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Integrating Towed Underwater Video w...
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Ilich, Alexander Ross.
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Integrating Towed Underwater Video with Multibeam Acoustics for Mapping Benthic Habitat and Assessing Reef Fish Communities on the West Florida Shelf.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Integrating Towed Underwater Video with Multibeam Acoustics for Mapping Benthic Habitat and Assessing Reef Fish Communities on the West Florida Shelf./
Author:
Ilich, Alexander Ross.
Published:
Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:
139 p.
Notes:
Source: Masters Abstracts International, Volume: 80-07.
Contained By:
Masters Abstracts International80-07.
Subject:
Ecology. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10977899
ISBN:
9780438779600
Integrating Towed Underwater Video with Multibeam Acoustics for Mapping Benthic Habitat and Assessing Reef Fish Communities on the West Florida Shelf.
Ilich, Alexander Ross.
Integrating Towed Underwater Video with Multibeam Acoustics for Mapping Benthic Habitat and Assessing Reef Fish Communities on the West Florida Shelf.
- Ann Arbor : ProQuest Dissertations & Theses, 2018 - 139 p.
Source: Masters Abstracts International, Volume: 80-07.
Thesis (M.S.)--University of South Florida, 2018.
This item must not be sold to any third party vendors.
Using a towed underwater video camera system, benthic habitats were classified along transects in a popular offshore fishing area on the West Florida Shelf (WFS) known as "The Elbow." Additionally, high resolution multibeam bathymetry and co-registered backscatter data were collected for the entire study area. Using these data, full coverage geologic and biotic habitat maps were developed using both unsupervised and supervised statistical classification methodologies. The unsupervised methodology used was k-means clustering, and the supervised methodology used a random forest algorithm. The two methods produced broadly similar results; however, the supervised methodology outperformed the unsupervised methodology. The results of the supervised classification demonstrated "substantial agreement" (κ > 0.6) between observations and predictions for both geologic and biotic habitat, while the results of the unsupervised classification demonstrated "moderate agreement" (κ > 0.4) between observations and predictions for both geologic and biotic habitat. Comparisons were made with the previously existing map for this area created by Florida Fish and Wildlife Conservation Commission's Fish and Wildlife Research Institute (FWC-FWRI). Some features are distinguishable in both maps, but the FWC-FWRI map shows a greater extent of low relief hard bottom features than was predicted in our habitat maps. The areas predicted as low relief hard-bottom by FWC-FWRI often coincide with areas of higher uncertainty in the supervised map of geologic habitat from this study, but even when compared with ground-truth points from the towed video rather than predictions, the low relief hard bottom in FWC-FWRI's map still corresponds to what was identified as sand in the video 73% of the time. The higher uncertainty might be a result of the presence of mixed habitats, differing morphology of hard-bottom, or the presence of sand intermixed with gravel or debris. More ground-truth samples should be taken in these areas to increase the confidence of these classifications and resolve discrepancies between the two maps. Data from the towed video system were also used to assess differences in fish communities among habitat types and to calculate habitat-specific densities for each taxa. Fish communities were found to significantly differ between soft and hard bottom habitats as well as among the hard-bottom habitats with different vertical relief (flat hard-bottom vs more steeply sloping areas). Additionally, significant differences were found between the fish communities in habitats with attached fauna such as sponges and gorgonians, and areas without attached fauna; however, attached fauna require rock to attach to and the rock habitats rarely lacked attached fauna, so this difference may just reflect the difference between fish communities in sand and rock habitats without the consideration of vertical relief. Moreover, the species driving the differences in the fish communities were identified. Fish were more likely to be present and assemblages were more species rich in more complex habitats (rockier, higher relief, presence of attached fauna). Habitat specific densities were calculated for each species, and general trends are discussed. Lastly the habitat-specific densities were extrapolated to the total area of habitat type (sand vs rock) as predicted by the supervised geologic habitat map. There is predicted to be approximately 111,000 fish (95% CI [67015, 169405]) within the study area based on this method, with ~47,000 (~43%) predicted to be within the sand habitat and ~64,000 (~57%) in the rock habitat. This demonstrates the potential of offshore rocky reefs as "critical habitats" for demersal fish in the offshore environment as rock accounts for just 4% of the study area but is expected to contain over half of the total abundance. The value of sand habitats is also shown, as due to their large area they are able to contribute substantially to the total number of fish despite sustaining comparatively low densities.
