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...

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Published in:Diversity and Distributions
Main Authors: 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
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2020
Subjects:
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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spelling 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
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container_start_page 495
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