A new arc–chord ratio (ACR) rugosity index for quantifying three-dimensional landscape structural complexity

Preez, Cherisse Du

doi:10.1007/s10980-014-0118-8

Cited by 51 publications

(46 citation statements)

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“…Despite the 12 year difference between the multibeam and the imagery expeditions, there was no evidence that a major landscape changing event had occurred, and it was determined the multibeam data still reflected the present bathymetry on Cobb Seamount in 2012. Four environmental datasets were derived from multibeam bathymetry of Cobb Seamount (20 m cell size raster): depth (in meters), slope (in degrees), and small- and large-scale metrics of roughness (complexity), specifically arc-chord ratio (ACR) rugosity at 4000 m 2 and 4 km 2 [31]. These two scales represent the smallest and largest areas that could be geoprocessed for multi-cell rugosity, given the resolution of the bathymetric data and the spatial distribution of the images.…”

Section: Methodsmentioning

confidence: 99%

“…These two scales represent the smallest and largest areas that could be geoprocessed for multi-cell rugosity, given the resolution of the bathymetric data and the spatial distribution of the images. ACR rugosity was specifically used (over other complexity metrics) because it is decoupled from slope [31]. All spatial analyses and value extractions (to point image samples) were executed in ESRIArcMap 10.2.0.3348 using the Benthic Terrain Modeler [32] and the ACR tool [31].…”

Section: Methodsmentioning

confidence: 99%

“…ACR rugosity was specifically used (over other complexity metrics) because it is decoupled from slope [31]. All spatial analyses and value extractions (to point image samples) were executed in ESRIArcMap 10.2.0.3348 using the Benthic Terrain Modeler [32] and the ACR tool [31]. Other variables originally derived from multibeam data (e.g., curvature and BPI indices) were found to be highly correlated with depth and removed from the analysis.…”

Section: Methodsmentioning

confidence: 99%

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The Structure and Distribution of Benthic Communities on a Shallow Seamount (Cobb Seamount, Northeast Pacific Ocean)

2016

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Partially owing to their isolation and remote distribution, research on seamounts is still in its infancy, with few comprehensive datasets and empirical evidence supporting or refuting prevailing ecological paradigms. As anthropogenic activity in the high seas increases, so does the need for better understanding of seamount ecosystems and factors that influence the distribution of sensitive benthic communities. This study used quantitative community analyses to detail the structure, diversity, and distribution of benthic mega-epifauna communities on Cobb Seamount, a shallow seamount in the Northeast Pacific Ocean. Underwater vehicles were used to visually survey the benthos and seafloor in ~1600 images (~5 m2 in size) between 34 and 1154 m depth. The analyses of 74 taxa from 11 phyla resulted in the identification of nine communities. Each community was typified by taxa considered to provide biological structure and/or be a primary producer. The majority of the community-defining taxa were either cold-water corals, sponges, or algae. Communities were generally distributed as bands encircling the seamount, and depth was consistently shown to be the strongest environmental proxy of the community-structuring processes. The remaining variability in community structure was partially explained by substrate type, rugosity, and slope. The study used environmental metrics, derived from ship-based multibeam bathymetry, to model the distribution of communities on the seamount. This model was successfully applied to map the distribution of communities on a 220 km2 region of Cobb Seamount. The results of the study support the paradigms that seamounts are diversity 'hotspots', that the majority of seamount communities are at risk to disturbance from bottom fishing, and that seamounts are refugia for biota, while refuting the idea that seamounts have high endemism.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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The Structure and Distribution of Benthic Communities on a Shallow Seamount (Cobb Seamount, Northeast Pacific Ocean)

2016

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“…The approach of using a plane-of-best-fit when calculating surface roughness estimates such as this is generally favoured over the use of the true, real-world horizontal plane. This is because using plane-of-best-fit de-couples slope and SR, ensuring that change in elevation does not influence surface roughness calculations [20,38]. This approach was completed for five different nominal sizes of virtual quadrats, 0.25 m 2 , 1 m 2 , 2.25 m 2 , 4 m 2 , and 9 m 2 , giving sample sizes (number of non-overlapping quadrat which could be fit on the surface) of 456, 114, 48, 27, and 12 respectively.…”