ISBN: 9780438779600Subjects--Topical Terms:
516476
Ecology.
Integrating Towed Underwater Video with Multibeam Acoustics for Mapping Benthic Habitat and Assessing Reef Fish Communities on the West Florida Shelf.
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Using a towed underwater video camera system, benthic habitats were classified along transects in a popular offshore fishing area on the West Florida Shelf (WFS) known as "The Elbow." Additionally, high resolution multibeam bathymetry and co-registered backscatter data were collected for the entire study area. Using these data, full coverage geologic and biotic habitat maps were developed using both unsupervised and supervised statistical classification methodologies. The unsupervised methodology used was k-means clustering, and the supervised methodology used a random forest algorithm. The two methods produced broadly similar results; however, the supervised methodology outperformed the unsupervised methodology. The results of the supervised classification demonstrated "substantial agreement" (κ > 0.6) between observations and predictions for both geologic and biotic habitat, while the results of the unsupervised classification demonstrated "moderate agreement" (κ > 0.4) between observations and predictions for both geologic and biotic habitat. Comparisons were made with the previously existing map for this area created by Florida Fish and Wildlife Conservation Commission's Fish and Wildlife Research Institute (FWC-FWRI). Some features are distinguishable in both maps, but the FWC-FWRI map shows a greater extent of low relief hard bottom features than was predicted in our habitat maps. The areas predicted as low relief hard-bottom by FWC-FWRI often coincide with areas of higher uncertainty in the supervised map of geologic habitat from this study, but even when compared with ground-truth points from the towed video rather than predictions, the low relief hard bottom in FWC-FWRI's map still corresponds to what was identified as sand in the video 73% of the time. The higher uncertainty might be a result of the presence of mixed habitats, differing morphology of hard-bottom, or the presence of sand intermixed with gravel or debris. More ground-truth samples should be taken in these areas to increase the confidence of these classifications and resolve discrepancies between the two maps. Data from the towed video system were also used to assess differences in fish communities among habitat types and to calculate habitat-specific densities for each taxa. Fish communities were found to significantly differ between soft and hard bottom habitats as well as among the hard-bottom habitats with different vertical relief (flat hard-bottom vs more steeply sloping areas). Additionally, significant differences were found between the fish communities in habitats with attached fauna such as sponges and gorgonians, and areas without attached fauna; however, attached fauna require rock to attach to and the rock habitats rarely lacked attached fauna, so this difference may just reflect the difference between fish communities in sand and rock habitats without the consideration of vertical relief. Moreover, the species driving the differences in the fish communities were identified. Fish were more likely to be present and assemblages were more species rich in more complex habitats (rockier, higher relief, presence of attached fauna). Habitat specific densities were calculated for each species, and general trends are discussed. Lastly the habitat-specific densities were extrapolated to the total area of habitat type (sand vs rock) as predicted by the supervised geologic habitat map. There is predicted to be approximately 111,000 fish (95% CI [67015, 169405]) within the study area based on this method, with ~47,000 (~43%) predicted to be within the sand habitat and ~64,000 (~57%) in the rock habitat. This demonstrates the potential of offshore rocky reefs as "critical habitats" for demersal fish in the offshore environment as rock accounts for just 4% of the study area but is expected to contain over half of the total abundance. The value of sand habitats is also shown, as due to their large area they are able to contribute substantially to the total number of fish despite sustaining comparatively low densities.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10977899
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