Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/124099
Title: A 50-year (1971–2021) mesozooplankton biomass data collection in the Canary Current System: Base line, gaps, trends, and future prospect
Authors: Couret Huertas, María 
Landeira Sánchez, José María 
Santana Del Pino, Ángelo 
Hernández León, Santiago Manuel 
UNESCO Clasification: 251001 Oceanografía biológica
251007 Oceanografía física
Keywords: Canary Current System
Gamm
Mesozooplankton Biomass
Seasonality
Time-Series
Issue Date: 2023
Journal: Progress in Oceanography 
Abstract: Mesozooplankton have been widely used as a bioindicator of marine ecosystems due to their key position in ocean food webs, rapid response to environmental changes, and ubiquity. Here, we show mesozooplankton biomass values in the Canary Current System from 1971 to 2021 in three different areas in relation to mesoscale activity: (1) scarcely affected by mesoscales structures (North of the Canary Islands), (2) affected by mesoscale activity and the presence of the islands (South and around the islands), and (3) close to the Northwest African coastal upwelling system (Upwelling influenced). A Generalized Additive Mixed Model (GAMM) was used to analyze the general mesozooplankton biomass trend throughout the studied period discriminating differences in biomass between the areas, annual cycle, and day-nighttime periods. The GAMM showed a significant negative biomass tendency North of the Canary Islands over the 50-year time-series compared to the South and around the islands, and significant differences between day and nighttime periods (p < 0.001) and the annual cycle (p < 0.0001). Linear regression analyses showed different tendencies depending on the area, season, and period. When comparing biomass data of the most oligotrophic zone (north of the islands) with other tropical-subtropical time-series stations in Hawaii (HOTS) and Bermuda (BATS), we obtained increasing biomass tendencies for both fixed time stations but decreasing tendency for our time-series.
URI: http://hdl.handle.net/10553/124099
ISSN: 0079-6611
DOI: 10.1016/j.pocean.2023.103073
Source: Progress in Oceanography [ISSN 0079-6611], v. 216, (Agosto 2023)
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