The biomass density changes (%) observed for all modelled functional groups at the end of the first bottom-up forcing scenario.

<p>The biomass density changes (%) observed for all modelled functional groups at the end of the first bottom-up forcing scenario.</p

The time series for primary production in the Southern Ocean used in the three Ecosim scenarios that incorporated bottom-up forcing.

<p>The time series for primary production in the Southern Ocean used in the three Ecosim scenarios that incorporated bottom-up forcing.</p

The changes in predator biomass densities coincident with the peak “krill surplus” in the first three Ecosim scenarios.

<p>The changes in predator biomass densities coincident with the peak “krill surplus” in the first three Ecosim scenarios.</p

Supplementary Tables from Southern Ocean biological iron cycling in the pre-whaling and present ecosystems

This study aimed to create the first model of biological iron (Fe) cycling in the Southern Ocean food web. Two biomass-balanced Ecopath models were built to represent pre- and post-whaling ecosystem states (1900 and 2008). Functional group biomasses (tonnes wet weight km^-2) were converted to biogenic Fe pools (kg Fe km^-2) using published Fe content ranges. In both models, biogenic Fe pools and consumption in the pelagic Southern Ocean were highest for plankton and small nektonic groups. The production of plankton biomass, particularly unicellular groups, accounted for the highest annual Fe demand. Microzooplankton contributed most to biological Fe recycling, followed by carnivorous zooplankton and krill. Biological Fe recycling matched previous estimates, and under most conditions, could entirely meet the Fe demand of bacterioplankton and phytoplankton. Iron recycling by large baleen whales was reduced 10-fold by whaling between 1900 and 2008. However, even under the 1900 scenario, the contribution of whales to biological Fe recycling was negligible compared with that of planktonic consumers. These models are a first step in examining oceanic-scale biological Fe cycling, highlighting gaps in our present knowledge and key questions for future research on the role of marine food webs in the cycling of trace elements in the sea

The biomass density changes (%) observed for all modelled functional groups at the peak of the simulated “krill surplus” (1954) in the second bottom-up forcing scenario.

<p>The biomass density changes (%) observed for all modelled functional groups at the peak of the simulated “krill surplus” (1954) in the second bottom-up forcing scenario.</p

The biomass density changes (%) observed for all modeled functional groups at the end of the second bottom-up forcing scenario.

<p>The biomass density changes (%) observed for all modeled functional groups at the end of the second bottom-up forcing scenario.</p

The biomass density time series for large rorquals (dotted) and small rorquals (dashed), reconstructed from IWC catch data tabulated by Leaper et al.

<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0114978#pone.0114978-Leaper1" target="_blank">[1]</a></p

The biomass density changes (%) observed for all modelled functional groups at the peak of the simulated “krill surplus” (1976) in the first bottom-up forcing scenario.

<p>The biomass density changes (%) observed for all modelled functional groups at the peak of the simulated “krill surplus” (1976) in the first bottom-up forcing scenario.</p

The biomass density changes (%) observed for all modelled functional groups in response to the simulated depletion of both large and small rorquals.

<p>The biomass density changes (%) observed for all modelled functional groups in response to the simulated depletion of both large and small rorquals.</p

Grand mean functional group biomass changes by EwE MSE scenario.

<p>a) <i>F</i>_{<i>target</i>} = 0.1 except <i>SOK</i> (0.01) and the <i>MSY</i>_<i>s</i> and <i>MSY</i>_<i>e</i> scenarios (0.4 and 0.6, respectively, at the higher <i>B</i>_<i>lim</i>) b) <i>F</i>_{<i>target</i>} = 0.2 except <i>SOK</i> (0.01) and the <i>MSY</i>_<i>s</i> and <i>MSY</i>_<i>e</i> scenarios (0.4 and 0.6, respectively, at the lower <i>B</i>_<i>lim</i>).</p