Assessment of trawlable and untrawlable seafloor using multibeam-derived metrics

Pirtle, Jodi L.; Weber, Thomas C.; Wilson, Christopher D.; Rooper, Christopher N.

doi:10.1016/j.mio.2015.06.001

Cited by 22 publications

(44 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Approximately 18% of the GOA habitats sampled during the bottom trawl survey have been determined to be untrawlable typically due to rocky and rugose seafloors. This finding is similar to those by Pirtle, Weber, Wilson, and Rooper (2015) and Baker, Palsson, Zimmermann, and Rooper (2018, in review) who used different approaches to characterize the rugosity of GOA seafloor habitats. The untrawlable habitat bias of the bottom trawl survey has been discussed by Cordue (2007) in terms of stock abundance estimation, and a number of species such as several rockfishes are denser than in rocky habitats and in surrounding smooth seafloor habitats (Jones et al, 2012;Williams, Rooper, & Towler, 2010).…”

Section: Goa Bottom Trawl Surveysupporting

confidence: 90%

“…Habitat complexity within the GOA may afford opportunities for species to access a wide range of depths and temperatures without large spatial movements. That same habitat complexity constrains the availability of habitats to bottom trawl surveys (Rooper & Martin, ; Pirtle et al., , and Baker et al., , in review). While we recognize that it is possible that the six species we examined may differentially shift to untrawlable or pelagic habitats, the effect of these factors has not been examined by size groups and is therefore beyond the scope of this study.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

How “The Blob” affected groundfish distributions in the Gulf of Alaska

Yang

Cokelet

Stabeno

et al. 2019

Fisheries Oceanography

View full text Add to dashboard Cite

We investigated the distributional shifts of groundfish in response to anomalous ocean conditions, particularly the recent anomalously warm period (2014–2016; “The Blob”), based on data from ten Gulf of Alaska bottom trawl surveys conducted by the Alaska Fisheries Science Center during 1996–2015. Six groundfish species were considered: Pacific cod (Gadus macrocephalus), arrowtooth flounder (Atheresthes stomias), walleye pollock (Gadus chalcogrammus), Pacific ocean perch (Sebastes alutus), northern rock sole (Lepidopsetta polyxystra), and southern rock sole (Lepidopsetta bilineata). Ontogenetic differences were examined by dividing data for each fish species into size classes. Our study demonstrated that after accounting for size‐specific depth preferences, the spatial responses of groundfish to anomalous ocean conditions differed by species and foraging guild in the central Gulf of Alaska. Pacific cod and arrowtooth flounder showed similar responses to ocean warming, but different responses to cooling. In general, Pacific cod moved to deeper depths in warmer years and moved to shallower depths in colder years. Arrowtooth flounder also moved deeper in warmer years. However, in colder years, large arrowtooth flounder (>40 cm) shifted toward shallower depths while smaller‐sized fish shifted toward deeper depths. In warmer years, large pollock (>30 cm) moved to deeper waters while smaller pollock (10–20 cm) moved to shallower waters. Pacific ocean perch exhibited an opposite response to thermal changes in habitat compared with Pacific cod and arrowtooth flounder. They moved deeper in colder years, but there was no clear change in depth as a function of size in response to warmer habitat.

show abstract

Section: Goa Bottom Trawl Surveysupporting

confidence: 90%

Section: Methodsmentioning

confidence: 99%

How “The Blob” affected groundfish distributions in the Gulf of Alaska

Yang

Cokelet

Stabeno

et al. 2019

Fisheries Oceanography

View full text Add to dashboard Cite

show abstract

“…The more general term "multi-scale" is used in this paper to refer to both types of analysis as well as geomorphometric analysis using data of different resolutions. (Lundblad et al, 2006;Lanier et al, 2007;Micallef et al, 2012a;Dolan and Lucieer, 2014) Aspect (Galparsoro et al, 2009), northness/northerness and eastness/easterness (Monk et al, 2011) Mean curvature (Dolan et al, 2008); profile curvature (Guinan et al, 2009); plan/planimetric curvature (Ross et al, 2015); Bathymetric Position Index (BPI) (Monk et al, 2010;Pirtle et al, 2015) Rugosity (Dunn and Halpin, 2009); vector ruggedness measure (VRM) (Tempera et al, 2012); relative relief (Elvenes, 2013); fractal dimension (Wilson et al, 2007) Commonly used terrain attribute and software (algorithm reference)…”

Section: General Geomorphometry (Terrain Attributes)mentioning

confidence: 99%

A review of marine geomorphometry, the quantitative study of the seafloor

Lecours

Dolan

Micallef

et al. 2016

Hydrol. Earth Syst. Sci.

