Modelling the spatial distribution of cetaceans in New Zealand waters
Aim Cetaceans are inherently difficult to study due to their elusive, pelagic and often highly migratory nature. New Zealand waters are home to 50% of the world's cetacean species, but their spatial distributions are poorly known. Here, we model distributions of 30 cetacean taxa using an extens...
Published in: | Diversity and Distributions |
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Language: | English |
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Wiley
2020
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Online Access: | https://archimer.ifremer.fr/doc/00606/71827/70345.pdf https://archimer.ifremer.fr/doc/00606/71827/70346.pdf https://doi.org/10.1111/ddi.13035 https://archimer.ifremer.fr/doc/00606/71827/ |
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ftarchimer:oai:archimer.ifremer.fr:71827 2023-05-15T15:45:15+02:00 Modelling the spatial distribution of cetaceans in New Zealand waters Stephenson, Fabrice Goetz, Kimberly Sharp, Ben R. Mouton, Theophile Beets, Fenna L. Roberts, Jim Macdiarmid, Alison B. Constantine, Rochelle Lundquist, Carolyn J. Sarmento Cabral, Juliano 2020-04 application/pdf https://archimer.ifremer.fr/doc/00606/71827/70345.pdf https://archimer.ifremer.fr/doc/00606/71827/70346.pdf https://doi.org/10.1111/ddi.13035 https://archimer.ifremer.fr/doc/00606/71827/ eng eng Wiley https://archimer.ifremer.fr/doc/00606/71827/70345.pdf https://archimer.ifremer.fr/doc/00606/71827/70346.pdf doi:10.1111/ddi.13035 https://archimer.ifremer.fr/doc/00606/71827/ info:eu-repo/semantics/openAccess restricted use Diversity And Distributions (1366-9516) (Wiley), 2020-04 , Vol. 26 , N. 4 , P. 495-516 boosted regression tree models cetacean distribution New Zealand relative environmental suitability models spatial management species distribution models text Publication info:eu-repo/semantics/article 2020 ftarchimer https://doi.org/10.1111/ddi.13035 2022-02-22T23:50:59Z Aim Cetaceans are inherently difficult to study due to their elusive, pelagic and often highly migratory nature. New Zealand waters are home to 50% of the world's cetacean species, but their spatial distributions are poorly known. Here, we model distributions of 30 cetacean taxa using an extensive at‐sea sightings dataset (n > 14,000) and high‐resolution (1 km2) environmental data layers. Location New Zealand's Exclusive Economic Zone (EEZ). Methods Two models were used to predict probability of species occurrence based on available sightings records. For taxa with <50 sightings (n = 15), Relative Environmental Suitability (RES), and for taxa with ≥50 sightings (n = 15), Boosted Regression Tree (BRT) models were used. Independently collected presence/absence data were used for further model evaluation for a subset of taxa. Results RES models for rarely sighted species showed reasonable fits to available sightings and stranding data based on literature and expert knowledge on the species' autecology. BRT models showed high predictive power for commonly sighted species (AUC: 0.79–0.99). Important variables for predicting the occurrence of cetacean taxa were temperature residuals, bathymetry, distance to the 500 m isobath, mixed layer depth and water turbidity. Cetacean distribution patterns varied from highly localised, nearshore (e.g., Hector's dolphin), to more ubiquitous (e.g., common dolphin) to primarily offshore species (e.g., blue whale). Cetacean richness based on stacked species occurrence layers illustrated patterns of fewer inshore taxa with localised richness hotspots, and higher offshore richness especially in locales of the Macquarie Ridge, Bounty Trough and Chatham Rise. Main conclusions Predicted spatial distributions fill a major knowledge gap towards informing future assessments and conservation planning for cetaceans in New Zealand's extensive EEZ. While sightings datasets were not spatially comprehensive for any taxa, these two best available approaches allow for predictive modelling of both more common, and of rarely sighted, cetacean species with limited available information. Article in Journal/Newspaper Blue whale Archimer (Archive Institutionnelle de l'Ifremer - Institut français de recherche pour l'exploitation de la mer) Bounty Trough ENVELOPE(178.070,178.070,-45.499,-45.499) New Zealand Diversity and Distributions 26 4 495 516 |
institution |
Open Polar |
collection |
Archimer (Archive Institutionnelle de l'Ifremer - Institut français de recherche pour l'exploitation de la mer) |
op_collection_id |
ftarchimer |
language |
English |
topic |
boosted regression tree models cetacean distribution New Zealand relative environmental suitability models spatial management species distribution models |
