Measuring seining strategies and fishing success in the Philippines

We maintain that mean catch per trip is a reasonable, if indirect measure of a skipper's skill. It expresses "success per unit of effort" or the amount of catch while holding effort (trips) constant.'o Variability in mean catch per trip, therefore, describes the dimension of fishing success due to the skipper's skill, separate from effort or differences in gear or technology. We elaborated our existing multiple regression models for efficiency in order to investigate how variability in mean catch per trip is related to different fishing tactics (cf. Durrenberger and PAlsson 1986). Subsequently, we added the tactics variables to the multiple regression model for "Total Catch" to determine whether they would explain any additional variability in the standard measure of fishing success.

Table 4 indicates that the number of locations fished per two week period (Bays per Period), the number of two week periods fished throughout the season (Periods), and the number of different species caught (Species per Period) are all moderately and significantly correlated with Total Catch and Mean Catch Per Trip. The average catch size when there is a catch is also correlated with Bays per period, Trips, and Periods. These correlations together suggest that fishing effort (represented by a high number of trips throughout the entire fishing season); going after different species of fish; and trying a diversity of locations throughout the season on a regular basis are important variables that partially explain larger catches and the sizes of catches relative to the number of trips.

Two separate multiple regression analyses were carried out on the sample of 46 boats for the dependent variables "Total Catch" and "Mean Catch per Trip." The most parsimonious models that account for the greatest proportion of variability in the dependent variable, measured by r2 and adjusted r2, are presented in Table 5 and highlighted in boldface.11 The "best" regression model and the significance of each independent variable was assessed by examining the individual t-tests for each parameter, Ho: fi=0, the standardized regression coefficients (Afifi and Clark 1984:149), and the F-tests for the uniqueness index of each independent variable (Hatcher and Stepanski 1994: 407-415).'2 These statistics are presented in Table 6. Fifty-four percent of the variability in Efficiency (mean catch per trip) is accounted for by the number of crew, bays per period, and species per period (Table 5). The number of periods fished did not significantly improve the model (Table 6).

When the tactics variables were added to the regression model for fishing success, as measured by total seasonal catch, we found that 78% of the variability in catch was accounted for by the number of trips, the number of crew, and the number of bays fished per period. The number of species caught per period did not add significant information to the regression model (Tables 5 and 6). It is interesting to note that when we added our tactics variables into our original multiple regression model for total catch, their explanatory value is minimal. Only the bay in which the skipper fished is significant in the most parsimonious model, and then the overall amount of variance explained by the model is only marginally better than our original model based on trips and number of crew.