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Database Title

7.6 Ministry of Fisheries database: age
Keywords
Type1.
Type 11.		 New Zealand EEZ; marine; oceans; fisheries; age; growth
Abstract

Contains age readings and catalogues of otoliths and other fish ageing material obtained from the Scientific Observer programme, market sampling, and trawl surveys.

Details exist on the database for over 50 species of fish, with over 85% of the data coming from 7 species (Snapper, hoki, hake, trevally, orange roughy, ling, and red cod in declining order.) Data exists from 1972, but regular collection of large amounts of material (over 10,000 fish per year - often double this) first commenced in 1989.
Geographical Coverage New Zealand EEZ
Dataset start date. 1972
Dataset end date. Current
Status/currency. In progress
Update frequency. Annual
Maintenance. NIWA
Database size. 2,261,351 kb

 

Technical Evaluation

  
Parameters- what is measured
  • Length
  • Sex
  • Maturity
  • Age
  • Measure of confidence in age measure
  • Location
Parameters- what is calculated
  • Growth rates
  • Age at maturity
  • Longevity and estimated natural mortality
Methods used to measure parameters Data comes from:
  • Scientific observers
  • Research vessels
  • Programme to sample commercial landed fish
Scale of use. Variable
Number of records Unknown
GIS compatibility. Not to date.
It is possible as latitude and longitude data is collected.
Available formats for users. Electronic relational database; requests are usually responded to with a flat file (Excel, ASCII).
Numerous reports that analyse the data
Access constraints. By request to the Ministry of Fisheries. There is no cost for the data although there is a NIWA charge to extract data.
Measurement Accuracy To be completed by database manager.
Completeness of dataset To be completed by database manager.
Positional accuracy To be completed by database manager.
Database steward Ministry of Fisheries
Steward contact person. Kim Duckworth (Research Data Manager)
Database custodian - NIWA
Database custodian contact person Don Robertson
Database custodian Contact
Address
Phone
Fax
Email		 PO Box 14 901
Kilbirnie
Wellington
+ 64 4 386 0519
+ 64 4 386 0572
d.robertson@niwa.cri.nz
References Mackay, K.A.; George, K. 1993. Marine research database documentation:8.age. NIWA Internal Report No 214. 28p.
Bagley, N.W.; Anderson, O.F.; Hurst, R.J.; Francis, M.P.; Taylor, P.R.; Clark. M.R.; Paul, L.J. 2000. Atlas of New Zealand fish and squid distributions from mid water trawls, tuna long line sets, and aerial sightings. NIWA technical report 72. 171p.
Date metadata record prepared. June 2000
Author of metadata record. Victoria Froude

 

Management Evaluation

  
Original purpose. To improve fisheries management and to develop population models for commercial species.
Relationships with classification systems. N/A
Relationships with other databases Information from this database is used with other fisheries databases and physical databases to address various management and research questions.
Known relationships with proposed EPIP indicators. May contribute to fisheries indicators.
Database uses? Fisheries management and research
Public awareness of the database Low
Database strengths.
  • Large data set
  • Quality data
Database limitations.
  • The domestic fleet is under-represented for scientific observer data.

 

What are the Current and Emerging Uses of the Database for:

  
Assisting with determining historic state/baseline. The database can be used to assess changes over time in locations where there is a regular series of data. Various research projects have modeled changes in the main commercial species.
Assisting with determining current state/baseline. The data is used for this.
Assisting with modeling possible future outcomes. Models have been developed to assess population trends and biomass of the main commercial species (e.g. orange roughy).
Risk assessment. The models are used to project likely future outcomes and risks under different senarios for the main commercial fish species.
Monitoring site selection and sample design. N/A
Aggregating and reporting data locally, regionally or nationally. This is possible.