Identification of skipjack tuna (Katsuwonus pelamis) pelagic hotspots applying a satellite remote sensing-driven analysis of ecological niche factors: A short-term run.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2020
Historique:
received: 04 05 2020
accepted: 31 07 2020
entrez: 21 8 2020
pubmed: 21 8 2020
medline: 21 10 2020
Statut: epublish

Résumé

Skipjack tuna (SJT) pelagic hotspots in the western North Pacific (WNP) were modelled using fishery and satellite remotely sensed data with Ecological Niche Factor Analysis (ENFA) models. Our objectives were to model and predict habitat hotspots for SJT and assess the monthly changes in sub-surface temperatures and mixed layer depths at fishing locations. SJT presence-only monthly resolved data, sea surface temperature, chlorophyll-a, diffuse attenuation coefficient, sea surface heights and surface wind speed were used to construct ENFA models and generate habitat suitability indices using a short-term dataset from March-November 2004. The suitability indices were then predicted for July-October (2007 and 2008). Monthly aggregated polygons of areas fished by skipjack tuna pole and line vessels were also overlaid on the predicted habitat suitability maps. Distributions of sub-surface temperatures and mixed layer depths (MLD) at fishing locations were also examined. Our results showed good fit for ENFA models, as indicated by the absolute validation index, the contrast validation index and the continuous Boyce index. The predicted hotspots showed varying concurrences when compared with 25-degree polygons derived from fished areas. Northward shifts in SJT hotspots corresponded with declining MLDs from March to September. The MLDs were shallower in summer and deeper in autumn and winter months. The habitat hotspots modeled using ENFA were consistent with the known ecology and seasonal migration pattern of SJT. The findings of this work, derived from a short-term dataset, enable identification of SJT hotspots in the WNP, thus contributing valuable information for future research on SJT habitat prediction models.

Identifiants

pubmed: 32817669
doi: 10.1371/journal.pone.0237742
pii: PONE-D-20-12929
pmc: PMC7440647
doi:

Substances chimiques

Chlorophyll A YF5Q9EJC8Y

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0237742

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Références

Proc Natl Acad Sci U S A. 1957 Mar 15;43(3):293-5
pubmed: 16590018
Science. 2010 Jul 16;329(5989):319-22
pubmed: 20576848
PLoS One. 2014 Aug 06;9(8):e103701
pubmed: 25098694
PLoS One. 2017 Oct 2;12(10):e0185601
pubmed: 28968405

Auteurs

Robinson Mugo (R)

Regional Center for Mapping of Resources for Development, Nairobi, Kenya.

Sei-Ichi Saitoh (SI)

Arctic Research Center, Hokkaido University, Hokkaido, Japan.

Hiromichi Igarashi (H)

Information Engineering Program, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan.

Takahiro Toyoda (T)

Oceanography and Geochemistry Research Department, Meteorological Research Institute, Japan Meteorological Agency, Yokosuka, Japan.

Shuhei Masuda (S)

Research Institute for Global Change (RIGC), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan.

Toshiyuki Awaji (T)

Department of Geophysics, Kyoto University, Kyoto, Japan.

Yoichi Ishikawa (Y)

Information Engineering Program, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan.

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Classifications MeSH