Improving the predictive capability of benthic species distribution models by incorporating oceanographic data – Towards holistic ecological modelling of a submarine canyon
Improving the predictive capability of benthic species distribution models by incorporating oceanographic data – Towards holistic ecological modelling of a submarine canyon
Submarine canyons are associated with increased biodiversity, including cold-water coral (CWC) colonies and reefs which are features of high conservation value that are under increasing anthropogenic pressure. Effective spatial management and conservation of these features requires accurate distribution maps and a deeper understanding of the processes that generate the observed distribution patterns. Predictive distribution modelling offers a powerful tool in the deep sea, where surveys are constrained by cost and technological capabilities. To date, predictive distribution modelling in canyons has focussed on integrating groundtruthed acoustically acquired datasets as proxies for environmental variables thought to influence faunal patterns. Physical oceanography is known to influence faunal patterns but has rarely been explicitly included in predictive distribution models of canyon fauna, thereby omitting key information required to adequately capture the species-environment relationships that form the basis of predictive distribution modelling. In this study, acoustic, oceanographic and biological datasets were integrated to undertake high-resolution predictions of benthic megafaunal
diversity and CWC distribution within Whittard Canyon, North-East Atlantic. The main aim was to investigate which environmental variables best predict faunal patterns in canyons and to assess whether including oceanographic data improves predictive modelling. General additive models, random forests and
boosted regression trees were used to build predictive maps for CWC occurrence, megafaunal abundance, species richness and biodiversity. To provide more robust predictions, ensemble techniques that summarise the variation in predictions and uncertainties between modelling approaches were applied to build final maps. Model performance improved with the inclusion of oceanographic data. Ensemble maps identified areas of elevated current
speed that coincided with steep ridges and escarpment walls as the areas most likely to harbour CWCs and increased biodiversity, probably linked to local hydrodynamics interacting with topography to concentrate food
resources. This study shows how incorporating oceanographic data into canyon models can broaden our understanding of processes generating faunal patterns and improve the mapping of features of conservation, supporting effective procedures for spatial ecosystem management.
Cold-water corals, Internal tide, Species distribution models, Submarine canyons
Pearman, Tabitha Rosemary Rainbow
33c2dc66-b726-4e03-b993-962f422da1d0
Robert, Katleen
a2e2547d-d9f6-4945-8f09-204079ce6c08
Callaway, Alex
508fd262-9dcf-4e4b-9500-a1dbf4c27256
Hall, Robert
2a3a90bb-b421-4487-8f38-c114ac0b7ed7
Lo Iacono, claudio
42498fdf-6b51-49af-b2bd-4f464cee7356
Huvenne, Veerle
f22be3e2-708c-491b-b985-a438470fa053
1 May 2020
Pearman, Tabitha Rosemary Rainbow
33c2dc66-b726-4e03-b993-962f422da1d0
Robert, Katleen
a2e2547d-d9f6-4945-8f09-204079ce6c08
Callaway, Alex
508fd262-9dcf-4e4b-9500-a1dbf4c27256
Hall, Robert
2a3a90bb-b421-4487-8f38-c114ac0b7ed7
Lo Iacono, claudio
42498fdf-6b51-49af-b2bd-4f464cee7356
Huvenne, Veerle
f22be3e2-708c-491b-b985-a438470fa053
Pearman, Tabitha Rosemary Rainbow, Robert, Katleen, Callaway, Alex, Hall, Robert, Lo Iacono, claudio and Huvenne, Veerle
(2020)
Improving the predictive capability of benthic species distribution models by incorporating oceanographic data – Towards holistic ecological modelling of a submarine canyon.
Progress in Oceanography, 184, [102338].
(doi:10.1016/j.pocean.2020.102338).
Abstract
Submarine canyons are associated with increased biodiversity, including cold-water coral (CWC) colonies and reefs which are features of high conservation value that are under increasing anthropogenic pressure. Effective spatial management and conservation of these features requires accurate distribution maps and a deeper understanding of the processes that generate the observed distribution patterns. Predictive distribution modelling offers a powerful tool in the deep sea, where surveys are constrained by cost and technological capabilities. To date, predictive distribution modelling in canyons has focussed on integrating groundtruthed acoustically acquired datasets as proxies for environmental variables thought to influence faunal patterns. Physical oceanography is known to influence faunal patterns but has rarely been explicitly included in predictive distribution models of canyon fauna, thereby omitting key information required to adequately capture the species-environment relationships that form the basis of predictive distribution modelling. In this study, acoustic, oceanographic and biological datasets were integrated to undertake high-resolution predictions of benthic megafaunal
diversity and CWC distribution within Whittard Canyon, North-East Atlantic. The main aim was to investigate which environmental variables best predict faunal patterns in canyons and to assess whether including oceanographic data improves predictive modelling. General additive models, random forests and
boosted regression trees were used to build predictive maps for CWC occurrence, megafaunal abundance, species richness and biodiversity. To provide more robust predictions, ensemble techniques that summarise the variation in predictions and uncertainties between modelling approaches were applied to build final maps. Model performance improved with the inclusion of oceanographic data. Ensemble maps identified areas of elevated current
speed that coincided with steep ridges and escarpment walls as the areas most likely to harbour CWCs and increased biodiversity, probably linked to local hydrodynamics interacting with topography to concentrate food
resources. This study shows how incorporating oceanographic data into canyon models can broaden our understanding of processes generating faunal patterns and improve the mapping of features of conservation, supporting effective procedures for spatial ecosystem management.
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Improving the predictive capability of benthic species
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More information
Accepted/In Press date: 17 April 2020
e-pub ahead of print date: 21 April 2020
Published date: 1 May 2020
Keywords:
Cold-water corals, Internal tide, Species distribution models, Submarine canyons
Identifiers
Local EPrints ID: 442047
URI: http://eprints.soton.ac.uk/id/eprint/442047
ISSN: 0079-6611
PURE UUID: 4171ce67-d2b1-4f60-840d-e4ed12184bc7
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Date deposited: 06 Jul 2020 16:31
Last modified: 17 Mar 2024 02:59
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Contributors
Author:
Tabitha Rosemary Rainbow Pearman
Author:
Katleen Robert
Author:
Alex Callaway
Author:
Robert Hall
Author:
claudio Lo Iacono
Author:
Veerle Huvenne
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