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.
Located in
Library
/
RBINS Staff Publications 2021
We investigated the use of multisensory satellite data to determine long-term changes in surface chlorophyll concentrations using a 19-year (1998–2016) time series of chlorophyll data in the Danish Kattegat region of the Baltic Sea. Merged satellite estimates (SeaWiFS-MODIS/Aqua-MERIS-VIIRS) were compared with in situ ship based time series from four monitoring stations situated with increasing distance from land and nutrient sources. In situ and satellite derived estimates showed similar trend in chlorophyll with several fold higher values closer to land. Satellites aligned very well with in situ estimates in the open water stations but showed significant differences in magnitude and inter-annual variability, in particular in shallow coastal waters. Some systematic deviation was observed with satellite underestimating the growing season average for the earlier periods (1998–2002) and overestimating for the later period (2012–2016) compared to in situ estimates. Comparing growing season chlorophyll means over the 19 year period showed increasing magnitude and variability in nearshore and shallower areas, most pronounced for the satellite derived chlorophyll. Satellites overestimated chlorophyll in nearshore areas 2–4 fold, despite excluding shallow nearshore areas with possible benthic interferences from the analyses. This bias needs further validation and requires correction to improve the overall applicability of satellites for long-term monitoring of chlorophyll in the Kattegat region. From analysis of normalized data, we developed a simple correction model, which reduced deviations considerably between methods, underlying the importance of in situ data for application of satellite observations. While significant deviations were observed from in situ data, satellites are clearly advantageous in the much higher temporal and high spatial coverage they provide. Multisensory satellites can, however, not be used currently as a standalone technique for long-term assessment of chlorophyll. They require validation with in situ measurements, which provide essential data for calibration, validation and correction of satellite based estimates. A complementary use of multisensory satellite and in situ measurements therefore remains essential to assess trends in the ecological status of optically complex waters such as the Kattegat region of the Baltic Sea.
Located in
Library
/
RBINS Staff Publications 2022
