The effect of fish behaviour and spatial structures on acoustic and trawl surveys

Abstract

Time series of scientific survey estimates of fisheries resources are used to measure changes in stock size and composition. Standardization of sampling equipment and design is regarded crucial for reliable trawl and acoustic survey estimates, but in spite of established routines the reliability of the survey estimates are reduced due to variations in fish behavior and changes in their spatial distribution. The main objectives of this thesis are to investigate the effects of spatial and temporal variation in fish distribution and behavior on acoustic and bottom trawl estimates, and the study presents methods to identify and correct for these sources of errors. A large variety of data are examined ranging from acoustic recordings from the spawning grounds of blue whiting (Micromesistius poutassou) and Norwegian Spring Spawning herring (Clupea harengus) to bottom trawl survey data and commercial CPUE of Namibian hake (Merluccius capensis and M. paradoxus) and the results are presented in six scientific papers. We show that blue whiting is distributed deeper and covers a narrower depth range at daytime than at night during its spawning west of the British Isles. As a consequence the tilt angle distribution changes and reduces the average acoustic target strength of the measured fish. This explains why we observed higher acoustic densities of blue whiting at daytime than at night. The effect of the diel variation on the survey estimates varies between years and therefore reduces the reliability of the survey time series (Paper I). Not surprisingly we observed that the diel oscillation in the sample values is closely related to rise and set for the sun. However, time-dependent variation in the catch rates and echo density also occur within daylight and the density measures increase from dawn to noon and then subsequently decrease to dusk (Papers I and IV). For the catch rates of Namibian hakes we found that the maximum is reached when the sun is about 20 degrees above the horizon, but the amplitude of the diel oscillation decreases with depth and increases with density of hake. Highest amplitude values are found in shallow waters which are dominated by the M. capensis species (Paper IV). The effect of weather and environmental conditions on the diel variation is not investigated in our studies due to lack of adequate data, but a in situ experiments we carried out in Namibia indicates a between-year difference in the escapement of hake under the fishing line due to annual differences in the oxygen levels near the seabed (Paper III). This type of escapement is likely to change with time of the day as hake lifts from the bottom at night and may also explain some of the differences in the diel oscillation we found in the different areas of the Namibian waters. It is often stressed that the assessment surveys should be repeated at the same time each year, as many fish stocks move in more or less repeating geographical migration patterns. However, the substantial geographical dynamic we identified in the Namibian trawler fleet (Paper V) suggests substantial annual variation in the spatial distribution of the hakes and changes in survey estimates may therefore be a sampling artifact due to variable environmental conditions and location of fish. Fish populations are usually patchily distributed and show gradient structures and the individuals within a shoal or a limited area tend to have more similar characteristics than those of the entire population. An example of small scale patchiness is found in the herring trawl samples with a significant relationship between depth distribution and maturity state of herring where the spawners dominated the trawl catches taken close to the sea-bed (Paper II). In Paper VI, the precision of the abundance estimates by length group of Namibian hake is increased by including the information of spatial autocorrelation. Using geo-statistic, the geographical structure of the distribution can be model and thus enhance the quality of the survey estimates. The overall result shows that the catch rates and acoustic density of fish are influenced by the fish’s location and its response to the approaching trawl which vary with time of the day. The swimming performance and reaction pattern to catching device are also affected by the density of fish, species and length dependent behavior, bottom depth, level of dissolved oxygen and temperatures. All these parameters can be included in the generic term “survey condition”, and any change in the survey condition tend to influence the relationship between measured and true fish density. The survey errors investigated in this thesis are not included in standard estimation procedures, and obviously it is a difficult task to correct for errors caused by variation in the survey condition. We have applied statistical modeling to identify systematic spatial and diel variability in large survey and commercial fishing data-sets, which can be used to correct for these errors. However, diel variation and geo-statistical models depend on the correct estimation of several parameters, which negatively affect the precision of the survey estimates. Therefore, a better approach is to integrate several sampling methodologies so the effect of variable survey conditions can be directly measured. Many places on the globe are also on the doorstep to a complex ecosystem management approach which demands scientific surveillance of several species and trophic levels. A simultaneous monitoring of inter-specific interaction is a fundament of this types of surveys and requires advanced survey strategies where many sources of data collected with trawls, CTD probes, echo-sounders, transducers and sonars are integrated and together form the basis for the concurrent measurement of the environment, survey condition and fish densities. Furthermore, the allocation of survey effort are occasionally sub-optimize due to variation in the spatial structure of the target stock between surveys. An adaptive sampling strategy which utilizes for instance satellite tracking data of the commercial fishing fleet to map the stock distribution in advance of the surveys may improve the effort allocation and hence increase the reliability of the survey estimates.