Evaluating top-down, bottom-up, and environmental drivers of pelagic food web dynamics along an estuarine gradient

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1002/ecy.4274. This is version 4 of this Preprint.

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Tanya L Rogers, Samuel M Bashevkin , Christina E Burdi, Denise D Colombano, Peter N Dudley, Brian Mahardja, Lara Mitchell, Sarah Perry, Parsa Saffarinia


Identification of the key biotic and abiotic drivers within food webs is important for understanding species abundance changes in ecosystems, particularly across ecotones where there may be strong variation in interaction strengths. Using structural equation models and four decades of integrated data from the San Francisco Estuary, we investigated the relative effects of top-down, bottom-up, and environmental drivers on multiple trophic levels of the pelagic food web along an estuarine salinity gradient and at both annual and monthly temporal resolutions. We found that interactions varied across the estuarine gradient, and that the detectability of different interactions depended on timescale. For example, for zooplankton and estuarine fishes, bottom-up effects appeared to be stronger in the freshwater upstream regions, while top-down effects were stronger in the brackish downstream regions. Some relationships (e.g., bottom-up effects of phytoplankton on zooplankton) were seen primarily at annual timescales, whereas others (e.g., temperature effects) were only observed at monthly timescales. We also found that the net effect of environmental drivers was similar to or greater than bottom-up and top-down effects for all food web components. These findings can help identify which trophic levels or environmental factors could be targeted by management actions to have the greatest impact on estuarine forage fishes, and the spatial and temporal scale at which responses might be observed. More broadly, this study highlights how environmental gradients can structure community interactions and how long-term datasets can be leveraged to generate insights across multiple scales.




Aquaculture and Fisheries Life Sciences, Ecology and Evolutionary Biology, Life Sciences, Terrestrial and Aquatic Ecology


bottom-up, Estuaries, fish, food webs, invasive species, long term monitoring, phytoplankton, Structural Equation Model, top-down, Zooplankton


Published: 2022-12-15 13:37

Last Updated: 2024-02-29 19:41

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CC BY Attribution 4.0 International

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Data and Code Availability Statement:
Data and code are available at https://github.com/Delta-Stewardship-Council/swg-21-foodwebs