Use of acoustic classification of sidescan sonar data for mapping benthic habitat in the Northern Channel Islands, California

Cochrane, Guy R.; Lafferty, Kevin D.

doi:10.1016/s0278-4343(01)00089-9

“…Unfortunately, backscatter data could not be included in the GLMs used here because there were too many unique values (n = 256) in the raw, unclassified, side scan mosaics, causing the models to crash due to limitations in computer processing power. One possible solution would be to use classified backscatter intensity as described by Cochrane & Lafferty (2002) and Intelmann & Cochrane (2006), thereby reducing the number of substrate texture classes to a more manageable range.…”

Section: Evaluation Of Modeling Methodsmentioning

confidence: 99%

“…Unfortunately, backscatter data could not be included in the GLMs used here because there were too many unique values (n = 256) in the raw, unclassified, side scan mosaics, causing the models to crash due to limitations in computer processing power. One possible solution would be to use classified backscatter intensity as described by Cochrane & Lafferty (2002) and Intelmann & Cochrane (2006), thereby reducing the number of substrate texture classes to a more manageable range.Another potential flaw with the Sebastes elongatus model could be the small number of observations recorded for this species. Although not applied here, different methods, such as ordination, may be more suitable in situations where very few presence points exist.…”

mentioning

confidence: 99%

Multivariate bathymetry-derived generalized linear model accurately predicts rockfish distribution on Cordell Bank, California, USA

Young

¹

,

Iampietro²,

Kvitek³

et al. 2010

Mar. Ecol. Prog. Ser.

View full text Add to dashboard Cite

Accurate efficient estimation of actual and potential species distribution is a critical requirement for effective ecosystem-based management and marine protected area design. In this study we tested the applicability of a terrestrial landscape modeling technique in a marine environment for predicting the distribution of ecologically and economically important groundfish, using 3 species of rockfish at Cordell Bank National Marine Sanctuary (CBNMS) as a model system. Autoclassification of multibeam bathymetry along with georeferenced submersible video transect data of the seafloor and demersal fishes were used to model the abundance and distribution of rockfish. Generalized linear models (GLMs) were created using habitat classification analyses of high-resolution (3 m) digital elevation models combined with fish presence/absence observations. Model accuracy was assessed using a reserved subset of the observation data. The resulting probability of occurrence models generated at 3 m resolution for the entire 120 km 2 study area proved reliable in predicting the distribution of all the species. The accuracies of the models for Sebastes rosaceus, S. flavidus and S. elongatus were 96, 92 and 92%, respectively. The probability of occurrence of S. flavidus and S. rosaceus was highest in the high relief rocky areas and lowest in the low relief, soft sediment areas. The model for S. elongatus had an opposite pattern, with the highest predicted probability of occurrence taking place in the low relief, soft sediment areas and a lower probability of occurrence in the rocky areas. These results indicate that site-specific and species-specific algorithmic habitat classification applied to high-resolution bathymetry data can be used to accurately extrapolate the results from in situ video surveys of demersal fishes across broad areas of habitat.KEY WORDS: Ecosystem-based management · Rockfish · Groundfish · GLMs · Marine protected area · Fishery management Resale or republication not permitted without written consent of the publisherMar Ecol Prog Ser 415: [247][248][249][250][251][252][253][254][255][256][257][258][259][260][261] 2010 Traditional methods of distributional estimates have typically relied upon broad extrapolation from narrowly constrained or sparse data sets, or very costly intense sampling efforts carried out over broad areas (Margules & Austin 1991, Li & Hilbert 2008. However, because the selection of habitats by organisms is nonrandom (Rhodes et al. 2005), habitat conditions important to the occurrence of a species can be used to predict their distribution and aid in the development of management plans (Fernandez et al. 2003).In terrestrial environments, spatially explicit habitat suitability modeling has emerged as an efficient tool for generating accurate patterns and predictions of species abundance and distribution (Austin et al. 1994, Rotenberry et al. 2006, Kleinwachter & Rickfelder 2007, Valavanis et al. 2008. The integration of recent advancements in GIS software , Rotenberry et al. 2006)...

show abstract

“…The weaker agreements in Class II (2-mresolution grid, 51 percent accurate; 5-m-resolution grid, 49 percent accurate) and Class III (2-mresolution grid, 35 percent accurate; 5-m-resolution grid, 42 percent accurate) likely are due to (1) the distribution of small, localized rock outcrops, (2) the relatively narrow and intermittent nature of transition zones from sediment to rock, and (3) the size of the buffer. The bedrock outcrops in this area are composed of differentially eroded sedimentary rocks (Cochrane and Lafferty, 2002). Erosion of softer layers produces Class I and II sediments, resulting in patchy areas of rugose rock and boulder habitat (Class III) on the seafloor.…”

Section: By Mercedes D Erdey and Guy R Cochranementioning

confidence: 99%

California State Waters Map Series — Monterey Canyon and vicinity, California

Dartnell¹,

Maier²,

Erdey³

et al. 2016

Self Cite

View full text Add to dashboard Cite

show abstract

“…Coarser sediments accumulated in seafloor depressions (Class IV) often form megaripples, which might not be always recognizable on the video footage especially when visibility is limited. Bedrock outcrops in this area are composed of differentially eroded sedimentary rocks (Cochrane and Lafferty, 2002). Erosion of softer layers produces Class I and II sediments, resulting in patchy areas of rugose rock and boulder habitat (Class III) on the seafloor.…”

Section: By Peter Dartnellmentioning

confidence: 99%