Abstract
Subtidal natural hard substrates (SNHS) promote occupancy by rich benthic communities that provide irreplaceable and fundamental ecosystem functions, representing a global priority target for nature conservation and recognised in most European environmental legislation. However, scientifically validated methodologies for their quantitative spatial demarcation, including information on species occupancy and fine-scale environmental drivers (e.g., the effect of stone size on colonisation) are rare. This is, however, crucial information for sound ecological management. In this investigation, high-resolution (1 m) multibeam echosounder (MBES) depth and backscatter data and derivates, underwater imagery (UI) by video drop-frame, and grab sediment samples, all acquired within 32 km2 of seafloor in offshore Belgian waters, were integrated to produce a random forest (RF) spatial model, predicting the continuous distribution of the seafloor areal cover/m2 of the stones’ grain sizes promoting colonisation by sessile epilithic organisms. A semi-automated UI acquisition, processing, and analytical workflow was set up to quantitatively study the colonisation proportion of different grain sizes, identifying the colonisation potential to begin at stones with grain sizes Ø ≥ 2 cm. This parameter (i.e., % areal cover of stones Ø ≥ 2 cm/m2) was selected as the response variable for spatial predictive modelling. The model output is presented along with a protocol of error and uncertainty estimation. RF is confirmed as an accurate, versatile, and transferable mapping methodology, applicable to area-wide mapping of SNHS. UI is confirmed as an essential aid to acoustic seafloor classification, providing spatially representative numerical observations needed to carry out quantitative seafloor modelling of ecologically relevant parameters. This contribution sheds innovative insights into the ecologically relevant delineation of subtidal natural reef habitat, exploiting state-of-the-art underwater remote sensing and acoustic seafloor classification approaches.
Highlights
Rx beam spacing was set in high-density equidistant geometry, and sound emitted at pulse length of 150 μs in multibeam echosounder (MBES) normal mode
= 2110) that was consistently uncolonised by epilithic fauna across the five video transects, that was consistently uncolonised by epilithic fauna across the five video transects, the the proportions of colonised coarse gravel (NDS = 5986), cobbles (NDS = 1492), boulders proportions of colonised coarse gravel (NDS = 5986), cobbles (NDS = 1492), boulders (NDS = 49), and large boulders (NDS = 2) significantly differed (
Future tests based on this predictive modelling approach may benefit from the use of random forest (RF) for quantile regression, having the potential to improve the uncertainty reporting by exploiting lower and upper quartiles as confidence around the mean predictions [66]. The results of this investigation show that the acquisition, processing, and analysis of underwater seafloor imagery data provide seafloor mappers with quantitative and ecologically relevant information on the distribution of subtidal natural hard substrates
Summary
Subtidal natural hard substrates (SNHS), whether of geogenic or biogenic origin, represent an important ecological habitat and cover essential functions in marine ecosystems [1], making them a worldwide priority target for environmental management, conservation, and restoration. Structural complexity at various scales enhances bentho-pelagic coupling, and subsequently, the associated ecological succession phases by acting as settling, shelter, feeding, and nursery grounds for a variety of marine organisms at multiple trophic levels [1,2]. In an anthropogenically threatened and rapidly changing marine environment [3,4], the heterogeneous and scattered distribution of SNHS represents keystone. SNHS-associated biological communities are regarded as rich (in terms of diversity, biomass, and species rarity) yet fragile environments, with low resistance and resilience to anthropogenic disturbance. While all European legislation, e.g., [10,11]
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