The interpretation of anglers’records (trout and sea trout, Salmo trutta L., and salmon, Salmo salar L.)

Abstract

Abstract. This paper collates the results of five surveys which were made to determine the average catch of anglers not making a return at game fisheries. This pilot study shows that the average catch per licence/permit () may be estimated from the average and the proportion of unprompted returns, (mu) and (pu) respectively, by the empirical equation , for trout and sea trout, Salmo trutta L. Salmon, Salmo salar L., catcrl’rates may be best estimated from . Typical values for United Kingdom waters are tabulated for recent seasons. Rod catches of stillwater and migratory fish closely follow the Negative Binomial distribution. Their means and variances are shown to be related empirically by Taylor's power law: for daily records of stillwater trout and migratory fish, and for annual records of salmon, and of sea trout. A method of estimating the expected frequency distribution of catches at any water is shown. The distribution is truncated where the nil catches are not recorded and is censored where the bag is limited; here a microcomputer was programmed to compute the estimates of the mean and variance of the catches and to print the full distribution.

Relationship between freshwater angling catch of Atlantic salmon and stock size in the River Bush, Northern Ireland

“…In many areas managers do not have access to accurate angler returns such as those available on the R. Bush, but methodology for the accurate estimation of angling catches from partial reporting of returns has been explored (Small & Downham, 1985), and various degrees of success have been claimed. Uncertainties about how representative of total angling success partial returns are, must always be included in the calculations, usually on the basis of local knowledge.…”

Assessing the status of British wild brown trout, Salmo trutta, stocks: a pilot study utilizing data from game fisheries

“…It is possible to estimate the average catcb of anglers not submitting a return from parameters of the negative binomal catch distribution for a given fishery calculated from returns submitted (Small & Downham, 1985).…”

Fishery stock assessment models

“…An alternative method of specifying σ 2 has its roots in the work of Curtis (1943) and Bartlett (1947), who showed that transformations to homogenize variance can be determined from the relationship between σ 2 and µ. Inasmuch as the σ 2 to µ relationship is seldom known, it is frequently inferred from regressions of s 2 on x (Green 1979, Taylor 1980, Taylor et al 1983). This practice is quite common in fisheries work because s 2 and x are often found to be highly correlated (Taylor 1953, Small and Downham 1985, Porch and Fox 1990, Lester et al 1991, Cyr et al 1992, Warwick and Clarke 1993, Welch and Ishida 1993, Dong and Restrepo 1996. However, the relationship between s 2 and x is largely spurious.…”