Loading…

Climate-induced changes in the suitable habitat of cold-water corals and commercially important deep-sea fishes in the North Atlantic

Loading DOI record...

Climate-induced changes in the suitable habitat of cold-water corals and commercially important deep-sea fishes in the North Atlantic

DOI: 10.1594/pangaea.910319

Type: Dataset

Year: 2019

Citations: 2

AZORES DEEP-SEA RESEARCH
Dataset Open access January 2019

Climate-induced changes in the suitable habitat of cold-water corals and commercially important deep-sea fishes in the North Atlantic

Total authors
59
Involved team members
4
Citations
2
References
1

Citations by year

1 years
2023
2

Related to this work

Abstract

We used environmental niche modelling along with the best available species occurrence data and environmental parameters to model habitat suitability for key cold-water coral and commercially important deep-sea fish species under present-day (1951-2000) environmental conditions and to forecast changes under severe, high emissions future (2081-2100) climate projections (RCP8.5 scenario) for the North Atlantic Ocean (from 18°N to 76°N and 36°E to 98°W). The VME indicator taxa included Lophelia pertusa , Madrepora oculata, Desmophyllum dianthus, Acanela arbuscula, Acanthogorgia armata, and Paragorgia arborea. The six deep-sea fish species selected were: Coryphaenoides rupestris, Gadus morhua, blackbelly Helicolenus dactylopterus, Hippoglossoides platessoides, Reinhardtius hippoglossoides, and Sebastes mentella. We used an ensemble modelling approach employing three widely-used modelling methods: the Maxent maximum entropy model, Generalized Additive Models, and Random Forest. This dataset contains: 1) Predicted habitat suitability index under present-day (1951-2000) and future (2081-2100; RCP8.5) environmental conditions for twelve deep-sea species in the North Atlantic Ocean, using an ensemble modelling approach. 2) Climate-induced changes in the suitable habitat of twelve deep-sea species in the North Atlantic Ocean, as determined by binary maps built with an ensemble modelling approach and the 10-percentile training presence logistic (10th percentile) threshold. 3) Forecasted present-day suitable habitat loss (value=-1), gain (value=1), and acting as climate refugia (value=2) areas under future (2081-2100; RCP8.5) environmental conditions for twelve deep-sea species in the North Atlantic Ocean. Areas were identified from binary maps built with an ensemble modelling approach and two thresholds: 10-percentile training presence logistic threshold (10th percentile) and maximum sensitivity and specificity (MSS). Refugia areas are those areas predicted as suitable both under present-day and future conditions. All predictions were projected with the Albers equal-area conical projection centred in the middle of the study area. The grid cell resolution is of 3x3 km.

Authors

4 involved team members
D
Domínguez-Carrió, Carlos
W
Wei, C
G
García-Alegre, A
J
Javier Murillo, F
C
Callery, Oisín
C
Chimienti, G
E
Egilsdottir, Hronn
F
Freiwald, André
G
Gutierrez-Zárate, C
G
Gilkinson, Kent
W
Wareham Hayes, V E
H
Hedges, K
H
Henry, Lea Anne
J
Johnson, Devin S
K
Koen-Alonso, M
L
Lirette, C
R
Ragnarsson, Stefan Aki
R
Rice, J
R
Ross, Steve W
S
Snelgrove, Paul V R
S
Stirling, David
T
Treble, Margaret A
W
Watling, L
W
Walkusz, Wojciech
L
Levin, L A

Record details

Type
dataset
Language
EN

Keywords

Habitat Gadus Ecology Environmental niche modelling Ecological niche Fishery Environmental science Climate change Atlantic cod Sebastes Geography Species distribution Environmental data Environmental change Niche Range (aeronautics) Ensemble forecasting Environment variable Pluvial Principle of maximum entropy Environmental indicator

Related DOI items

Follow us on social media to stay updated

Location

Institute of Marine Sciences — Okeanos, University of the Azores

Departamento de Oceanografia e Pescas — Universidade dos Açores

Rua Prof. Doutor Frederico Machado, No. 4
9901-862 Horta, Portugal

Contact

FOLLOW US
ADSR

AZORES DEEP-SEA RESEARCH © 2020-2026 — RELEASE 2.1

Developed by Valter Medeiros VALTER MEDEIROS