Benthic N pathways in illuminated and bioturbated sediments studied with network analysis

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Abstract

The regulation of benthic nitrogen (N) cycling by multiple interactions among bacteria, macrofauna, and primary producers is poorly understood. We hypothesized that a biodiverse benthic system should better exploit the benthic N-availability and retain N than a simpler one. Retention occurs by avoiding losses both to the water column via increased recycling and to the atmosphere via decreased N2 fluxes and by limiting energy-costly processes as N-fixation. We also hypothesized that primary producer-bacterial competition is reduced in the presence of macrofauna due to mobilization of refractory N pools. To this purpose, the effects of two bioturbators (the detritivorous Sparganophilus tamesis and the filter-feeding Corbicula spp.) and two primary producer growth forms (the rooted macrophyte Vallisneria spiralis and microphytobenthos) on benthic N cycling were studied. An array of N-processes were measured along a complexity gradient (from bare sediments to all combinations of the above mentioned organisms), and experimental outcomes were analyzed via ecological network analysis (ENA). This suite of algorithms, applied to the microscale, revealed differential partitioning of N fluxes among bare sediments (highest denitrification rates), sediments with macrofauna (highest recycling), and sediments with rooted plants (highest N-fixation). N2 losses and inputs were significantly reduced when all components were represented, and N requirements by primary producers were to a large extent supported by the activity of macrofauna. Ecological interactions in biodiverse benthic systems promoted an efficient exploitation of sedimentary N pools, increased the coupling between recycling and uptake, and maximized N use efficiency at the expenses of losses and imports.

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Magri, M., Benelli, S., Bondavalli, C., Bartoli, M., Christian, R. R., & Bodini, A. (2018). Benthic N pathways in illuminated and bioturbated sediments studied with network analysis. Limnology and Oceanography, 63, S68–S84. https://doi.org/10.1002/lno.10724

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