Pelagic fisheries Habitat selection and migration Schooling behaviour Avoidance Attraction and association Learning Effects of behaviour on fisheries and stock assessment by population dynamic models Effects of behaviour on stock assessment by acoustic surveys Other methods of stock assessment and fish behaviour.

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Dynamics of pelagic fish distribution and behaviour : effects on fisheries and stock assessment

Where possible, automation has been a common response of humankind to many activities that have to be repeated numerous times. The routine identification of specimens of previously described species has many of the characteristics of other activities that have been automated, and poses a major constraint on studies in many areas of both pure and applied biology. In this paper, we consider some of the reasons why automated species identification has not become widely employed, and whether it is a realistic option, addressing the notions that it is too difficult, too threatening, too different or too costly. Although recognizing that there are some very real technical obstacles yet to be overcome, we argue that progress in the development of automated species identification is extremely encouraging that such an approach has the potential to make a valuable contribution to reducing the burden of routine identifications. Vision and enterprise are perhaps more limiting at present than practical constraints on what might possibly be achieved.

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Automated species identification: why not?

Automated classification of bird and amphibian calls using machine learning: A comparison of methods

Noninvasive species identification remains a longterm goal of fishers, researchers, and resource managers who use sound to locate, map, and count aquatic organisms. Since the first biological applications of underwater acoustics, four approaches have been used singly or in combination to survey marine and freshwater environments: passive sonar; prior knowledge and direct sampling; echo statistics from high-frequency measures; and matching models to low-frequency measures. Echo amplitudes or targets measured using any sonar equipment are variable signals. Variability in reflected sound is influenced by physical factors associated with the transmission of sound through a compressible fluid, and by biological factors associated with the location, reflective properties, and behaviour of a target. The current trend in acoustic target identification is to increase the amount of information collected through increases in frequency bandwidth or in the number of acoustic beams. Exclusive use of acoustics to identify aquatic organisms reliably will require a set of statistical metrics that discriminate among a wide range of similar body types at any packing density, and incorporation of these algorithms in routine data processing.

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Acoustic approaches to remote species identification: a review

Marine aliens are non-native species that have been transported across major geographical barriers by human activities, involving vectors that move propagules along pathways. Species may also be newly observed in a geographical area due to range shifts, generally in association with climate change. Artificial structures are considered to be either man-made materials or natural materials shaped or displaced to serve a specific function for human activities. All types of artificial structures are currently increasing dramatically in coastal zones due to increasing human populations on coastlines. Most of the significant marine vectors and pathways involve mobile artificial structures and are reviewed here. These include shipping (ballast water and hull fouling) and aquaculture, including stock transfer and unintentional introductions, all of which can move species into new biogeographical provinces. Some types of structures frequently move long distances but have low fouling loads (e.g., commercial shipping), whereas others (e.g., barges and pontoons) can be hyperfouled due to long stationary periods such that when moved they transport mature fouling communities. We also examine the presence of alien marine species on static (immobile) artificial structures, which support different communities from those on natural hard substrata. We consider the role of these structures, such as coastal defences, artificial reefs, and offshore platforms, in the dispersal and abundance of alien species. Marinas include both mobile and immobile structures and are apparently particularly favourable habitats for many aliens. For example, in coastal North America approximately 90% of the alien species inhabiting hard substrata have been reported from docks and marinas. Detailed case studies of alien marine species (two seaweeds and four invertebrates) are provided, with an analysis of their origin, vectors of transport, habitat in the introduced range, and potential impact. Although there are exceptions, a large majority of marine alien species seem to be associated, at least for some of the time, with artificial structures. It is clear that artificial structures can pave the way and act as stepping stones or even corridors for some marine aliens, as do urban areas, roads and riparian environments in terrestrial ecosystems. The observed acceleration of spread rates for marine invasions over the course of the last two centuries may partly be a result of the increase of artificial structures in coastal environments coupled with greater activity of vectors.

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Changing coasts: marine aliens and artificial structures

The paper reports the results of species-recognition-rate measurements on caged aggregations of mackerel, horse mackerel, saithe, haddock, and two sizes of cod. Data on the acoustic backscattering coeYcients were collected in eight contiguous bandwidth intervals covering the frequency band between 27 and 54 kHz. The measurements were made during two to six periods of 24 h for each aggregation of fish. Replicate experiments were carried out for mackerel, horse mackerel, and two sizes of cod. The data were processed to give average frequency spectra. The number of independent observations used to establish the mean was varied to examine the species-recognition dependence on the number of independent observations. The mean spectra were analysed using two recognition methods: neural network and discriminant analysis. A neural network was trained on subsets of the data and recognition rates established for the diVerent numbers of samples used to calculate the mean spectra. Classical discriminant analysis was applied using the same data sets. The results of the two identification methods are presented and show that recognition rates of about 95% are possible using average spectra. The diVering recognition rates by species and fish sizes are discussed and the two identification methods compared. Implications for the future development of these methods are considered. ? 1996 International Council for the Exploration of the Sea

Species identification using wideband backscatter with neural network and discriminant analysis

F. G. O’Neill1*, S. M. Simmons2, D. R. Parsons2, J. L. Best3, P. J. Copland1, F. Armstrong1, M. Breen1, and K. Summerbell1 Marine Scotland Science, Aberdeen AB11 9DB, UK Department of Geography, Environment and Earth Science, University of Hull, Hull HU6 7RX, UK Departments Geology, Geography and Geographic Information Science, Mechanical Science and Engineering, and Ven Te Chow Hydrosystems Laboratory, University of Illinois, 1301 West Green Street, Urbana, IL 61801, USA

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F. Armstrong

Papers

Species identification using wideband backscatter with neural network and discriminant analysis

Monitoring the generation and evolution of the sediment plume behind towed fishing gears using a multibeam echosounder