spellingShingle |
boosted regression tree models cetacean distribution New Zealand relative environmental suitability models spatial management species distribution models Stephenson, Fabrice Goetz, Kimberly Sharp, Ben R. Mouton, Theophile Beets, Fenna L. Roberts, Jim Macdiarmid, Alison B. Constantine, Rochelle Lundquist, Carolyn J. Sarmento Cabral, Juliano Modelling the spatial distribution of cetaceans in New Zealand waters |
topic_facet |
boosted regression tree models cetacean distribution New Zealand relative environmental suitability models spatial management species distribution models |
description |
Aim Cetaceans are inherently difficult to study due to their elusive, pelagic and often highly migratory nature. New Zealand waters are home to 50% of the world's cetacean species, but their spatial distributions are poorly known. Here, we model distributions of 30 cetacean taxa using an extensive at‐sea sightings dataset (n > 14,000) and high‐resolution (1 km2) environmental data layers. Location New Zealand's Exclusive Economic Zone (EEZ). Methods Two models were used to predict probability of species occurrence based on available sightings records. For taxa with <50 sightings (n = 15), Relative Environmental Suitability (RES), and for taxa with ≥50 sightings (n = 15), Boosted Regression Tree (BRT) models were used. Independently collected presence/absence data were used for further model evaluation for a subset of taxa. Results RES models for rarely sighted species showed reasonable fits to available sightings and stranding data based on literature and expert knowledge on the species' autecology. BRT models showed high predictive power for commonly sighted species (AUC: 0.79–0.99). Important variables for predicting the occurrence of cetacean taxa were temperature residuals, bathymetry, distance to the 500 m isobath, mixed layer depth and water turbidity. Cetacean distribution patterns varied from highly localised, nearshore (e.g., Hector's dolphin), to more ubiquitous (e.g., common dolphin) to primarily offshore species (e.g., blue whale). Cetacean richness based on stacked species occurrence layers illustrated patterns of fewer inshore taxa with localised richness hotspots, and higher offshore richness especially in locales of the Macquarie Ridge, Bounty Trough and Chatham Rise. Main conclusions Predicted spatial distributions fill a major knowledge gap towards informing future assessments and conservation planning for cetaceans in New Zealand's extensive EEZ. While sightings datasets were not spatially comprehensive for any taxa, these two best available approaches allow for predictive modelling of both more common, and of rarely sighted, cetacean species with limited available information. |
format |
Article in Journal/Newspaper |
author |
Stephenson, Fabrice Goetz, Kimberly Sharp, Ben R. Mouton, Theophile Beets, Fenna L. Roberts, Jim Macdiarmid, Alison B. Constantine, Rochelle Lundquist, Carolyn J. Sarmento Cabral, Juliano |
author_facet |
Stephenson, Fabrice Goetz, Kimberly Sharp, Ben R. Mouton, Theophile Beets, Fenna L. Roberts, Jim Macdiarmid, Alison B. Constantine, Rochelle Lundquist, Carolyn J. Sarmento Cabral, Juliano |
author_sort |
Stephenson, Fabrice |
title |
Modelling the spatial distribution of cetaceans in New Zealand waters |
title_short |
Modelling the spatial distribution of cetaceans in New Zealand waters |
title_full |
Modelling the spatial distribution of cetaceans in New Zealand waters |
title_fullStr |
Modelling the spatial distribution of cetaceans in New Zealand waters |
title_full_unstemmed |
Modelling the spatial distribution of cetaceans in New Zealand waters |
title_sort |
modelling the spatial distribution of cetaceans in new zealand waters |
publisher |
Wiley |
publishDate |
2020 |
url |
https://archimer.ifremer.fr/doc/00606/71827/70345.pdf https://archimer.ifremer.fr/doc/00606/71827/70346.pdf https://doi.org/10.1111/ddi.13035 https://archimer.ifremer.fr/doc/00606/71827/ |
long_lat |
ENVELOPE(178.070,178.070,-45.499,-45.499) |
geographic |
Bounty Trough New Zealand |
geographic_facet |
Bounty Trough New Zealand |
genre |
Blue whale |
genre_facet |
Blue whale |
op_source |
Diversity And Distributions (1366-9516) (Wiley), 2020-04 , Vol. 26 , N. 4 , P. 495-516 |
op_relation |
https://archimer.ifremer.fr/doc/00606/71827/70345.pdf https://archimer.ifremer.fr/doc/00606/71827/70346.pdf doi:10.1111/ddi.13035 https://archimer.ifremer.fr/doc/00606/71827/ |
op_rights |
info:eu-repo/semantics/openAccess restricted use |
op_doi |
https://doi.org/10.1111/ddi.13035 |
container_title |
Diversity and Distributions |
container_volume |
26 |
container_issue |
4 |
container_start_page |
495 |
op_container_end_page |
516 |
_version_ |
1766379576231985152 |