Issue |
Aquat. Living Resour.
Volume 36, 2023
|
|
---|---|---|
Article Number | 15 | |
Number of page(s) | 14 | |
DOI | https://doi.org/10.1051/alr/2023008 | |
Published online | 16 May 2023 |
Research Article
Portfolio of distribution maps for Octopus vulgaris off Mauritania
1
IMROP, Nouadhibou, Mauritania
2
Ministry of Fisheries and Maritime Economy, Nouakchott, Mauritania
3
MARBEC, IRD, Univ Montpellier, Ifremer, CNRS, INRAE, Sète, France
* Corresponding author: dedah.ahmed-babou@ird.fr
Handling Editor: Verena Trenkel
Received:
19
October
2022
Accepted:
30
March
2023
This study introduces the concept of portfolios of distribution maps, which consist of the reduced set of empirical orthogonal maps that best explain spatial biomass distributions of a given species over time. The approach is demonstrated for the distributions of common octopus (Octupus vulgaris) off Mauritania over the last thirty years. The maps in the portfolio are the subset of empirical orthogonal maps that allowed to recover 60% of the spatiotemporal biomass distribution variance and whose temporal weights were significantly correlated with abundance. For octopus during the hot season, one single map explained half of the overall variance of the distribution data, while during the cold season, the portfolio of octopus distribution maps consisted of four maps, with the temporal weights of the second map being negatively correlated with upwelling intensity six months before. The size of each portfolio represents the number of distinct spatial patterns describing octopus spatial distributions. Assuming that specific but hidden processes explain each biomass spatial distribution of the portfolio, the size of a map portfolio might be interpreted as a proxy for system resilience. A small portfolio could reflect systems that are more fragile.
Key words: Spatiotemporal distribution data / Maps portfolio / temporal dynamics / Octopus vulgaris
© D. Ahmed-Babou et al., Published by EDP Sciences 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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