Bridging between litterbags and whole-ecosystem experiments: a new approach for studying lake sediments

Submitted: 18 October 2016
Accepted: 13 January 2017
Published: 22 February 2017
Abstract Views: 4409
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Authors

Nearshore sediments have a major influence over the functioning of aquatic ecosystems, but predicting their response to future environmental change has proven difficult. Previous manipulative experiments have faced challenges controlling environmental conditions, replicating sediment mixing dynamics, and extrapolating across spatial scales. Here we describe a new approach to manipulate lake sediments that overcomes previous concerns about reproducibility and environment controls, whilst also bridging the gap between smaller microcosm or litterbag experiments and whole-ecosystem manipulations. Our approach involves submerging moderate-sized (~15 L) artificial substrates that have been standardised to mimic natural sediments within the littoral zones of lakes.  We show that this approach can accurately mirror the absolute dissolved organic carbon concentrations and pH of pore water, and to a lesser degree inorganic carbon concentrations, from natural lake sediments with similar organic matter profiles. On a relative basis, all measured variables had similar temporal dynamics between artificial and adjacent natural sediments. Late-summer zooplankton biomass also did not differ between natural and artificial sediments.  By offering a more realistic way to manipulate freshwater sediments than previously possible, our approach can improve predictions of lake ecosystems in a changing world.

 
This work is licensed under a Creative Commons Attribution 4.0 International.

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Natural Environment Research Council

How to Cite

Tanentzap, Andrew J., Erik J. Szkokan-Emilson, Cyndy M. Desjardins, Chloe Orland, Kurt Yakimovich, Randy Dirszowsky, Nadia Mykytczuk, Nathan Basiliko, and John Gunn. 2017. “Bridging Between Litterbags and Whole-Ecosystem Experiments: A New Approach for Studying Lake Sediments”. Journal of Limnology 76 (2). https://doi.org/10.4081/jlimnol.2017.1588.

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