
Pham, Christopher Kim
Tempera, Fernando
Carreiro-Silva, Marina
Morato, Telmo
collection Datos científicos de ciencias marinas y ambientales
contents We developed habitat suitability models for 14 vulnerable and foundation CWC taxa of the Azores employing an original combination of traditional and novel modelling techniques. We introduced the term ecoscape to identify a sensu stricto environmental filter that delimits the potential distribution of coexisting species. --- The published data include: 1. GAM and Maxent habitat suitability predictions classified as high (3), medium (2) or low (1) confidence. Confidence in habitat suitability prediction was estimated with a bootstrap process and depended on the frequency individual raster cells were classified as suitable based on sensitivity‐specificity sum maximization thresholds. Based on this process habitat suitability predictions were categorized as low [1-50%), medium [50-90%) or high [90-100%] confidence. 2. Combined Suitability Maps. GAM and Maxent predictions were combined and each raster cell predicted as suitable was classified based on local fuzzy matching and bootstrap frequencies as follow: value of 1.0 in .tif files: high confidence suitable cells, raster cells predicted as suitable with high confidence by GAM or Maxent, or both and with a local fuzzy similarity greater than 0.5; value of 0.5 in .tif files: medium confidence suitable cells, raster cells predicted as suitable with medium confidence by both GAM and Maxent OR raster cells predicted as suitable with high confidence by GAM or Maxent and with a local fuzzy similarity not equal to zero; value of 0.0 in .tif files: low confidence suitable cell, any other cell predicted as suitable by GAM or Maxent, or both. 3. Overlapping habitat suitability predictions. The .tif file shows the number of taxa predicted as suitable for each raster cell. 4. Regional ecoscapes. Ecoscapes were classified as shallow areas (1), upper slopes (2) and lower slopes (3). 5. Environmetal clusters used to define regional ecoscapes. Clusters were derived using the X-means algorithm.
format Dataset Open Access
id pangaea_https___doi_org_10_1594_PANGAEA_921282
institution PANGAEA
language en
publishDate 2020
publisher PANGAEA
record_format pangaea
spellingShingle Habitat suitability and ecoscape predictions for vulnerable and foundation cold-water coral of the Azores (NE Atlantic)
Taranto, Gerald Hechter
González-Irusta, José-Manuel
Domínguez-Carrió, Carlos
Pham, Christopher Kim
Tempera, Fernando
Carreiro-Silva, Marina
Morato, Telmo
Atlantic; Azores; Azores_reef; BIO; Biology; cold-water corals; Deep sea; ecoscape; environmental filtering; foundation species; habitat suitability; Image; Image (File Size); Image (Media Type); Species; vulnerable marine ecosystems
We developed habitat suitability models for 14 vulnerable and foundation CWC taxa of the Azores employing an original combination of traditional and novel modelling techniques. We introduced the term ecoscape to identify a sensu stricto environmental filter that delimits the potential distribution of coexisting species. --- The published data include: 1. GAM and Maxent habitat suitability predictions classified as high (3), medium (2) or low (1) confidence. Confidence in habitat suitability prediction was estimated with a bootstrap process and depended on the frequency individual raster cells were classified as suitable based on sensitivity‐specificity sum maximization thresholds. Based on this process habitat suitability predictions were categorized as low [1-50%), medium [50-90%) or high [90-100%] confidence. 2. Combined Suitability Maps. GAM and Maxent predictions were combined and each raster cell predicted as suitable was classified based on local fuzzy matching and bootstrap frequencies as follow: value of 1.0 in .tif files: high confidence suitable cells, raster cells predicted as suitable with high confidence by GAM or Maxent, or both and with a local fuzzy similarity greater than 0.5; value of 0.5 in .tif files: medium confidence suitable cells, raster cells predicted as suitable with medium confidence by both GAM and Maxent OR raster cells predicted as suitable with high confidence by GAM or Maxent and with a local fuzzy similarity not equal to zero; value of 0.0 in .tif files: low confidence suitable cell, any other cell predicted as suitable by GAM or Maxent, or both. 3. Overlapping habitat suitability predictions. The .tif file shows the number of taxa predicted as suitable for each raster cell. 4. Regional ecoscapes. Ecoscapes were classified as shallow areas (1), upper slopes (2) and lower slopes (3). 5. Environmetal clusters used to define regional ecoscapes. Clusters were derived using the X-means algorithm.
title Habitat suitability and ecoscape predictions for vulnerable and foundation cold-water coral of the Azores (NE Atlantic)
topic Atlantic; Azores; Azores_reef; BIO; Biology; cold-water corals; Deep sea; ecoscape; environmental filtering; foundation species; habitat suitability; Image; Image (File Size); Image (Media Type); Species; vulnerable marine ecosystems
url https://doi.org/10.1594/PANGAEA.921282