Ecological Sustainability Assessment for the Firth of Thames Shellfish Aquaculture: Biological Modelling
1. Identification information
Status
Complete
Data Collection Date
Summary
Three separate simulation models were used, and three distinct farm scenarios modelled (no farms (NF), existing farms (0), and existing farms plus a maximal modelled western Firth Aquaculture Management Area (AMA) (1)). For each farm scenario simulations were made under six distinct hydrodynamic conditions.
The simulations indicated that under the existing farm scenario, the Firth-wide numbers of snapper larvae surviving to age 8 days post-spawn may be reduced by 2-6 percent relative to the NF scenario, and by 2.5-15 percent under scenario 1.
Two biological models were used to examine the influence of mussel farming upon phytoplankton and zooplankton, a 'logistic' and a 'biophysical' model. The logistic model suggested that the concentrations of fast growing plankton will be reduced by less than 10 percent within the farms, and that vulnerable plankton will suffer depletion of >20 percent within the farm, with depletion halos extending several km beyond the farm. The biophysical model indicated that farms will tend to suppress total phytoplankton abundance during spring, and predicted depletion of 30 percent within the farm, extending several km downstream of the farm. The model also showed that phytoplankton enhancement may result from the farming activities.
The modelled western Firth AMA was predicted to have larger impacts than any of the existing farms, reflecting its larger size, the fact that it will occupy shallower water than most existing farms, and that current speeds are lower in this region that this AMA would occupy.
Purpose:
NIWA were engaged by the Auckland Regional Council, Environment Waikato and the Western Firth Mussel Consortium to make quantitative predictions of the degree to which large-scale mussel farming in the western Firth would influence snapper egg / larval survival and plankton abundance and spatial distribution.
Content
Table of Contents:
2 Introduction
2.1 Comparison with earlier results
3 Methods
3.1 Weather/season scenario descriptions
3.2 Farm scenario descriptions
3.3 Farm details
3.3.1 Line arrangements
3.4 Model domain
3.5 The empirical model
3.6 The biophysical model
3.7 Mussel feeding sub-model
3.8 Implementing farms within the simulation models
3.9 Numerical solution
3.10 Simulations undertaken
4 Results
4.1 Interpretation of the plots
4.2 Snapper model
4.3 Logistic plankton
4.4 Biophysical model
5 Discussion
5.1 General comments
5.2 Over-estimation of mussel ingestion rates
5.3 Snapper model
5.4 Logistic plankton model
5.5 Biophysical model
6 Ecological implications
6.1 Snapper model
6.2 Plankton models
7 Conclusions and recommendations
8 References
Study Types
- Unknown
Categories
- Consents and Structures
- Aquaculture
- Water quality
2. Contact information
Commissioning Agencies
- Auckland Regional Council
- Environment Waikato
- Western Firth Mussel Consortium
Contact Organisations
- Environment Waikato
3. Spatial information
Geographic Coverage
Firth of Thames
Grid Coordinates
Locations
-
NameNZMG Easting0NZMG Northing0LocationFirth of ThamesEast Coast
4. Data acquisition information
Collection Date
Methodology
Frequency of collection:
One off data collection
5. Data quality information
Known Limitations
6. Distribution information
Format
Applications
Availability
Report freely available from Auckland Regional Council or Environment Waikato.
Sensitivity/Confidentiality:
Report publicly available. For raw data contact ARC, EW or NIWA.
7. Status information
Data Status
Study complete.
8. Metadata information
General Notes
Related Links
Publications
- Broekhuizen, N., Ren, J., Zeldis, J., Stephens, S. 2005: Ecological Sustainability Assessment for the Firth of Thames Shellfish Aquaculture : Tasks 2-4 - Biological Modelling. Environment Waikato Technical Report TR 2005/06, Auckland Regional Council Technical Publication TP 253. Prepared by NIWA. 62 p.
Related Publications
Related Datasets
9. Related files
No files have been attached to this dataset