Data

CMIP6 simulated zooplankton dynamics: grazing, mortality and other data streams

University of Tasmania, Australia
Rohr, Tyler
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25959/B7XN-W655&rft.title=CMIP6 simulated zooplankton dynamics: grazing, mortality and other data streams&rft.identifier=10.25959/B7XN-W655&rft.description=We compare the formulation and emergent dynamics of 11 CMIP6 IPCC marine biogeochemical models. We find that the largest source of uncertainty across model simulations of marine carbon cycling is grazing pressure (i.e. the phytoplankton specific loss rate to grazing). Variability in grazing pressure is driven by large differences in zooplankton specific grazing rates, which are not sufficiently compensated for by offsetting differences in zooplankton specific mortality rates. Models instead must tune the turnover rate of the phytoplankton population to balance large differences in top-down grazing pressure and constrain net primary production. We then run a controlled sensitivity experiment in a global, coupled ocean-biogeochemistry model to test the sensitivity of marine carbon cycling to this uncertainty and find that even when tuned to identical net primary production, export and secondary production remain extremely sensitive to grazing, likely biasing predictions of future climate states and food security.Maintenance and Update Frequency: notPlannedStatement: All data is model output. Either created in simulations run on NCI or publicly hosted (but further processed) CMIP6 data. Please see linked manuscript [to be added soon] and attached ReadMe file for full documentation on model files and methodology.&rft.creator=Rohr, Tyler &rft.date=2023&rft_rights=Data, products and services from IMAS are provided as is without any warranty as to fitness for a particular purpose.&rft_rights=&rft_rights= https://creativecommons.org/licenses/by/4.0/&rft_rights=https://licensebuttons.net/l/by/4.0/88x31.png&rft_rights=WWW:LINK-1.0-http--related&rft_rights=License Graphic&rft_rights=Creative Commons Attribution 4.0 International License&rft_rights=CC-BY&rft_rights=4.0&rft_rights=http://creativecommons.org/international/&rft_rights=WWW:LINK-1.0-http--related&rft_rights=WWW:LINK-1.0-http--related&rft_rights=License Text&rft_rights=Cite data as: Rohr, T. (2023). CMIP6 simulated zooplankton dynamics: grazing, mortality and other data streams [Data set]. Institute for Marine and Antarctic Studies (IMAS), University of Tasmania (UTAS). https://doi.org/10.25959/B7XN-W655&rft_rights=Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0&rft_subject=oceans&rft_subject=BIOGEOCHEMICAL CYCLES&rft_subject=EARTH SCIENCE&rft_subject=BIOSPHERE&rft_subject=ECOLOGICAL DYNAMICS&rft_subject=ECOSYSTEM FUNCTIONS&rft_subject=ZOOPLANKTON&rft_subject=AQUATIC ECOSYSTEMS&rft_subject=PLANKTON&rft_subject=COUPLED CLIMATE MODELS&rft_subject=EARTH SCIENCE SERVICES&rft_subject=MODELS&rft_subject=Biological Oceanography&rft_subject=EARTH SCIENCES&rft_subject=OCEANOGRAPHY&rft_subject=Chemical Oceanography&rft_subject=Physical Oceanography&rft_subject=Marine and Estuarine Ecology (incl. Marine Ichthyology)&rft_subject=BIOLOGICAL SCIENCES&rft_subject=ECOLOGY&rft.type=dataset&rft.language=English Access the data

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Cite data as: Rohr, T. (2023). CMIP6 simulated zooplankton dynamics: grazing, mortality and other data streams [Data set]. Institute for Marine and Antarctic Studies (IMAS), University of Tasmania (UTAS). https://doi.org/10.25959/B7XN-W655

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Brief description

We compare the formulation and emergent dynamics of 11 CMIP6 IPCC marine biogeochemical models. We find that the largest source of uncertainty across model simulations of marine carbon cycling is grazing pressure (i.e. the phytoplankton specific loss rate to grazing). Variability in grazing pressure is driven by large differences in zooplankton specific grazing rates, which are not sufficiently compensated for by offsetting differences in zooplankton specific mortality rates. Models instead must tune the turnover rate of the phytoplankton population to balance large differences in top-down grazing pressure and constrain net primary production. We then run a controlled sensitivity experiment in a global, coupled ocean-biogeochemistry model to test the sensitivity of marine carbon cycling to this uncertainty and find that even when tuned to identical net primary production, export and secondary production remain extremely sensitive to grazing, likely biasing predictions of future climate states and food security.

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Maintenance and Update Frequency: notPlanned
Statement: All data is model output. Either created in simulations run on NCI or publicly hosted (but further processed) CMIP6 data. Please see linked manuscript [to be added soon] and attached ReadMe file for full documentation on model files and methodology.

Issued: 17 05 2023

Data time period: 2022-09-01 to 2023-09-07

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