Coordinating Working Party on Fishery Statistics (CWP)

Time units

The CALENDAR (or CIVIL) YEAR, i.e., the period between 1 January and 31 December, is the annual time unit normally used in fishery statistics.

For certain specific purposes (e.g. for Antarctic pelagic whaling fisheries; and fiscal purposes) it is deemed more appropriate to use a SPLIT YEAR. Such situations arise when the sector under consideration exhibits appreciable activity over the end of the calendar year. The end points of the split year may be selected as desired but should be preferably at a time when activity in the sector is reduced. For Antarctic pelagic whaling fisheries, the split year is 1 July-30 June. Countries using a split year are: Australia (1 July - 30 June); Bangladesh; Myanmar (1 July - 30 June); Nepal ; US Virgin Islands (1 July - 30 June). [See also: Key economic variables and indicators]

The Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) covering the FAO Major Fishing Areas 48, 58 and 88, used to collect data on a split year basis 1 July - 30 June up to June 2002. In November 2002 the Commission adopted the "CCAMLR fishing season" as the annual interval for reporting fishery activities. The "CCAMLR fishing season" begins on 1 December and ends on 30 November of the following year. All fisheries managed by CCAMLR now operate within this annual interval, and the "CCAMLR fishing season" has replaced the previously used "Split Year".

In tabulations where space restricts the labeling of a split year to a single year or where data for calendar and split years are tabulated together, the practice is for the split year to be represented by the calendar year in which the split year ends. Thus a split year recorded in a statistical bulletin as 2002 refers to the split year 2001-2002.

Attention is drawn to the apparent anomalies that may be observed when comparing data from two sectors of fishery statistics. For example, in highly seasonal fisheries occurring at the end of the time period, recorded data on catches may not be matched by corresponding data on landings. This is explained by the catches being made in one time period, and the landings in the following one. Similar situations can arise with fishery commodities production and trade data.