Nitrogen (macroalgae, seagrass zostera, seagrass halophila & deep seagrass) (GBR4 BGC v4.2 baseline)

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    Data gap notice

    Some dates in the 4km eReefs BioGeoChemical model v4.2 dataset have been removed because the model output for those dates was found to be inaccurate, as shown in this sample video.

    The following date ranges have been removed:

    Start date End date
    2 Jan 2011 31 Jan 2011
    2 Feb 2012 2 Mar 2012
    9 Mar 2013 7 Apr 2013
    1 Mar 2014 30 Mar 2014
    6 Apr 2015 5 May 2015
    10 May 2016 8 Jun 2016
    14 Jun 2017 13 Jul 2017
    19 Jul 2018 17 Aug 2018
    23 Aug 2019 21 Sep 2019
    26 Sep 2020 25 Oct 2020
    31 Oct 2021 29 Nov 2021
    19 May 2022 17 Jun 2022

    Please use caution when interpreting the videos in the player above.

    Although the obviously inaccurate dates have been removed, the model may take some time to recover after each disruption. As a result, data in the days and weeks following the removed periods may also be affected. The 30-day buffer used here is a visual estimate and not scientifically validated, so some remaining inaccuracies may still be present in the dataset.

    We will update this portal when corrected model output becomes available.

    These visualisations show the amount of modelled seagrass and macroalgae represented as the amount of nitrogen contained in their biomass in each modelled pixel. Seagrass and macroalgae play a key role in the nitrogen cycle of inshore areas. When they grow they take up nitrogen, phosphorus and carbon from the water into their leaf and root structures. When they die they break down and release these nutrient stores back into the water column.

    Seagrasses are represented in the model as an amount per m2 with a constant stoichiometry (C:N:P = 550:30:1) for both above-ground, and belowground, biomass, and can translocate organic matter at this constant stoichiometry between the two stores of biomass. Growth occurs only in the above-ground biomass, but losses (grazing, decay etc.) occur in both. Multiple seagrass varieties are represented. The varieties are modelled using the same equations for growth, respiration and mortality, but with different parameter values.

    The model parameters for each of the three types of seagrass are shown in Table 24 (pg 48) of Baird et al. (2019).

    Details about the macroalgae model are detailed in section 4.2 of Baird et al. (2019).

    Limitations

    These maps show model derived estimates of density for seagrass and macroalgae. They are not derived from direct observations. Observed seagrass distributions can be found from the dataset: Seagrass mapping synthesis: A resource for coastal management in the Great Barrier Reef (NESP TWQ Project 3.2.1 and 5.4, TropWATER, James Cook University).

    The BGC model assumes that mortality of macroalgae has a constant rate (see section 4.2.4 of Baird et al. (2019)) and so macroalgae dynamics are not affected by environmental factors such as cyclones.

    Macroalgae N

    Concentration of nitrogen biomass per m2 of macroalgae. Macroalgae (or seaweed) grows above all other benthic plants (corals, seagrasses, benthic microalgae). It is parameterised as a non-calcifying leafy algae, with a C:N:P ratio of 550:30:1, and a formulation for calculating the percentage of the bottom covered as 1-exp(-ΩMA MA). In the model, in the absence of both calcifying macroalgae (particularly Halimeda) and unicellular epiphytes, macroalgae represents the biomass of all seaweeds and epiphytes. Light is accessed in the following order: Macroalgae, Seagrass, Coral.

    Seagrass Zostera N

    Concentration of nitrogen biomass per m2 of a seagrass form parameterised to be similar to Zostera. This form captures light after it has passed through macroalgae and before it passes through Halophila. This form is better adapted to high light, low nutrient conditions than Halophila as a result of a deeper root structure and being able to shade it. See macroalgae for elemental ratio and bottom cover. Light is accessed in the following order: Macroalgae, Seagrass, Coral.

    Seagrass Halophila N

    Concentration of nitrogen biomass per m2 of a seagrass form parameterised to be similar to Halophila. This form captures light after it has passed through the Zostera seagrass form. The Halophila form is better adapted to low light conditions than Zostera, having a faster growth rate and lower minimum light requirement. See macroalgae for elemental ratio and bottom cover. Light is accessed in the following order: Macroalgae, Seagrass, Coral.

    Deep seagrass N

    Concentration of nitrogen biomass per m2 of a seagrass form parameterised to be similar to Halophila deciphens. This form captures light after it has passed through the Zostera and Halophila ovalis seagrass form.

    References:

    Baird, M. E., Wild-Allen, K. A., Parslow, J., Mongin, M., Robson, B., Skerratt, J., Rizwi, F., Soja-Woźniak, M., Jones, E., Herzfeld, M., Margvelashvili, N., Andrewartha, J., Langlais, C., Adams, M. P., Cherukuru, N., Gustafsson, M., Hadley, S., Ralph, P. J., Rosebrock, U., Schroeder, T., Laiolo, L., Harrison, D., Steven, A. D. L. (2019) CSIRO Environmental Modelling Suite (EMS): Scientific description of the optical and biogeochemical models (vB3p0). Geosci. Model Dev. Discuss. https://doi.org/10.5194/gmd-2019-115

    Source data

    The videos/images on this page are based on the 4km eReefs BioGeoChemical model (v4.2) run with SOURCE Catchments using Baseline catchment conditions. The model builds on the CSIRO Environmental Modelling Suite (EMS), described in the paper: Scientific description of the optical and biogeochemical models (vB3p0). The dataset metadata is available from the NCI GeoNetwork: eReefs GBR4 Biogeochemistry and Sediments v4.2 baseline catchment scenario. The raw model data is available from the NCI THREDDS server (daily, in curvilinear NetCDF format).

    Data span

    These results are based on a fixed time period (Dec 2010 - Apr 2019) hind-cast analysis developed for comparing changes in land practices. The river runoff used to drive the BGC model was provided by the SOURCE Catchments modelling.