Epipelagic fish distributions in relation to thermal fronts in a coastal upwelling system using high-resolution remote-sensing techniques

Reese, Douglas C.; O’Malley, Robert T.; Brodeur, Richard D.; Churnside, James H.

doi:10.1093/icesjms/fsr107

Cited by 35 publications

(20 citation statements)

References 40 publications

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“…69 In addition to biomass estimates for fisheries management, lidar can be used to investigate aspects of fish behavior. For example, lidar data were used with those from an infrared radiometer on the same aircraft to show that sardines were associated with thermal fronts in the NE Pacific Ocean, 70 validating an earlier prediction. 71 Lidar data were used with visual observations to show the evolution of a foraging event involving whales, seabirds, herring, and euphasiids in the SE Bering Sea.…”

Section: Fisheriesmentioning

confidence: 79%

Review of profiling oceanographic lidar

Churnside

2013

Opt. Eng

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149

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This paper provides a review of the development of profiling oceanographic lidars. These can provide quantitative profiles of the optical properties of the water column to depths of 20 to 30 m in productive coastal waters and to depths of 100 m for a blue lidar in the open ocean. The properties that can be measured include beam attenuation, diffuse attenuation, absorption, volume scattering at the scattering angle of 180 deg, and total backscattering. Lidar can be used to infer the relative vertical distributions of fish, plankton, bubbles, and other scattering particles. Using scattering as a tracer, lidar can provide information on the dynamics of the upper ocean, including mixed-layer depth, internal waves, and turbulence. Information in the polarization of the lidar return has been critical to the success of many of these investigations. Future progress in the field is likely through a better understanding of the variability of the lidar ratio and the application of high-spectral-resolution lidar to the ocean. Somewhat farther into the future, capabilities are likely to include lidar profiling of temperature in the ocean and an oceanographic lidar in space.

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Section: Fisheriesmentioning

confidence: 79%

Review of profiling oceanographic lidar

Churnside

2013

Opt. Eng

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149

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“…Porpoises often have well‐defined home ranges that last for several weeks or months, although they sometimes switch behavior and move to new areas (Nabe‐Nielsen et al unpubl.). Porpoises feed on a wide range of fish species (Börjesson et al 2003) and although the spatial distribution of their prey is largely unknown in the study area, it is presumably related to patchy environmental features such as reefs, eelgrass beds and upwelling zones (Schneider et al 2008, Laidig et al 2009, Reese et al 2011). This suggests that a foraging model based on movement between small food patches may be realistic for porpoises.…”

mentioning

confidence: 99%

How a simple adaptive foraging strategy can lead to emergent home ranges and increased food intake

Nabe‐Nielsen

Tougaard

Teilmann

et al. 2013

Oikos

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Animals often alternate between searching for food locally and moving over larger distances depending on the amount of food they find. This ability to switch between movement modes can have large implications on the fate of individuals and populations, and a mechanism that allows animals to find the optimal balance between alternative movement strategies is therefore selectively advantageous. Recent theory suggests that animals are capable of switching movement mode depending on heterogeneities in the landscape, and that different modes may predominate at different temporal scales. Here we develop a conceptual model that enables animals to use either an area‐concentrated food search behavior or undirected random movements. The model builds on the animals’ ability to remember the profitability and location of previously visited areas. In contrast to classical optimal foraging models, our model does not assume food to be distributed in large, well‐defined patches, and our focus is on animal movement rather than on how animals choose between foraging patches with known locations and value. After parameterizing the fine‐scale movements to resemble those of the harbor porpoise Phocoena phocoena we investigate whether the model is capable of producing emergent home ranges and use pattern‐oriented modeling to evaluate whether it can reproduce the large‐scale movement patterns observed for porpoises in nature. Finally we investigate whether the model enables animals to forage optimally. We found that the model was indeed able to produce either stable home ranges or movement patterns that resembled those of real porpoises. It enabled animals to maximize their food intake when fine‐tuning the memory parameters that controlled the relative contribution of area concentrated and random movements.

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“…This system has also been employed to study fish behaviour such fish schooling (Churnside ) and study the correlation between fish species and their environment (Reese et al . ) or species identification and population estimation (Carrera et al . ).…”

Section: Preharvestmentioning

confidence: 99%

“…A LiDAR transmits and receives electromagnetic radiation at high frequency and operates in the ultraviolet, visible and infrared region. This system has also been employed to study fish behaviour such fish schooling (Churnside 2003) and study the correlation between fish species and their environment (Reese et al 2011) or species identification and population estimation (Carrera et al 2006).…”

Section: Preharvestmentioning

confidence: 99%

Application of machine vision systems in aquaculture with emphasis on fish: state‐of‐the‐art and key issues

Saberioon

Gholizadeh

Císař

et al. 2016

Reviews in Aquaculture

185

109

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Demands of aquatic products are increasing dramatically during past decades. Also quality assurance has gradually received more attention by both producers and consumers. Thus, fish producers are exploring all possible approaches for improving the productivity and profitability. Monitoring of fish state and behaviour during cultivation may help to improve profitability for producers and also reduce the threat of severe loss because of disease and stress incidents. It is necessary to evaluate and measure quality of fish products in accurate, fast and objective way for meeting the different demands of the fish‐processing industry after harvesting. Traditional methods are usually time‐consuming, expensive, laborious and invasive. Using rapid, inexpensive and noninvasive methods is therefore important and desirable. Optical sensors and machine vision system provide the possibility of developing faster, cheaper and noninvasive methods for in situ and after harvesting monitoring of quality in aquaculture. This review describes the most recent technologies and the suitability of different optical sensors for the fish farming management and also assessment, measurement and prediction of fish products quality. Two major areas of optical sensors applications in aquaculture are discussed in this review: (i) preharvesting and during cultivation; and (ii) post‐harvesting. Finally, accuracy and uncertainty of optical sensors applications in aquaculture are discussed. This review showed that MVSs and optical sensors have found real‐world application based on tremendous possibility offered by digital camera development and increasing the speed of computer‐based processing; however, still new algorithms, methods and re‐engineered sensors need to be developed to meet real‐world requirements.

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Epipelagic fish distributions in relation to thermal fronts in a coastal upwelling system using high-resolution remote-sensing techniques

Cited by 35 publications

References 40 publications

Review of profiling oceanographic lidar

Review of profiling oceanographic lidar

How a simple adaptive foraging strategy can lead to emergent home ranges and increased food intake

Application of machine vision systems in aquaculture with emphasis on fish: state‐of‐the‐art and key issues

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