7116 (2) - Laserfiche WebLink

Home Browse Search

18 The lower catch ability of bottom dwelling ani- mals and in vegetated areas has been mentioned. The animals will often be immobilized out of sight of the fisherman. It may then be advantageous to use constant rather than pulsed direct current. This will shorten the attraction radius, but is partly compensated for by a reduction in the immobilization radius. Thus the possibility of getting the animals out of their cover before they are immobilized will increase. When catching (or affecting) large decapodes like crayfishes it is also advantageous to use constant direct current as the risk of the animals loosing their claws will be reduced. An interesting combination unit for catching bottom dwelling animals have been con- structed by Phillips and Scolaro (1980). They used constant direct current to make the animals leave cover, after which alternating current (0.1 V /cm) was used to immobilize the attracted animals. Population estimation Introduction This section and the next concern estimating population size and population changes from elec- trofishing data. In this section we review some widely used - and useful - methods of assessing the number of fish in a closed site of a stream or the litoral zone of a lake, and in the next this theme is continued with the next question - how to select these sites and how to make more general statements about stocks. Unfortunately the methods of population esti- mation are not easily accessible for people not trained in statistics. We have therefore tried to make the presentation as clear as possible. The calculations require only a pocket calculator with preprogrammed functions for mean and standard deviation, and th examples provided are intended to faciliate the use of the methods. Before these are presented, however, it might be useful to recall some basic statistical concepts. Statistical and systematic errors There are seldom opportunities to obtain exact measurements of the size or density of fish popu- lations. Rather, the true population size y is esti- mated as y, more or less close to the true but generally unknown y. As an estimate with unknown error is quite useless, several ways of expressing and estimating these errors have been developed. The types of error that may arise can be illustrated by firing a rifle at a target (Fig. 7). If the shot group is tight but its center at a distance from the bullseye, the statistical error or sampling error is small, but the systematic error large and represented by the dis- tance between the center of the shot group and the bullseye. This distance is the bias. If the sampling error of an estimate is small, the precision is good, and if the bias is small, the accuracy is good. A biased method of estimation will, on the average, yield either over- or underestimation (positive or negative bias). There are usually no easy ways to assess the bias of estimates of natural populations. Occasionally it is possible to apply a specific method to populations of known size, e.g. marked members, and thus get an idea of the bias. Further, if two methods are applied to the same population of unknown size, at least one of them is biased if the estimates, on the average, differ. Finally, a critical look at the assumptions on which the method is based will often reveal at least the direction of the bias. The sampling error has the effect that the esti- mate y would fluctuate around a mean E(y) if, hypothetically, the estimation were repeated many times under identical conditions. This fluctuation can be measured as the sampling variance V(y) of y, which is the average value of the squared deviations E (y) - y. The square root of V(y) is called the Standard Error of y, or SE(y). This can be viewed as a direct measure of this (hypo- thetical) fluctuation (Fig. 7). Another useful measure of the sampling error is the coefficient of variation C = SE(y )/y, indicating the relative sampling error. In addition it may sometimes be possible to estimate the sampling error (or its effects) as a I' i r \ I ) r I r Ii \: I :: ( r