Finfish bycatch taken by the U.S. Gulf of Mexico shrimp fishery is an important issue in the management of fisheries resources given the perceived high mortality of the different fish stocks taken as bycatch in the region. Bycatch data are characterized by a high number of low catches, a few high catches, and depending on the finfish species, a significant proportion of observations with zero bycatch. An evaluation of the current general linear model for generating bycatch estimates indicates that the bycatch data do not conform to the assumptions of this model because bycatch estimates depend upon choices within the model that can significantly change the results of the model. These choices include the constant value added to catch-per-unit-of-effort (CPUE) values prior to the logarithmic transformation (to avoid undefined logarithms with zero CPUEs) and the standard time-unit selection for calculating CPUE values from catch in numbers and variable tow times. Currently a value of one is added to observed CPUE, and a constant time unit of one hour has been used; however, these choices are somewhat arbitrary. An alternative approach to model bycatch data is to use a delta distribution that has two components. Component one models the proportion of zeros, and component two models the positive catches. In our study, we applied the delta lognormal model to estimate finfish bycatch in the shrimp fishery. This model avoids the problems of 1) the addition of a constant positive value to log-transformed CPUEs, and 2) the selection of a standard time unit for CPUE calculations. Bycatch estimates determined with the current general linear model were compared with those determined with the delta lognormal model for Atlantic croaker (Micropogonias undulatus), red snapper (Lutjanus campechanus), Spanish mackerel (Scomberomorus maculatus), and all finfish from 1972 through 1995. Analysis and evaluation of the performance of the delta lognormal model indicated that this model fits the bycatch database better than the current general linear model.
|Original language||English (US)|
|Number of pages||17|
|State||Published - Jul 1 2000|
ASJC Scopus subject areas
- Aquatic Science