Quantifying relationships between abundances of cold-water coral Lophelia pertusa and terrain features: A case study on the Norwegian margin

Tong, Ruiju; Purser, Autun; Guinan, Janine; Unnithan, Vikram; Yu, Jinsongdi; Zhang, Chengcheng

doi:10.1016/j.csr.2016.01.012

Cited by 19 publications

(10 citation statements)

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“…В частности, этот подход применялся для выявления и классификации ледников, покрытых плотной поверхностной мореной, которые на снимках сливаются с прилегающими долинами [Alifu et al, 2016[Alifu et al, , 2020, а также для выявления ледяных утесов водорослевых рифов [Marchese et al, 2020]. Использование моделей локальных величин и индексов шероховатости позволяет прогнозировать распределение колоний холодноводных кораллов [Tong et al, 2016;Bargain et al, 2017].…”

Section: Discussionunclassified

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2021

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Сборник включает материалы, представленные на Международную конференцию «ИнтерКарто. ИнтерГИС 27». В статьях рассматриваются теоретические и методические аспекты геоинформационного и картографического обеспечения экологических, экономических и социальных вопросов устойчивого развития, геоинформатики, картографии, создания атласов, дистанционного зондирования Земли. Также рассматриваются аспекты картографического и геоинформационного обеспечения решения вопросов общественного здоровья, сельского хозяйства и землепользования, туризма, природного и культурного наследия, исторической географии и географического образования. Сборник выпускается 1 раз в год, начиная с 1994 г.

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Section: Discussionunclassified

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2021

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“…Noise present in the primary bathymetry and backscatter data layers can also be propagated, and even amplified in derivative layers [ 75 ], which can also affect model performance [ 50 ]. A decrease in spatial resolution can reduce data noise in derivative layers [ 46 , 67 ]. By averaging derivative data layers over an increasing area, noise can be smoothed out and made less distinct (see [ 32 ] for a comprehensive analysis of the effects of data coarsening on bathymetric derivatives).…”

Section: Discussionmentioning

confidence: 99%

“…Bottom currents transport sediments and control rates of erosion and deposition, making them one of the strongest drivers of sediment distribution [ 32 , 46 , 76 ]. Morphology influences the speed and orientation of currents, and also describes the exposure of seabed to them.…”

Section: Discussionmentioning

confidence: 99%

“…In addition to the attributes identified by Lecours et al [ 42 ], we derived a set of variables that may apply specifically to the distribution of sediment grain size. Seabed curvature (degrees per metre) influences current regimes and can be used to identify landform boundaries [ 44 ], while measures of relative seabed position such as benthic position index (BPI; metres) identify topographic highs and lows that can affect bottom currents and sediment transport [ 45 , 46 ]. Rugosity (the ratio of surface area to planar area) and the vector ruggedness index (the variability in surface orientation) are both unitless measures of terrain variability, which can describe seabed topography and substrate at appropriate scales (e.g.…”

Section: Methodsmentioning

confidence: 99%

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A multiscale approach to mapping seabed sediments

2018

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Benthic habitat maps, including maps of seabed sediments, have become critical spatial-decision support tools for marine ecological management and conservation. Despite the increasing recognition that environmental variables should be considered at multiple spatial scales, variables used in habitat mapping are often implemented at a single scale. The objective of this study was to evaluate the potential for using environmental variables at multiple scales for modelling and mapping seabed sediments. Sixteen environmental variables were derived from multibeam echosounder data collected near Qikiqtarjuaq, Nunavut, Canada at eight spatial scales ranging from 5 to 275 m, and were tested as predictor variables for modelling seabed sediment distributions. Using grain size data obtained from grab samples, we tested which scales of each predictor variable contributed most to sediment models. Results showed that the default scale was often not the best. Out of 129 potential scale-dependent variables, 11 were selected to model the additive log-ratio of mud and sand at five different scales, and 15 were selected to model the additive log-ratio of gravel and sand, also at five different scales. Boosted Regression Tree models that explained between 46.4 and 56.3% of statistical deviance produced multiscale predictions of mud, sand, and gravel that were correlated with cross-validated test data (Spearman’s ρmud = 0.77, ρsand = 0.71, ρgravel = 0.58). Predictions of individual size fractions were classified to produce a map of seabed sediments that is useful for marine spatial planning. Based on the scale-dependence of variables in this study, we concluded that spatial scale consideration is at least as important as variable selection in seabed mapping.

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“…At the more local scale, however, some terrain attributes, such as morphological features (topographic highs) and roughness, appear to be key contributors to CWC distribution (Dolan et al, 2008;Giusti et al, 2014;Rengstorf et al, 2014;Tong et al, 2016), where suitable environmental parameters for coral growth are present (in terms of temperature, salinity, dissolved oxygen, pH-values, and food availability). The interplay between local hydrodynamics and elevated features indeed promotes moderate to strong hydrodynamics and turbulent mixing, coupled with reduced terrigenous input and constant delivery of organic material, which in turn maintain CWC growth (White et al, 2005;Mienis et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Santa Maria di Leuca Province (Mediterranean Sea): Identification of Suitable Mounds for Cold-Water Coral Settlement Using Geomorphometric Proxies and Maxent Methods

et al. 2017

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The Santa Maria di Leuca (SML) cold-water coral province (northern Ionian Sea) has the largest occurrence of a living white coral community currently known in the Mediterranean Sea. Madrepora oculata and Lophelia pertusa, identified as marking sensitive habitats of relevance by the General Fisheries Commission for the Mediterranean, have been observed heterogeneously distributed on the summits of several mounds. This particularly patchy and uneven distribution in addition to their importance for regional biodiversity highlights the need to better understand their environmental preferences and predict their distribution. Bathymetric data (40 m resolution) was used to derive seafloor characteristics. A fine scale index quantifying the landscape elevation (Bathymetric Position Index at 120 m resolution) was used to select all the elevated features considered as candidate morphologies for potential coral mounds. Statistics on 22 known coral topped mounds were computed. Two statistical methods were then used to identify other potential coral mounds based on predictive variables. The first method, the Geomorphometric proxies method, consists in computing basic statistics of terrain variables, using them for a step-by-step classification in a quantitative approach to select a subset of candidate morphologies. The second method consists in using a predictive Habitat Suitability Model (Maxent model). The Geomorphometric proxies method identified 736 potential coral mounds while the Maxent method predicted 1,252 potential coral mounds. A subset of 517 potential coral mounds was common to both methods. The analysis of the contribution of each variable with the Maxent method showed that the variable "Vector Ruggedness Measure" at a resolution of 5 pixels (200 m) contributed to 53% of the final Maxent model, followed by the "Terrain Texture" index (31%) at a resolution of 11 pixels (440 m). The common potential coral mounds are mainly located in an area characterized by a mass transport deposit, also called the mounds Bargain et al. SML: Suitable Mounds for CWC area because of the roughness of the seafloor, in accordance with the high proportional contribution of the noticeable first roughness index to the Maxent model. The results highlight the importance of the global conservation of the entire Province, with white coral probably widespread over the entire 600 km 2 SML area.

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Quantifying relationships between abundances of cold-water coral Lophelia pertusa and terrain features: A case study on the Norwegian margin

Cited by 19 publications

References 54 publications

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A multiscale approach to mapping seabed sediments

Santa Maria di Leuca Province (Mediterranean Sea): Identification of Suitable Mounds for Cold-Water Coral Settlement Using Geomorphometric Proxies and Maxent Methods

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