179

120

View full text Add to dashboard Cite

Abstract. Geomorphometry, the science of quantitative terrain characterization, has traditionally focused on the investigation of terrestrial landscapes. However, the dramatic increase in the availability of digital bathymetric data and the increasing ease by which geomorphometry can be investigated using geographic information systems (GISs) and spatial analysis software has prompted interest in employing geomorphometric techniques to investigate the marine environment. Over the last decade or so, a multitude of geomorphometric techniques (e.g. terrain attributes, feature extraction, automated classification) have been applied to characterize seabed terrain from the coastal zone to the deep sea. Geomorphometric techniques are, however, not as varied, nor as extensively applied, in marine as they are in terrestrial environments. This is at least partly due to difficulties associated with capturing, classifying, and validating terrain characteristics underwater. There is, nevertheless, much common ground between terrestrial and marine geomorphometry applications and it is important that, in developing marine geomorphometry, we learn from experiences in terrestrial studies. However, not all terrestrial solutions can be adopted by marine geomorphometric studies since the dynamic, fourdimensional (4-D) nature of the marine environment causes its own issues throughout the geomorphometry workflow. For instance, issues with underwater positioning, variations in sound velocity in the water column affecting acousticbased mapping, and our inability to directly observe and measure depth and morphological features on the seafloor are all issues specific to the application of geomorphometry in the marine environment. Such issues fuel the need for a dedicated scientific effort in marine geomorphometry.This review aims to highlight the relatively recent growth of marine geomorphometry as a distinct discipline, and offers the first comprehensive overview of marine geomorphometry to date. We address all the five main steps of geomorphometry, from data collection to the application of terrain attributes and features. We focus on how these steps are relevant to marine geomorphometry and also highlight differences and similarities from terrestrial geomorphometry. We conclude with recommendations and reflections on the future of marine geomorphometry. To ensure that geomorphometry is used and developed to its full potential, there is a need to increase awareness of (1) marine geomorphometry amongst scientists already engaged in terrestrial geomorphometry, and of (2) geomorphometry as a science amongst marine scientists with a wide range of backgrounds and experiences.

show abstract

“…Geosciences 2018, 8,14 3 of 16 In order to capture bathymorphologic elements at the desired scales, the algorithm supports the definition of a search annulus contained between an internal radius ( ) acting like a low-pass filter, and an external radius ( ) that limits the extent of the spatial analysis. Although the node neighborhood may be potentially evaluated in any range of directions, exploratory tests have shown that limiting the analysis to eight directions ( ) (the four cardinal directions and the four main inter-cardinal directions) provides a good working tradeoff between computation efficiency and stability of the retrieved information (Figure 1) Figure 1.…”

Section: Area Kernels Based On Landform Classificationmentioning

confidence: 99%

“…However, there are few studies that have offered general methods for using a machine-focused approach to combine and use the information found in co-located bathymetric digital elevation models (DEMs) and acoustic mosaics [16][17][18][19][20][21][22]. Modern multibeam sonars and processing software now typically produce geo-located bathymetry and backscatter mosaic products, thus offering the opportunity to treat both data sets together [21,23].…”

Section: Introductionmentioning

confidence: 99%

A Bathymetry- and Reflectivity-Based Approach for Seafloor Segmentation

2018

View full text Add to dashboard Cite

A robust and flexible technique to segment seafloor acoustic mapping data by analyzing co-located bathymetric digital elevation models and acoustic backscatter mosaics is presented. The algorithm first uses principles of topographic openness, pattern recognition, and texture classification to identify geomorphic elements of the seafloor or "area kernels", and then derives the final seafloor segmentation by merging or splitting the kernels based on principles of similarity and multi-modality. The output is a collection of homogeneous, non-overlapping seafloor segments of consistent morphology and acoustic backscatter texture. Each labeled segment is enriched by a list of derived, physically-meaningful attributes that can be used for subsequent task-specific analysis.

show abstract

Assessment of trawlable and untrawlable seafloor using multibeam-derived metrics

Cited by 22 publications

References 25 publications

How “The Blob” affected groundfish distributions in the Gulf of Alaska

How “The Blob” affected groundfish distributions in the Gulf of Alaska

A review of marine geomorphometry, the quantitative study of the seafloor

A Bathymetry- and Reflectivity-Based Approach for Seafloor Segmentation

Contact Info

Product

Resources

About