Zooplankton Ocean Observations and Modelling (ZOOM) Task Team
Background and Rationale
Relative to our knowledge of the oceans’ phytoplankton and fisheries, we have little understanding of the zooplankton (from small nauplii @ 100 um to larval fish @ 1 cm) that link them. This is a major gap, as it is the zooplankton that graze the ocean phytoplankton (which provide ~50% of the oxygen we breathe), drive the production of our fisheries, and play a key role in global carbon export.
Broadly there are three classes of biological models using zooplankton:
- Biogeochemical models
- Size-based ecosystem models
- Food web based ecosystem models
Each category has application in Australian waters, and can be improved through using IMOS data streams. It is probable that the optimal coupling point between biogeochemical models and food-web based model is copepod-sized zooplankton. Thus the task team will be investigating both the use of zooplankton data for single classes of models, and for their coupling.
1. Review existing literature on best-practice in how zooplankton observations are currently being used in ecosystem models
2. Summarise the strengths and weaknesses of IMOS and emerging zooplankton observation platforms in relation to their potential uptake in ecosystem models, and provide recommendations.
3. Develop zooplankton fields and datasets that are directly applicable in ecosystem models and make these available through IMOS and CARS (CSIRO Atlas of Regional Seas)
4. Initiate model developments that bring model outputs closer to observations (i.e. acoustics as a model output).
5. Develop techniques to incorporate individual zooplankton data streams (i.e. LOPC, CPR etc.) into models.
6. Use the models that have incorporated multiple individual data streams to investigate the synergies / agreement / correlation between data streams.
7. Outline recommended methods for using IMOS observations for assessing biogeochemical and ecosystem models.
- Contact Details
Interested in being involved and/or informed? Please contact:
Jason Everett, University of New South Wales