Do not forget 0-CPUE data in your CPUE standardizations to avoid wrong management advice: A case study on carp fisheries in Thailand

Abstract

We investigated how the missing 0-CPUE data in nominal CPUE datasets affects CPUE standardizations, stock assessments, stock status, and management advice. The 0-CPUE data is one of the important statistics that represents the 0 (zero) abundance index. We used the catch and CPUE datasets of five commercially important carp and carp-like species from Ubonrat Reservoir in Khon Khaen, Thailand. The data were collected by the Inland Fisheries Research and Development Division of the Department of Fisheries (DOF) of Thailand.

The results indicated as follows: (a) The nominal CPUE datasets without 0-CPUE data, produced an overestimated (biased) standardized CPUE by an average factor of 19, compared to those with unbiased CPUE datasets including 0-CPUE data; (b) this resulted in a 4.7 times higher r2 (catch versus standardized CPUE) compared to biased CPUE datasets excluding 0-CPUE data; (c) this high r2 further led to biased stock assessment (ASPIC) results without 0-CPUE data, compared to unbiased results with 0-CPUE data, i.e. on average 38 % bias in TB/TBMSY and 18 % bias in F/FMSY ;(d) such a situation will consequently lead to biased stock status; then, to wrong management advice (e.g. wrong TAC); (e) in such case, managers will advise much higher TAC, even when the stock status is in the red (unsafe) zone in the Kobe plot, which worsens the stock status (i.e. very dangerous situation); and (f) Nonetheless, these results are based on our study with carp data, so no general theoretical conclusions can be drawn, but such a tendency can be expected to occur to varying degrees.

In this regard, to avoid producing 0-CPUE, we recommend that you use the horizontal data entry format to ensure the inclusion of 0-catch (hence 0-CPUE) data in your nominal CPUE datasets. This is because it lists all species in one row and forces 0-catches to be entered so that 0-catch (0-CPUE data) cannot be ignored nor overlooked. In this way, you will not produce biased CPUE standardizations, stock assessment results, and stock status. You will then be able to provide correct management advice to your managers to ensure the sustainability of fisheries and resources.