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ABSTRACT Marine heatwaves (MHWs) caused by multiple phenomena with days to months duration are increasingly common disturbances in ocean ecosystems. We investigated the impacts of MHWs on pelagic communities using spatially resolved time‐series of multiple trophic levels from the Southern California Current Ecosystem. Indices of phytoplankton biomass mostly declined during MHWs because of reduced nutrient supply (exceptingProchlorococcus) and were generally more sensitive to marine heatwave intensity than duration. By contrast, mesozooplankton (as estimated by zooplankton displacement volume) were somewhat more strongly correlated with MHW duration than intensity. Zooplankton anomalies were also positively correlated with fucoxanthin (diatom) anomalies, highlighting possible bottom‐up influences during MHWs. Mobile consumers (forage fish) showed more complex responses, with fish egg abundance declining during MHWs but not correlating with any MHW characteristics. Our findings provide partial evidence of how MHW characteristics can shape variable ecological responses due to the differing life spans and behaviours of different trophic levels.
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Global Distribution of Zooplankton Biomass Estimated by In Situ Imaging and Machine Learning
Zooplankton plays a major role in ocean food webs and biogeochemical cycles, and provides major ecosystem services as a main driver of the biological carbon pump and in sustaining fish communities. Zooplankton is also sensitive to its environment and reacts to its changes. To better understand the importance of zooplankton, and to inform prognostic models that try to represent them, spatially-resolved biomass estimates of key plankton taxa are desirable. In this study we predict, for the first time, the global biomass distribution of 19 zooplankton taxa (1-50 mm Equivalent Spherical Diameter) using observations with the Underwater Vision Profiler 5, a quantitative in situ imaging instrument. After classification of 466,872 organisms from more than 3,549 profiles (0-500 m) obtained between 2008 and 2019 throughout the globe, we estimated their individual biovolumes and converted them to biomass using taxa-specific conversion factors. We then associated these biomass estimates with climatologies of environmental variables (temperature, salinity, oxygen, etc.), to build habitat models using boosted regression trees. The results reveal maximal zooplankton biomass values around 60°N and 55°S as well as minimal values around the oceanic gyres. An increased zooplankton biomass is also predicted for the equator. Global integrated biomass (0-500 m) was estimated at 0.403 PgC. It was largely dominated by Copepoda (35.7%, mostly in polar regions), followed by Eumalacostraca (26.6%) Rhizaria (16.4%, mostly in the intertropical convergence zone). The machine learning approach used here is sensitive to the size of the training set and generates reliable predictions for abundant groups such as Copepoda (R2 ≈ 20-66%) but not for rare ones (Ctenophora, Cnidaria, R2 < 5%). Still, this study offers a first protocol to estimate global, spatially resolved zooplankton biomass and community composition from in situ imaging observations of individual organisms. The underlying dataset covers a period of 10 years while approaches that rely on net samples utilized datasets gathered since the 1960s. Increased use of digital imaging approaches should enable us to obtain zooplankton biomass distribution estimates at basin to global scales in shorter time frames in the future.
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- Award ID(s):
- 1654663
- PAR ID:
- 10415824
- Date Published:
- Journal Name:
- Frontiers in Marine Science
- Volume:
- 9
- ISSN:
- 2296-7745
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/fmars.2022.894372