Section: Patch-scalementioning

confidence: 99%

Accuracy and Precision of Habitat Structural Complexity Metrics Derived from Underwater Photogrammetry

et al. 2015

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Abstract:In tropical reef ecosystems corals are the key habitat builders providing most ecosystem structure, which influences coral reef biodiversity and resilience. Remote sensing applications have progressed significantly and photogrammetry together with application of structure from motion software is emerging as a leading technique to create three-dimensional (3D) models of corals and reefs from which biophysical properties of structural complexity can be quantified. This enables the addressing of a range of important marine research questions, such as what the role of habitat complexity is in driving key ecological processes (i.e., foraging). Yet, it is essential to assess the accuracy and precision of photogrammetric measurements to support their application in mapping, monitoring and quantifying coral reef form and structure. This study evaluated the precision (by repeated modeling) and accuracy (by comparison with laser reference models) of geometry and structural complexity metrics derived from photogrammetric 3D models of marine benthic habitat at two ecologically relevant spatial extents; individual coral colonies of a range of common morphologies and patches of reef area of 100s of square metres. Surface rugosity measurements were generally precise across all morphologies and spatial extents with average differences in the geometry of replicate models of 1-6 mm for coral colonies and 25 mm for the reef area. Precision decreased with complexity of the coral morphology, with metrics for small massive corals being the most precise (1% coefficient of variation (CV) in surface rugosity) and metrics for bottlebrush corals being the least precise (10% CV in surface rugosity). There was no indication however that precision was related to complexity for the patch-scale modelling. The 3D geometry of coral models differed by only 1-3 mm from laser reference models. However, high spatial variation in these differences around the model led to a consistent underestimation of surface rugosity values for all morphs of between 8% and 37%. This study highlights the utility of several off-the-shelf photogrammetry tools for the measurement of structural complexity across a range of scales relevant to ecologist and managers. It also provides important information on the accuracy and precision of these systems which should allow for their targeted use by non-experts in computer vision within these contexts.

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“…There is usually a variety of different factors or gradients generating substratum (Sebens 1991, Gratwicke & Speight 2005Du Preez 2015). For example, substratum height, height variation and interstitial space will affect the rugosity, while diversity of substratum composition, areal extent and spatial distribution will affect the heterogeneity (Gratwicke & Speight 2005.…”

Section: Concepts and Definitionsmentioning

confidence: 99%

Disentangling Habitat Concepts for Demersal Marine Fish Management

Elliott¹,

Milligan²,

Heath³

et al. 2016

Oceanography and Marine Biology - An Annual Review

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Fishing and other anthropogenic impacts have led to declines in many fish stocks and modification of the seabed. As a result, efforts to restore marine ecosystems have become increasingly focused on spatially explicit management methods to protect fish and the habitats they require for survival. This has led to a proliferation of investigations trying anthropogenic impacts and identify fish resource requirements in order to meet conservation and management needs.A wide range of habitat-related concepts, with different uses and understandings has arisen as a consequence. Inconsistencies in terminology can cause confusion between studies, making it difficult to investigate and understand the ecology of fish and the factors that affect their survival. Ultimately, the inability to discern the relationships between fish and their environment clearly can hinder conservation and management measures for fish populations.This review identifies and addresses the present ambiguity surrounding -related concepts currently used in spatial management of demersal marine fish populations. The role of spatial and temporal scales is considered, in addition to examples of how to assess fish habitat for conservation and management purposes.

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A new arc–chord ratio (ACR) rugosity index for quantifying three-dimensional landscape structural complexity

Cited by 51 publications

References 51 publications

The Structure and Distribution of Benthic Communities on a Shallow Seamount (Cobb Seamount, Northeast Pacific Ocean)

The Structure and Distribution of Benthic Communities on a Shallow Seamount (Cobb Seamount, Northeast Pacific Ocean)

Accuracy and Precision of Habitat Structural Complexity Metrics Derived from Underwater Photogrammetry

Disentangling Habitat Concepts for Demersal Marine Fish Management

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