Geomorphological Classification of the Benthic Structures on a Tropical Continental Shelf

Abstract

Geomorphological research offers a valuable first step to understand the complexity of seafloor patterns that are likely to support particular fauna, thereby providing value for future targeted studies on benthic communities and habitats. The objective of this study is to perform a geomorphological classification of a tropical continental shelf, located in the north of the State of Pernambuco, Brazil, using Benthic Terrain Modeler (BTM), as a first step to characterize benthic habitats. The classification of the seabed is based on the bathymetry, broad-scale and fine-scale BPI (Benthic Positioning Index), seafloor slope, and a decision table containing definitions and thresholds appropriate to the data input. The relationships between morphology and the deposition of surface sediments were also investigated. Results from the BTM analysis revealed eight types of benthic structures: Flat Plains, Depressions, Gentle Slopes, Steep Slopes, Flat Ridge Tops, Rock Outcrop Highs, Local Pinnacles in Depressions and Local Pinnacles on Broad Flats. The results from this study may therefore assist in selecting priority areas to investigate, supporting better marine spatial planning in the region, and, in the future, collaborating to determine biodiversity patterns in Brazilian waters.

The influence of seafloor terrain on fish and fisheries: A global synthesis

“…Spatial variation in terrain (e.g. seafloor complexity and relief) can modify the distribution of ecosystems and topographically complex features, across seascapes (Goes et al., 2019; Ismail et al., 2018; Wicaksono et al., 2019). These three‐dimensional terrain features alter the hydrodynamic properties of seascapes through their effects on currents, tides and waves (Genin, 2004; Harris et al., 2018; Rogers, Maticka, et al., 2018) and provide fish with important refuges from predation, feeding areas and spawning zones (Bouchet et al., 2017; Farmer et al., 2017; Pirtle et al., 2017).…”

A Novel GIS-Based Approach for Automated Detection of Nearshore Sandbar Morphological Characteristics in Optical Satellite Imagery

“…The study suggests a new approach based on the Relative Bathymetric Position Index (RBPI) and a combination of data processing and filtering operations designed specifically for the purpose. The Bathymetric Position Index has been widely used with bathymetric datasets for various coastal and marine applications [94][95][96][97][98][99][100][101][102][103], including sandbar extraction in the bathymetric LiDAR dataset [26], but the idea of using this metric in remote sensing images without derived bathymetry to our knowledge has never been explored before. This article illustrates that with a newly designed methodology, RBPI is suitable to discriminate nearshore morphology in non-bathymetric remote sensing images.…”

Marine spatial planning

“…Com vistas ao ordenamento das atividades/usos do espaço marinho da região Sul do Brasil, Gandra (2020) propõe uma abordagem para definição de unidades ambientais marinhas e áreas prioritárias para gestão. Destacam-se para a atividade de pesca, independentemente de sua modalidade, algumas pesquisas no contexto de PEM Fonseca et al, 2017;; bem como, levantamentos e mapeamentos de fundo (Goes et al, 2019;Mattos et al, 2018;Gorman et al, 2017;Maia & De Alencar Castro (2015) e diagnósticos sobre a distribuição e ocorrência de espécies Pinheiro et al, 2019;Patrizzi & Dobrovolski (2018); Cruz et al, 2015) que podem, posteriormente, orientar esforços de conservação e uso sustentável do espaço marinho brasileiro. Acrescenta-se ainda, estudos nacionais que orientam para a integração das mudanças climáticas no desenvolvimento do PEM (Patrizzi & Dobrovolski;.…”