Review and meta-analysis of the importance of remotely sensed habitat structural complexity in marine ecology. (5th April 2020)

• Record Type: Journal Article
• Authors: Pygas, Daniel R.; Ferrari, Renata; Figueira, Will F.
• Is Part Of: Estuarine, coastal and shelf science. Volume 235(2020)
• Publication Date: 2020-04-05
• Subjects: Habitat structural complexity -- Remote sensing -- Meta-analysis -- Rugosity -- Fish -- Invertebrates; Estuarine oceanography -- Periodicals; Coasts -- Periodicals; Estuarine biology -- Periodicals; Seashore biology -- Periodicals; Coasts; Estuarine biology; Estuarine oceanography; Seashore biology; Periodicals; 551.461805
• DOI: 10.1016/j.ecss.2019.106468
• Languages: English
• ISSNs: 0272-7714

Abstract

Abstract: Habitat structural complexity is a key determinant of the distribution of marine biota. It mediates several abiotic and biotic processes and provides resources including shelter from prey and water current and a surface for attachment and growth. Recent studies based on remote sensing have examined the influence of various measures of complexity on a range of marine biota, though until now there has been no attempt to review and synthesise the findings. This review and meta-analysis of 51 studies developed a standardised rank-based scoring metric (Rs1-10 ) that enabled meaningful comparisons of the influence of various measures of complexity and other predictors across these disparate studies. While measures of terrain variability and morphology were important, often in site- and species-specific circumstances, other predictors, including derivatives of hydroacoustic backscatter, abiotic and biotic habitat descriptors, and relative geographic location often outperformed measures of complexity. Of note, Rs1-10 identified surface rugosity, one of the most well-known, utilised and conceptualised measures of complexity, to be of the poorest performing predictors. Explanations for the generally poor performance of measures of complexity included the ability of other predictors to act as broad surrogates of other structuring environmental gradients, the ecological relevance of measures, and whether they capture complexity too broad or specific for the target organism, in addition to the potentially confounding role of spatial extent and resolution. Having been identified, such considerations provide opportunities for improved design and implementation of the next generation of remote sensing studies with improved potential for the conservation of biodiversity and management of marine resources. In particular, those based on photogrammetry, which can capture high resolution 3D models of the seafloor over extents far greater than that achievable using in-situ diver methods.